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pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"},"responsivegrid":{"columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 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ensuring a workload performs its\nintended function correctly and consistently, recovering from failures\nto meet business and regulatory demands. This involves architecting for\nhigh availability and fault tolerance, ensuring the resiliency of both\nthe service and the data itself, and operationalizing plans for business\ncontinuity and disaster recovery. The goal is to build a data platform\nthat is optimally designed to recover from failure and also meet\nfluctuating demand.\u003C/p\u003E\n","\u003Ch2\u003EPrinciples\u003C/h2\u003E\n","\u003Ch3\u003EEnsure data is trustworthy and correct\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EReliability in the AI Data Cloud is ultimately defined by the\ntrustworthiness of the data itself. This principle prioritizes data\nquality, integrity, and correctness as the ultimate measure of a\nreliable system, because business decisions depend on accurate and\ncomplete data.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EDesign systems to anticipate and withstand failure\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EA reliable system is designed with the assumption that failures will\noccur. This principle involves building for high availability, fault\ntolerance, and resiliency at every layer, from data storage,\ningestion, and transformation pipelines, to AI and BI workloads, to\nminimize the impact of disruptions.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EAutomate recovery and operations to reduce human error\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EManual processes are a common source of failure and slow down\nrecovery. This principle advocates for automating operational tasks,\nrecovery procedures, and change management to ensure consistent,\nrepeatable, and rapid responses to both planned and unplanned events.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EContinuously test and validate recovery procedures\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EA recovery plan is only reliable if it is proven to work. This\nprinciple mandates the regular testing of business continuity and\ndisaster recovery plans through drills and simulations, ensuring that\nboth the technology and the operational procedures are effective when\na real incident occurs.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EClearly define and operationalize shared responsibilities\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EReliability is a shared effort between the cloud provider, Snowflake,\nand the customer. This principle emphasizes the importance of\nunderstanding, documenting, and operationalizing the specific\nresponsibilities at each layer to ensure there are no gaps in\nownership for achieving end-to-end reliability.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch2\u003ERecommendations\u003C/h2\u003E\n","\u003Cp\u003EThe following key recommendations are covered within each principle of\nReliability:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EReliability Strategy & Governance\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EShared Responsibility Model\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESLA & Regulatory Compliance\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EInherited Controls\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EResource Monitoring & Quotas\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EImmutable Snapshots (WORM) & Archival Storage\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EHigh Availability & Fault Tolerance\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EAvailability Zones\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELifecycle Management (Version Upgrades & Planned Downtime)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EAutomatic Query Retries\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EError Handling\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData & Object Resiliency\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EData Resiliency (Streams, Tasks, Database, Stored Procedure, UDF,\nPolicy, Object Tag Replication)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EAccount Object Resiliency (Roles, Users, Warehouse, Resource Monitor\nReplication)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ETime Travel\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFail-safe\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESnowsight Objects (Notebooks & Worksheets)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EData Recovery\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EResilient Data Pipelines\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EPipeline Object Replication (Snowpipe, Stages, File Formats)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIdempotent Pipeline Integration (External Volume, Multi-location\nStorage/Notification)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELoad History Replication\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EExactly Once Delivery without Data Loss\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EMonitoring & Operations\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EMonitoring, Alerting & Observability\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EResource Monitoring & Quotas\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EBusiness Continuity Planning & Testing\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDisaster Recovery\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003EReplication & Failover Groups\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClient Redirect\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFailover Commands (UI & SQL)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EBackup & Replication\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EReliability strategy & governance\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EReliability Strategy & Governance establishes the foundational framework\nfor making informed decisions about your data platform's resilience. It\ninvolves defining \u003Cem\u003Eclear responsibilities\u003C/em\u003E, setting \u003Cem\u003Emeasurable\nreliability targets\u003C/em\u003E, and aligning technical architecture with business,\nfinancial, and regulatory requirements. This strategic planning ensures\nthat all subsequent reliability efforts are purposeful and directly\nsupport your organization's goals.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing a sound reliability strategy and governance model, your\norganization achieves clear alignment between business objectives,\ntechnical capabilities, and financial investments. This proactive\napproach reduces operational and regulatory risk, ensures predictable\nperformance, and fosters a culture of shared ownership for reliability\nacross teams. You can confidently claim that your reliability posture is\nnot merely a technical function but a strategic capability, governed by\nclear policies and designed to meet specific business, financial, and\ncompliance mandates.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EShared Responsibility Model\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThe Shared Responsibility Model is a framework that delineates the\ndistinct reliability duties between the cloud provider (e.g., AWS,\nAzure, GCP), Snowflake, and you, the customer. Its importance lies in\ncreating clarity and preventing gaps in ownership, ensuring that every\naspect of reliability—from physical data center security to the code in\nyour data pipelines—is explicitly accounted for. We recommend you\nformally document and socialize this model within your organization,\nmapping specific internal roles and teams to the responsibilities\ndesignated to the customer. This ensures clear accountability for tasks\nsuch as data governance, workload management, and business continuity\nplanning.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESLA & regulatory compliance\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThis involves understanding both your contractual uptime commitments via\nthe Snowflake Service Level Agreement (SLA) and the mandatory legal and\nindustry regulations that govern your data, such as DORA for financial\nservices or HIPAA for healthcare. A key aspect of this is leveraging the\nplatform's agility to support flexible SLAs for different Lines of\nBusiness (LoB). Not all workloads share the same criticality;\nSnowflake's architecture allows you to apply stringent,\nhigh-availability configurations and replication strategies only to the\nmost critical LoBs, while using more cost-effective approaches for less\ncritical workloads. Adherence across all levels is critical to avoid\nsignificant financial penalties, operational disruption, and\nreputational damage. We recommend you review\nthe(\u003Ca href=\"/en/legal/\"\u003E<u>/en/legal/</u>\u003C/a\u003E),\nidentify all applicable regulations, and map these requirements to\nspecific Snowflake features and operational procedures to create an\nauditable compliance trail that reflects the unique needs of each\nbusiness unit.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EInherited controls\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThis allows you to leverage Snowflake's existing third-party\ncertifications, such as HITRUST or FedRAMP, to accelerate your own\ncompliance and audit processes. This is a powerful advantage, as it\nsignificantly reduces the time, cost, and effort required to demonstrate\nthat your data platform meets stringent security and reliability\nstandards. We recommend you engage your compliance and security teams to\nreview the reports available on the(\n\u003Ca href=\"https://trust.snowflake.com/\"\u003E<u>https://trust.snowflake.com/</u>\u003C/a\u003E).\nYou should use the HITRUST Shared Responsibility Matrix to formally\ndocument which controls you inherit from Snowflake, streamlining your\naudit preparations and demonstrating due diligence.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EResource monitoring & quotas\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EWhile Snowflake provides virtually unlimited and readily available\ncompute, its consumption must be governed to ensure platform\nreliability. Resource Monitors are a critical governance control for\nmanaging credit consumption by setting quotas on virtual warehouses and\nthe account as a whole. Their importance to reliability is profound:\nthey act as a crucial safety net to prevent runaway queries or\nmisconfigured workloads from exhausting compute resources, which could\notherwise lead to performance degradation or service disruptions for\ncritical business processes. We recommend you assign a Resource Monitor\nto all production virtual warehouses with clearly defined credit quotas.\nYou should configure these monitors to send notifications at various\nconsumption thresholds and to automatically suspend the warehouse if the\nquota is exceeded, thereby protecting your critical workloads and\nensuring predictable platform performance.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImmutable snapshots (WORM) & archival storage\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThis area addresses the need to meet strict regulatory requirements for\ndata retention and legal holds, where data must be stored in a\nnon-erasable, non-rewritable format (Write-Once, Read-Many, or WORM).\nWhile Snowflake's native Time Travel and Fail-safe features provide\npowerful short-term data protection, certain regulations require\nlonger-term, provably immutable storage. For data subject to these\nstringent requirements, we recommend leverage Snowflake Snapshots to\nperiodically create immutable backups of your tables, schemas and\ndatabases.. This process should be documented thoroughly to provide a\nclear audit trail for regulatory bodies.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImplement the Shared Responsibility Model:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EDownload and review the\n\u003Ca href=\"/en/resources/report/snowflake-shared-responsibility-model/\"\u003E<u>whitepaper</u>\u003C/a\u003E.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a RACI (Responsible, Accountable, Consulted, Informed) chart\nthat maps your internal teams (e.g., Data Engineering, Security,\nFinance, Application Owners) to each of the "Customer"\nresponsibilities.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIncorporate this chart into your team onboarding and operational\nrunbooks.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESet up Demand Management Controls:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EUse the \u003Ccode\u003ECREATE RESOURCE MONITOR\u003C/code\u003E command to establish credit quotas\nfor warehouses or the entire account.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EConfigure the monitor to trigger notifications or suspend warehouses\nat specific consumption thresholds (e.g., \u003Ccode\u003ENOTIFY AT 75 PERCENT\u003C/code\u003E,\n\u003Ccode\u003ESUSPEND_IMMEDIATE AT 95 PERCENT\u003C/code\u003E).\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EPerform Basic Capacity Planning:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EExecute queries against the\n\u003Ccode\u003ESNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY\u003C/code\u003E view to analyze\ncredit consumption over time.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIdentify daily, weekly, or monthly peak usage patterns to inform\nwarehouse sizing and scaling policy decisions.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nimplementing a comprehensive reliability strategy and governance model:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EStakeholder alignment:\u003C/strong\u003E Have you identified and engaged key\nstakeholders from business, finance, and technology to contribute to\nthe reliability strategy?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBusiness requirements:\u003C/strong\u003E Have you conducted a Business Impact\nAnalysis to define clear availability and recovery targets (SLOs, RTO,\nRPO) for your critical workloads?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERegulatory landscape:\u003C/strong\u003E Have you identified and documented all\nindustry-specific and geographical regulations (e.g., DORA, HIPAA,\nGDPR) that apply to your data?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFinOps maturity:\u003C/strong\u003E Does your organization have a defined FinOps team\nor function responsible for cloud financial management and cost\ngovernance?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EOwnership:\u003C/strong\u003E Have you assigned clear ownership for each of the\ncustomer responsibilities outlined in the Shared Responsibility Model?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EHigh availability & fault tolerance\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EHigh Availability (HA) and Fault Tolerance are the architectural\ncornerstones that ensure your data platform remains operational and\naccessible, even in the face of component failures or planned\nmaintenance. This involves leveraging Snowflake’s inherently resilient\narchitecture, which is distributed across multiple availability zones,\nand designing workloads that can gracefully handle transient errors. A\nwell-architected system minimizes downtime and provides a consistent,\nreliable experience for your users and applications.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing best practices for High Availability and Fault\nTolerance, your organization achieves continuous operations for its\ncritical data workloads, enhancing user trust and business productivity.\nThis design philosophy protects your business processes from localized\ninfrastructure failures, transient network issues, and planned platform\nupdates, ensuring consistent and predictable performance. After\nimplementing these recommendations, you can claim that your data\nplatform is architected for continuous availability, providing a\nresilient foundation for your data-driven applications.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAvailability Zones\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ESnowflake’s architecture is natively designed for high availability by\ndistributing its service across three independent Availability Zones\n(AZs) within a cloud provider's region. This built-in redundancy is\nfundamental to the platform's resilience, as it ensures that the failure\nof a single data center does not impact the availability of your data or\nthe service as a whole. We recommend you rely on Snowflake’s intrinsic\nmulti-AZ architecture for intra-region high availability, as this fault\ntolerance is managed automatically without requiring any customer\nconfiguration. For workloads that require an even higher level of\navailability beyond a single region, you should complement this native\nHA with a multi-region or multi-cloud disaster recovery strategy.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ELifecycle management (version upgrades & planned downtime)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ESnowflake manages platform updates through a process of weekly,\nnon-disruptive releases, which are deployed transparently with zero\ndowntime for your workloads. This approach is critical for maintaining a\nhigh-availability posture, as it eliminates the need for\ncustomer-managed maintenance windows that would otherwise interrupt\nservice. We recommend you leverage Snowflake's zero-downtime upgrades\nfor your production accounts to ensure continuous operations. For\ncustomers with Enterprise Edition or higher, we advise designating\nnon-production accounts for \u003Ca href=\"https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/intro-releases%23early-access-to-full-releases\"\u003E<u>early access to new\nreleases</u>\u003C/a\u003E\nto test for potential impacts on critical workloads before the\nproduction rollout.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAutomatic query retries\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThe Snowflake platform is designed to be fault-tolerant by automatically\nretrying certain query failures that occur due to transient,\nintermittent issues within the service, such as a temporary network\nfailure or a faulty compute instance. This built-in mechanism is\nimportant because it transparently handles temporary platform failures,\npreventing them from becoming user-facing errors and improving the\noverall reliability of your workloads. We recommend you rely on the\nnative automatic query retry feature to handle transient platform\nissues, which simplifies your application logic. For custom data\npipelines, you should supplement this by implementing your own retry\nlogic for failures outside the scope of automatic retries, such as using\nthe RETRY LAST option for a failed task graph.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EError handling\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ERobust error handling involves designing a centralized framework to\ncapture, log, and manage exceptions from all workloads, not just data\nloading. This is crucial for creating observable and resilient systems,\nas it provides a single source of truth for identifying, analyzing, and\nresponding to failures from any process, including data pipelines,\nstored procedures, or UDFs. We recommend you implement a standardized\nerror logging pattern, such as writing exceptions to a dedicated event\ntable. This approach ensures that all failures are captured\nconsistently, enabling automated alerting and providing a comprehensive\naudit trail for root-cause analysis and remediation.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EVerify Your Snowflake Release:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ETo check the current release version of your account, execute the\nfollowing SQL command: SELECT CURRENT_VERSION();\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EReview the monthly behavior change logs to stay informed of upcoming\nupdates.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImplement Centralized Error Handling:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a standardized event table to log errors from various\nsources:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE TABLE my_event_table (\n  event_timestamp TIMESTAMP_LTZ,\n  error_source VARCHAR,\n  error_code VARCHAR,\n  error_message VARCHAR\n);\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EWithin your custom procedures or data pipelines, use a \u003Ccode\u003ETRY...CATCH\u003C/code\u003E\nblock to log exceptions to this central table before re-throwing the\nerror.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ESet up a Snowflake Alert to monitor the event table for new entries\nand trigger a notification, enabling proactive response to any\nfailure in your system.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERetry a Failed Task Graph:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIf a root task in a dependency tree fails, you can restart the run\nfrom the point of failure.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EExecute the following command, which will only re-run the failed\ntask and any of its downstream children: \u003Ccode\u003EEXECUTE TASK my_root_task RETRY LAST;\u003C/code\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nHigh Availability and Fault Tolerance:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERegional failure planning:\u003C/strong\u003E Have you confirmed that your business\ncontinuity plan addresses inter-region failure, given that\nintra-region HA is handled by Snowflake?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EChange management:\u003C/strong\u003E Do you have a process to review Snowflake's\nmonthly behavior change logs to proactively identify potential impacts\non your workloads?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EApplication logic:\u003C/strong\u003E Are your custom applications and ETL/ELT tools\nprepared to handle non-transient errors that are not automatically\nretried by Snowflake?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData quality feedback loop:\u003C/strong\u003E Do you have an automated process for\nreviewing, remediating, and reporting on records that were skipped or\nrejected during data loading?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EData & object resiliency\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EData and Object Resiliency provides critical safeguards against logical\ndata corruption, accidental deletion, or unauthorized changes, ensuring\nthe integrity of your data and the stability of your operational\nenvironment. This involves leveraging native Snowflake features like\nTime Travel for instant point-in-time recovery and object replication to\nprotect both your data and the account configurations that govern it.\nThe goal is to enable rapid, granular recovery from common operational\nfailures without invoking a full disaster recovery plan.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing a robust Data and Object Resiliency strategy, your\norganization significantly reduces the risk and impact of common\noperational failures, such as human error or application bugs. This\nensures the integrity of your critical data assets and the stability of\nyour governance and security posture, allowing you to confidently meet\noperational recovery objectives and minimize data-related incidents.\nAfter implementing these recommendations, you can claim that your data\nplatform is resilient to logical corruption and that you can restore\nboth data and critical account configurations to a known good state in\nminutes.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData resiliency (Streams & Tasks replication)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EData Resiliency focuses on replicating not just the data but also the\ndatabase-level objects that give it context and automate its lifecycle.\nThis is paramount because a replicated database is of limited use if the\nautomated pipelines that populate it or the governance policies that\nprotect it are missing upon recovery. We recommend that a failover group\nalways include schemas containing policy and pipeline objects - such as\nStreams, Tasks, and UDFs - to ensure that your data automation and\ngovernance logic is synchronized with your data, providing a complete\nand functional replica that can be activated quickly.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAccount \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-time-travel\"\u003E<u>object\nresiliency</u>\u003C/a\u003E\n(roles & users replication)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EUse \u003Cstrong\u003Efailover groups\u003C/strong\u003E to replicate databases \u003Cstrong\u003Eand\u003C/strong\u003E account objects\nlike users, roles, warehouses with point‑in‑time consistency.This is\ncrucial for operational continuity, as your security framework (roles\nand users) and compute configurations (warehouses) are essential to\nmaking your data accessible and usable after a failover. We recommend\nyou replicate all critical account-level objects to your secondary\naccount using an FailoverGroup to ensure your security posture and\noperational configurations are available immediately, preventing delays\nand security gaps during a recovery event.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETime Travel\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ESnowflake \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-time-travel\"\u003E<u>Time\nTravel</u>\u003C/a\u003E\nallows you to access historical versions of table data at any point\nwithin a defined retention period, which can be configured for up to 90\ndays. This feature is your first and fastest line of defense against\nlogical data corruption, such as accidental \u003Ccode\u003EUPDATE\u003C/code\u003E or \u003Ccode\u003EDELETE\u003C/code\u003E statements,\nas it enables instant, surgical recovery without restoring from\ntraditional backups. We recommend you configure an appropriate\n\u003Ccode\u003EDATA_RETENTION_TIME_IN_DAYS\u003C/code\u003E for all critical production tables,\nbalancing your recovery needs with storage costs, and leverage the\nextended 90-day retention available in Enterprise Edition for your most\ncritical data assets.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFail-safe\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EFail-safe provides a non-configurable, 7-day data recovery period that\nbegins immediately after the Time Travel retention period ends. It is a\nlast-resort recovery service, managed by Snowflake, designed to protect\nagainst catastrophic data loss from extreme operational failures. We\nrecommend you rely on Fail-safe as a final safety net and not as part of\nyour standard operational recovery procedures. Understand that recovery\nfrom Fail-safe is initiated via Snowflake Support; your primary and most\nimmediate recovery tool should always be Time Travel.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData recovery\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EData recovery is the practice of restoring data after an incident, which\nin Snowflake primarily involves using \u003Ccode\u003EUNDROP\u003C/code\u003E commands or querying\nhistorical data via Time Travel. Having a clear, documented, and tested\nprocess for these actions is essential to executing them quickly and\ncorrectly during a high-stress incident. We recommend you develop and\ndocument specific operational runbooks for common data recovery\nscenarios, such as restoring a dropped table using \u003Ccode\u003EUNDROP\u003C/code\u003E or correcting\na faulty data load using Time Travel's \u003Ccode\u003EAT | BEFORE\u003C/code\u003E clause, and\nregularly test these procedures.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EUse Time Travel to Correct an Error:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIdentify the query ID of the erroneous DML statement from the query\nhistory.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ERe-insert the correct data by querying the table from a point in\ntime before the error occurred:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EINSERT INTO\n    my_table\nSELECT\n    *\nFROM\n    my_table BEFORE(STATEMENT => '<query_id_of_bad_dml>');\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERestore a Dropped Object:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ETo restore a recently dropped table, simply execute the\n\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/undrop-table\"\u003E<u>\u003Ccode\u003EUNDROP\u003C/code\u003E</u> command\u003C/a\u003E:\n\u003Ccode\u003EUNDROP TABLE my_table\u003C/code\u003E;\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EThis command also works for schemas and databases.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EConfigure Extended Data Retention:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EFor critical production databases, set the Time Travel window to its\nmaximum value (requires Enterprise Edition or higher).\u003C/p\u003E\n","\u003Cp\u003EExecute the command:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EALTER DATABASE my_prod_db\nSET DATA_RETENTION_TIME_IN_DAYS = 90;\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nData and Object Resiliency:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData retention policy:\u003C/strong\u003E Have you defined the required data\nretention period for each critical table based on business\nrequirements and balanced it against storage costs?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EObject replication scope:\u003C/strong\u003E Have you identified all critical account\nand database objects (including roles, users, tasks, and policies)\nthat need to be included in replication groups?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERecovery runbooks:\u003C/strong\u003E Are your operational runbooks for common\nrecovery scenarios (e.g., \u003Ccode\u003EUNDROP\u003C/code\u003E, Time Travel query) documented,\naccessible, and regularly tested?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETable type strategy:\u003C/strong\u003E Have you evaluated the use of \u003Ccode\u003ETRANSIENT\u003C/code\u003E\ntables for staging data to optimize storage costs by opting out of\nFail-safe protection? Furthermore, have you considered using \u003Ccode\u003ETEMPORARY\u003C/code\u003E\ntables for session-specific, intermediate data that requires no\nrecovery whatsoever, providing an additional layer of cost and\nperformance optimization?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EResilient data pipelines\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EResilient Data Pipelines are the automated processes that reliably move\nand transform data from source to destination, engineered to withstand\nand recover from failures. This involves architecting for idempotency,\nensuring end-to-end data integrity, and replicating the pipeline's\ncomponents and state. The goal is to create a robust, self-healing data\nflow that consistently delivers timely and accurate data for analysis.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing resilient data pipelines, your organization builds trust\nin its data delivery systems, reduces operational overhead, and\naccelerates time-to-insight. This ensures that your data pipelines are\nnot brittle, but are robust systems that can automatically recover from\ntransient errors, prevent data duplication, and guarantee data\ncorrectness. After implementing these recommendations, you can claim\nthat your data lifecycle is managed by a reliable, automated, and\nfault-tolerant framework that consistently delivers high-quality data to\nthe business.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EPipeline object replication (Snowpipe, stages, file formats)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EPipeline Object Replication involves replicating the configuration and\nmetadata of data ingestion components—such as Snowpipes, external and\ninternal stages, and file formats—to a secondary account. This is\ncritical for business continuity because a replicated database is of\nlimited value if the mechanisms to load new data into it are unavailable\nafter a failover. We recommend you include all production Snowpipe,\nStage, and File Format objects in your replication groups alongside\ntheir target databases to ensure a fully functional and ready-to-use\ndata ingestion capability in your secondary account. Furthermore, you\nshould periodically validate that the required permissions are granted\non these replicated objects to prevent access issues post-failover.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIdempotent pipeline integration\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EAn idempotent pipeline is one where re-running an operation multiple\ntimes with the same input produces the same result, preventing data\nduplication or corruption. This architectural principle is paramount for\nbuilding reliable, self-healing pipelines, as it allows you to safely\nretry failed jobs without introducing data integrity issues. We\nrecommend you design all data loading and transformation logic to be\nidempotent, for example by using \u003Ccode\u003EMERGE\u003C/code\u003E statements instead of simple\n\u003Ccode\u003EINSERT\u003C/code\u003E statements. For streaming data, you should leverage features that\nprovide exactly-once semantics to ensure each event is processed\nprecisely one time.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ELoad history replication\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ELoad History Replication specifically replicates the metadata of files\ningested via Snowpipe to a secondary account. This is a crucial, yet\noften overlooked, component of a resilient data pipeline, as it prevents\nthe re-ingestion of already-processed files after a failover. Without\nthis history, a Snowpipe in a newly promoted primary account would\nre-process all existing files in a stage, leading to significant data\nduplication. Load History is automatically replicated as part of the\ndatabase that is being replicated in a failover group.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EExactly once delivery without data loss\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EAchieving exactly-once delivery is the gold standard for critical data\npipelines, guaranteeing that every record is processed precisely one\ntime, even in the face of failures and retries. This ensures the highest\nlevel of data integrity by preventing both data loss and data\nduplication, which is non-negotiable for financial reporting, regulatory\ncompliance, and other sensitive use cases. We recommend you combine\nidempotent DML logic, transactional controls, and robust error handling\nto architect pipelines that achieve exactly-once semantics. For\nreal-time ingestion, we advise using \u003Ca href=\"https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/snowpipe-streaming-overview\"\u003E<u>Snowpipe\nStreaming</u>\u003C/a\u003E,\nwhich is designed to provide these guarantees out of the box.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAdd a Pipe to a failover group:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIdentify the database and schema containing the pipe you wish to\nreplicate.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUse the \u003Ccode\u003EALTER FAILOVER GROUP\u003C/code\u003E command to add the pipe's parent\nobjects to the group:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EALTER FAILOVER GROUP my_fg\nADD my_db.my_schema.my_pipe TO REPLICATION_SCHEDULE;\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EWrite an Idempotent\n\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/merge\"\u003E<u>MERGE</u>\u003C/a\u003E\nstatement:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EUse a \u003Ccode\u003EMERGE\u003C/code\u003E statement to either insert new rows or update existing\nrows based on a unique key, preventing duplicates on re-run.\u003C/p\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EMERGE INTO target t\n  USING source s\n  ON t.id = s.id\n  WHEN MATCHED THEN UPDATE SET t.value = s.value\n  WHEN NOT MATCHED THEN INSERT (id, value) VALUES (s.id, s.value);\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECheck Snowpipe load history:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ETo validate that files have been loaded and to check for errors,\nuse the\n\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/copy_history\"\u003E<u>\u003Ccode\u003ECOPY_HISTORY\u003C/code\u003E</u>\u003C/a\u003E\nfunction.\u003C/p\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT\n  *\nFROM TABLE(INFORMATION_SCHEMA.COPY_HISTORY(\n              TABLE_NAME=>'my_table',\n              START_TIME=>DATEADD(hours, -1, CURRENT_TIMESTAMP())\n          ));\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nbuilding resilient data pipelines:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EPipeline inventory:\u003C/strong\u003E Have you identified and inventoried all\ncritical data pipelines and their constituent objects (pipes, stages,\ntasks, streams) that need to be made resilient?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIdempotency review:\u003C/strong\u003E Have you audited your existing ETL/ELT scripts\nto ensure they are idempotent and will not cause data duplication if\nretried?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EError handling strategy:\u003C/strong\u003E Do you have a defined process for\nhandling files or records that consistently fail to load (a\n"dead-letter queue" strategy) to prevent them from blocking the entire\npipeline?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDependency mapping:\u003C/strong\u003E For complex, multi-step pipelines using Tasks,\nhave you mapped all dependencies to ensure they are replicated and\nwill execute in the correct order after a failover?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EMonitoring & operations\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EMonitoring and Operations is the practice of maintaining the health,\nperformance, and reliability of your data platform in production. It\ninvolves establishing comprehensive observability into system behavior,\nimplementing proactive controls to manage resource consumption, and\noperationalizing your business continuity plans through rigorous\ntesting. A mature operational posture enables you to move from a\nreactive to a proactive state, identifying and mitigating issues before\nthey impact the business.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing a robust Monitoring and Operations strategy, your\norganization achieves a state of proactive control over its data\nplatform, leading to increased stability, predictable performance, and\noptimized costs. This approach minimizes the frequency and duration of\nservice disruptions, ensures that recovery plans are effective, and\nprovides the necessary visibility to manage resources efficiently. After\nimplementing these recommendations, you can claim that your data\nplatform is actively managed, fully observable, and that your\norganization is prepared to execute its business continuity plans with\nconfidence.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EMonitoring, alerting & observability\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThis practice involves gaining deep insights into the health and\nperformance of your Snowflake environment. While monitoring tells you\n\u003Cem\u003Ewhat\u003C/em\u003E is happening, observability helps you understand \u003Cem\u003Ewhy\u003C/em\u003E it's\nhappening, enabling rapid root-cause analysis. This is critical for\nproactively detecting anomalies, performance degradation, or data\npipeline failures. We recommend you leverage the SNOWFLAKE.ACCOUNT_USAGE\nschema for historical analysis of query performance and credit\nconsumption, and implement \u003Ca href=\"https://docs.snowflake.com/en/guides-overview-alerts\"\u003E<u>Snowflake\nAlerts</u>\u003C/a\u003E to\ntrigger timely, automated notifications for specific conditions,\nensuring your operations team is alerted to potential issues promptly.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EResource monitoring & quotas\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EResource Monitors are a critical governance control for managing credit\nconsumption by setting quotas on virtual warehouses and the account as a\nwhole. Their importance lies in preventing unexpected cost overruns from\nrunaway queries or misconfigured workloads and ensuring that compute\nresources are available for your most critical business processes. We\nrecommend you assign a\n\u003Ca href=\"https://docs.snowflake.com/en/user-guide/resource-monitors\"\u003E<u>resource-monitor</u>\u003C/a\u003E\nto all production virtual warehouses with clearly defined credit quotas\nthat align with your FinOps budgets. You should configure these monitors\nto send notifications at various consumption thresholds and to\nautomatically suspend the warehouse if the quota is exceeded, thereby\nproviding a crucial safety net for cost control and resource management.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBusiness Continuity planning & testing\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EA \u003Ca href=\"https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/business-continuity-disaster-recovery\"\u003E<u>Business\nContinuity</u>\u003C/a\u003E\nplan is a documented strategy outlining how your organization will\nmaintain critical functions during and after a disruption. However, a\nplan is only reliable if it is regularly tested. This practice is\nessential for validating your technical recovery procedures, building\noperational "muscle memory," and uncovering gaps in your strategy before\na real incident occurs. We recommend you formalize your Business\nContinuity and Disaster Recovery (BCDR) plans in accessible operational\nrunbooks. Crucially, you must establish a regular cadence for conducting\nDR drills—such as executing a failover of a non-production\nenvironment—to test your procedures, validate your RTO/RPO targets, and\nensure your operations team is prepared to respond effectively.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECreate a resource monitor:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EUse the \u003Ccode\u003ECREATE RESOURCE MONITOR\u003C/code\u003E command to define a credit quota and\nnotification thresholds.\u003C/p\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE RESOURCE MONITOR my_monitor \n  WITH CREDIT_QUOTA = 1000 \n  TRIGGERS ON 75 PERCENT DO NOTIFY \n           ON 90 PERCENT DO SUSPEND \n           ON 100 PERCENT DO SUSPEND_IMMEDIATE;\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EAssign the monitor to a warehouse:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003EALTER WAREHOUSE my_wh\n  SET RESOURCE_MONITOR = my_monitor;\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESet up a Snowflake Alert:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate an alert that checks for a specific condition on a schedule.\u003C/p\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ECREATE OR REPLACE ALERT long_running_query_alert WAREHOUSE = my_ops_wh SCHEDULE = '5 MINUTE'\n  IF (\n      EXISTS (\n          SELECT\n              1\n          FROM\n              SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY\n          WHERE\n              EXECUTION_STATUS = 'RUNNING'\n              AND START_TIME < DATEADD(hour, -1, CURRENT_TIMESTAMP())\n      )\n  ) THEN CALL SYSTEM $SEND_EMAIL(...)\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EResume the alert to activate it: \u003Ccode\u003EALTER ALERT long_running_query_alert RESUME;\u003C/code\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECheck for failed Tasks:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ETo monitor the operational health of your data pipelines, use the \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/task_history\"\u003E\u003Ccode\u003ETASK_HISTORY\u003C/code\u003E\u003C/a\u003E function.\u003C/p\u003E\n","\u003Cp\u003EExample:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode\u003ESELECT\n *\nFROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY(\n                 SCHEDULED_TIME_RANGE_START=>DATEADD('hour',-1,CURRENT_TIMESTAMP()),\n                 RESULT_LIMIT => 100\n           )\n         )\nWHERE STATE = 'FAILED';\n\u003C/code\u003E\u003C/pre\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nimplementing a mature Monitoring and Operations practice:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EObservability strategy:\u003C/strong\u003E Do you have a centralized dashboard for\nmonitoring key reliability metrics (e.g., query performance, warehouse\nutilization, data loading errors)?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAlerting channels:\u003C/strong\u003E Are your alert notification channels (e.g.,\nemail, PagerDuty) configured and integrated with Snowflake?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EQuota alignment:\u003C/strong\u003E Are your resource monitor quotas aligned with\nyour departmental budgets and FinOps strategy?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBCDR documentation:\u003C/strong\u003E Is your Business Continuity plan documented,\naccessible, and regularly reviewed by all relevant stakeholders?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETesting cadence:\u003C/strong\u003E Have you defined and committed to a schedule for\nconducting regular DR tests and "game day" exercises?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003EDisaster Recovery\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EDisaster Recovery (DR) is a critical component of a comprehensive\nreliability strategy, focused on restoring data and service in the event\nof a large-scale failure. Snowflake provides a multi-layered approach to\nDR, ensuring comprehensive protection is readily available. This begins\nwith automatic \u003Cstrong\u003ECross-Zone\u003C/strong\u003E recovery, where the platform transparently\nhandles an availability zone outage at no additional cost. For broader\nincidents, customers can implement \u003Cstrong\u003ECross-Region\u003C/strong\u003E DR to fail over to\nanother region, or even \u003Cstrong\u003ECross-Cloud\u003C/strong\u003E DR to fail over to an entirely\ndifferent cloud provider for the highest level of resilience. A\nwell-architected DR plan leverages these capabilities to minimize data\nloss and downtime, ensuring business continuity for your most critical\nworkloads. For a detailed overview of the concepts and features\ninvolved, refer to Snowflake’s documentation on \u003Ca href=\"https://docs.snowflake.com/en/user-guide/replication-intro\"\u003E<u>business continuity\nand disaster\nrecovery</u>\u003C/a\u003E.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing a robust Disaster Recovery (DR) strategy, your\norganization ensures business continuity for critical data workloads,\nprotecting against regional outages and minimizing data loss. This\nallows you to confidently meet stringent Recovery Time Objectives (RTO)\nand Recovery Point Objectives (RPO), maintain customer trust, and uphold\nregulatory obligations even in the face of a major disruption. After\nimplementing these recommendations, you can claim that your data\nplatform is resilient and your business is prepared for catastrophic\nfailures, with a tested and reliable plan to restore service.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFailover groups\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EFailover groups are the foundational Snowflake concept for implementing\na robust DR strategy. They allow you to group databases and critical\naccount objects—such as users, roles, and resource monitors—and\nreplicate them as a single, consistent unit to a secondary account in\nanother region or cloud. This is paramount for ensuring that not just\nyour data, but your entire operational environment, can be recovered\nwith point-in-time consistency after a disaster, thereby minimizing both\ndata loss (RPO) and recovery time (RTO). We recommend you group critical\ndatabases and their associated account objects into Failover Groups to\nensure they are replicated and failed over together, maintaining both\ntransactional and operational integrity. Furthermore, you should\nconfigure a frequent replication schedule for these groups, aligned with\nyour business requirements, to minimize your RPO.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EClient Redirect\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Ca href=\"https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/business-continuity-client-redirect\"\u003E<u>Client\nRedirect</u>\u003C/a\u003E\nis a feature that provides seamless, automated failover for your\napplications and users. It works via a connection object that\nautomatically reroutes client application traffic from a primary account\nto a secondary account after a failover has been initiated, without\nrequiring manual changes to connection strings. This feature The\nimportance of this feature cannot be overstated, as it dramatically\nsimplifies the recovery process and reduces your RTO by eliminating the\ncomplex and error-prone task of reconfiguring every client application\nduring an outage. To leverage this capability, we recommend you\nimplement a connection object with Client Redirect enabled for all\nproduction applications. It is also critical to ensure that all client\napplications are configured to use the single connection URL provided by\nthis object, rather than direct account URLs, to guarantee the automated\nredirection is effective.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EFailover commands (UI & SQL)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EExecuting a disaster recovery plan is ultimately controlled by specific\nfailover commands, which are available through both the Snowsight UI and\nSQL. These commands are used to promote a secondary failover group to\nbecome the primary, thereby formally initiating the failover process.\nHaving a clear, well-understood, and tested procedure for using these\ncommands is critical for a swift and successful recovery during a\nhigh-stress incident. We recommend you document the exact SQL failover\ncommands (e.g., \u003Ccode\u003EALTER FAILOVER GROUP... PRIMARY\u003C/code\u003E) in your operational\nrunbooks and grant the necessary privileges to a limited set of\nauthorized personnel to prevent accidental activation. Additionally,\nyour operations team should be familiarized with both the UI-based and\nSQL-based failover procedures as part of your regular DR testing to\nensure they can execute them efficiently under pressure.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBackup & replication\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EA comprehensive \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-cdp\"\u003E<u>data\nprotection</u>\u003C/a\u003E\nstrategy must address both large-scale disasters and more common\noperational failures. This is achieved by combining physical replication\nfor disaster recovery with logical backups for operational recovery.\nWhile cross-region replication is essential for surviving a regional\noutage, it is not a substitute for protecting against human error or\ndata corruption. Snowflake’s architecture provides powerful tools for\nboth scenarios. We recommend you complement your cross-region\nreplication strategy with a regular, automated process for creating\nzero-copy clones of critical databases. These clones serve as highly\nefficient, point-in-time logical backups that can be used for rapid\noperational recovery, development, and testing without incurring\nsignificant storage costs. You can alternatively leverage Snowflake\nSnapshots to periodically create and expire immutable backups. Finally,\nyou must verify that your backup and replication processes preserve your\nRole-Based Access Control (RBAC) and governance policies to ensure\nsecurity and compliance are maintained post-recovery.\u003C/p\u003E\n","\u003Ch3\u003EHow-To’s\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImplement Failover Groups:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIdentify critical databases and account objects (users, roles,\nwarehouses, etc.) required for business continuity.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/create-failover-group\"\u003E\u003Ccode\u003EFAILOVER GROUP\u003C/code\u003E\u003C/a\u003E in your primary account that includes these\nobjects.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a secondary \u003Ccode\u003EFAILOVER GROUP\u003C/code\u003E in your DR account as a replica\nand set a refresh schedule (e.g., \u003Ccode\u003EREPLICATION_SCHEDULE = '10 MININUTE'\u003C/code\u003E).\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EConfigure Client Redirect:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/sql/create-connection\"\u003E\u003Ccode\u003ECONNECTION\u003C/code\u003E\u003C/a\u003E object in your primary account.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEnable \u003Ca href=\"https://docs.snowflake.com/en/user-guide/client-redirect\"\u003E\u003Ccode\u003ECLIENT_REDIRECT\u003C/code\u003E\u003C/a\u003E for that connection object.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUpdate all client application connection strings to use the new\nconnection URL (e.g.,\n\u003Ccode\u003E<organization_name>-<connection_name>.snowflakecomputing.com\u003C/code\u003E).\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003E\u003Cstrong\u003EEstablish logical backup procedures:\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIdentify critical tables or databases that require frequent,\npoint-in-time backups for operational recovery.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECreate a Snowflake Task to automatically execute a \u003Ccode\u003ECREATE TABLE... CLONE\u003C/code\u003E statement on a defined schedule (e.g., daily).\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EImplement a data retention policy for these clones to manage storage\ncosts.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ETradeoffs & Considerations\u003C/h3\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nimplementing a disaster recovery strategy:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EBusiness impact analysis:\u003C/strong\u003E Have you identified your most critical\ndata workloads and quantified the business impact of an outage?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERTO/RPO definition:\u003C/strong\u003E Have you defined and documented the Recovery\nTime Objective (RTO) and Recovery Point Objective (RPO) for each\ncritical workload?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDR site selection:\u003C/strong\u003E Is your secondary Snowflake account located in\na separate geographic region or on a different cloud provider to\nprotect against large-scale failures?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETesting cadence:\u003C/strong\u003E Have you established a regular cadence for\nconducting DR drills to test your failover procedures and validate\nyour RTO/RPO targets?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERunbook availability:\u003C/strong\u003E Are your DR plans, including specific\nfailover commands and personnel contact information, documented in an\naccessible operational runbook?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Reliability","isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment","elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"## Overview\n\nThe Reliability Pillar focuses on ensuring a workload performs its\nintended function correctly and consistently, recovering from failures\nto meet business and regulatory demands. This involves architecting for\nhigh availability and fault tolerance, ensuring the resiliency of both\nthe service and the data itself, and operationalizing plans for business\ncontinuity and disaster recovery. The goal is to build a data platform\nthat is optimally designed to recover from failure and also meet\nfluctuating demand.\n\n## Principles\n\n### Ensure data is trustworthy and correct\n\n\u003E Reliability in the AI Data Cloud is ultimately defined by the\n\u003E trustworthiness of the data itself. This principle prioritizes data\n\u003E quality, integrity, and correctness as the ultimate measure of a\n\u003E reliable system, because business decisions depend on accurate and\n\u003E complete data.\n\n### Design systems to anticipate and withstand failure\n\n\u003E A reliable system is designed with the assumption that failures will\n\u003E occur. This principle involves building for high availability, fault\n\u003E tolerance, and resiliency at every layer, from data storage,\n\u003E ingestion, and transformation pipelines, to AI and BI workloads, to\n\u003E minimize the impact of disruptions.\n\n### Automate recovery and operations to reduce human error\n\n\u003E Manual processes are a common source of failure and slow down\n\u003E recovery. This principle advocates for automating operational tasks,\n\u003E recovery procedures, and change management to ensure consistent,\n\u003E repeatable, and rapid responses to both planned and unplanned events.\n\n### Continuously test and validate recovery procedures\n\n\u003E A recovery plan is only reliable if it is proven to work. This\n\u003E principle mandates the regular testing of business continuity and\n\u003E disaster recovery plans through drills and simulations, ensuring that\n\u003E both the technology and the operational procedures are effective when\n\u003E a real incident occurs.\n\n### Clearly define and operationalize shared responsibilities\n\n\u003E Reliability is a shared effort between the cloud provider, Snowflake,\n\u003E and the customer. This principle emphasizes the importance of\n\u003E understanding, documenting, and operationalizing the specific\n\u003E responsibilities at each layer to ensure there are no gaps in\n\u003E ownership for achieving end-to-end reliability.\n\n## Recommendations\n\nThe following key recommendations are covered within each principle of\nReliability:\n\n- **Reliability Strategy & Governance**\n\n  - Shared Responsibility Model\n\n  - SLA & Regulatory Compliance\n\n  - Inherited Controls\n\n  - Resource Monitoring & Quotas\n\n  - Immutable Snapshots (WORM) & Archival Storage\n\n- **High Availability & Fault Tolerance**\n\n  - Availability Zones\n\n  - Lifecycle Management (Version Upgrades & Planned Downtime)\n\n  - Automatic Query Retries\n\n  - Error Handling\n\n- **Data & Object Resiliency**\n\n  - Data Resiliency (Streams, Tasks, Database, Stored Procedure, UDF,\n    Policy, Object Tag Replication)\n\n  - Account Object Resiliency (Roles, Users, Warehouse, Resource Monitor\n    Replication)\n\n  - Time Travel\n\n  - Fail-safe\n\n  - Snowsight Objects (Notebooks & Worksheets)\n\n  - Data Recovery\n\n- **Resilient Data Pipelines**\n\n  - Pipeline Object Replication (Snowpipe, Stages, File Formats)\n\n  - Idempotent Pipeline Integration (External Volume, Multi-location\n    Storage/Notification)\n\n  - Load History Replication\n\n  - Exactly Once Delivery without Data Loss\n\n- **Monitoring & Operations**\n\n  - Monitoring, Alerting & Observability\n\n  - Resource Monitoring & Quotas\n\n  - Business Continuity Planning & Testing\n\n- **Disaster Recovery**\n\n  - Replication & Failover Groups\n\n  - Client Redirect\n\n  - Failover Commands (UI & SQL)\n\n  - Backup & Replication\n\n## Reliability strategy & governance\n\n### Overview\n\nReliability Strategy & Governance establishes the foundational framework\nfor making informed decisions about your data platform's resilience. It\ninvolves defining *clear responsibilities*, setting *measurable\nreliability targets*, and aligning technical architecture with business,\nfinancial, and regulatory requirements. This strategic planning ensures\nthat all subsequent reliability efforts are purposeful and directly\nsupport your organization's goals.\n\n### Desired outcome\n\nBy implementing a sound reliability strategy and governance model, your\norganization achieves clear alignment between business objectives,\ntechnical capabilities, and financial investments. This proactive\napproach reduces operational and regulatory risk, ensures predictable\nperformance, and fosters a culture of shared ownership for reliability\nacross teams. You can confidently claim that your reliability posture is\nnot merely a technical function but a strategic capability, governed by\nclear policies and designed to meet specific business, financial, and\ncompliance mandates.\n\n### Recommendations\n\n**Shared Responsibility Model**\n\nThe Shared Responsibility Model is a framework that delineates the\ndistinct reliability duties between the cloud provider (e.g., AWS,\nAzure, GCP), Snowflake, and you, the customer. Its importance lies in\ncreating clarity and preventing gaps in ownership, ensuring that every\naspect of reliability—from physical data center security to the code in\nyour data pipelines—is explicitly accounted for. We recommend you\nformally document and socialize this model within your organization,\nmapping specific internal roles and teams to the responsibilities\ndesignated to the customer. This ensures clear accountability for tasks\nsuch as data governance, workload management, and business continuity\nplanning.\n\n**SLA & regulatory compliance**\n\nThis involves understanding both your contractual uptime commitments via\nthe Snowflake Service Level Agreement (SLA) and the mandatory legal and\nindustry regulations that govern your data, such as DORA for financial\nservices or HIPAA for healthcare. A key aspect of this is leveraging the\nplatform's agility to support flexible SLAs for different Lines of\nBusiness (LoB). Not all workloads share the same criticality;\nSnowflake's architecture allows you to apply stringent,\nhigh-availability configurations and replication strategies only to the\nmost critical LoBs, while using more cost-effective approaches for less\ncritical workloads. Adherence across all levels is critical to avoid\nsignificant financial penalties, operational disruption, and\nreputational damage. We recommend you review\nthe([\u003Cu\u003E/en/legal/\u003C/u\u003E](/en/legal/)),\nidentify all applicable regulations, and map these requirements to\nspecific Snowflake features and operational procedures to create an\nauditable compliance trail that reflects the unique needs of each\nbusiness unit.\n\n**Inherited controls**\n\nThis allows you to leverage Snowflake's existing third-party\ncertifications, such as HITRUST or FedRAMP, to accelerate your own\ncompliance and audit processes. This is a powerful advantage, as it\nsignificantly reduces the time, cost, and effort required to demonstrate\nthat your data platform meets stringent security and reliability\nstandards. We recommend you engage your compliance and security teams to\nreview the reports available on the(\n[\u003Cu\u003Ehttps://trust.snowflake.com/\u003C/u\u003E](https://trust.snowflake.com/)).\nYou should use the HITRUST Shared Responsibility Matrix to formally\ndocument which controls you inherit from Snowflake, streamlining your\naudit preparations and demonstrating due diligence.\n\n**Resource monitoring & quotas**\n\nWhile Snowflake provides virtually unlimited and readily available\ncompute, its consumption must be governed to ensure platform\nreliability. Resource Monitors are a critical governance control for\nmanaging credit consumption by setting quotas on virtual warehouses and\nthe account as a whole. Their importance to reliability is profound:\nthey act as a crucial safety net to prevent runaway queries or\nmisconfigured workloads from exhausting compute resources, which could\notherwise lead to performance degradation or service disruptions for\ncritical business processes. We recommend you assign a Resource Monitor\nto all production virtual warehouses with clearly defined credit quotas.\nYou should configure these monitors to send notifications at various\nconsumption thresholds and to automatically suspend the warehouse if the\nquota is exceeded, thereby protecting your critical workloads and\nensuring predictable platform performance.\n\n**Immutable snapshots (WORM) & archival storage**\n\nThis area addresses the need to meet strict regulatory requirements for\ndata retention and legal holds, where data must be stored in a\nnon-erasable, non-rewritable format (Write-Once, Read-Many, or WORM).\nWhile Snowflake's native Time Travel and Fail-safe features provide\npowerful short-term data protection, certain regulations require\nlonger-term, provably immutable storage. For data subject to these\nstringent requirements, we recommend leverage Snowflake Snapshots to\nperiodically create immutable backups of your tables, schemas and\ndatabases.. This process should be documented thoroughly to provide a\nclear audit trail for regulatory bodies.\n\n### How-To’s\n\n**Implement the Shared Responsibility Model:**\n\n1.  Download and review the\n    [\u003Cu\u003Ewhitepaper\u003C/u\u003E](/en/resources/report/snowflake-shared-responsibility-model/).\n\n2.  Create a RACI (Responsible, Accountable, Consulted, Informed) chart\n    that maps your internal teams (e.g., Data Engineering, Security,\n    Finance, Application Owners) to each of the \"Customer\"\n    responsibilities.\n\n3.  Incorporate this chart into your team onboarding and operational\n    runbooks.\n\n**Set up Demand Management Controls:**\n\n1.  Use the `CREATE RESOURCE MONITOR` command to establish credit quotas\n    for warehouses or the entire account.\n\n2.  Configure the monitor to trigger notifications or suspend warehouses\n    at specific consumption thresholds (e.g., `NOTIFY AT 75 PERCENT`,\n    `SUSPEND_IMMEDIATE AT 95 PERCENT`).\n\n**Perform Basic Capacity Planning:**\n\n1.  Execute queries against the\n    `SNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY` view to analyze\n    credit consumption over time.\n\n2.  Identify daily, weekly, or monthly peak usage patterns to inform\n    warehouse sizing and scaling policy decisions.\n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nimplementing a comprehensive reliability strategy and governance model:\n\n- **Stakeholder alignment:** Have you identified and engaged key\n  stakeholders from business, finance, and technology to contribute to\n  the reliability strategy?\n\n- **Business requirements:** Have you conducted a Business Impact\n  Analysis to define clear availability and recovery targets (SLOs, RTO,\n  RPO) for your critical workloads?\n\n- **Regulatory landscape:** Have you identified and documented all\n  industry-specific and geographical regulations (e.g., DORA, HIPAA,\n  GDPR) that apply to your data?\n\n- **FinOps maturity:** Does your organization have a defined FinOps team\n  or function responsible for cloud financial management and cost\n  governance?\n\n- **Ownership:** Have you assigned clear ownership for each of the\n  customer responsibilities outlined in the Shared Responsibility Model?\n\n## High availability & fault tolerance\n\n### Overview\n\nHigh Availability (HA) and Fault Tolerance are the architectural\ncornerstones that ensure your data platform remains operational and\naccessible, even in the face of component failures or planned\nmaintenance. This involves leveraging Snowflake’s inherently resilient\narchitecture, which is distributed across multiple availability zones,\nand designing workloads that can gracefully handle transient errors. A\nwell-architected system minimizes downtime and provides a consistent,\nreliable experience for your users and applications.\n\n### Desired outcome\n\nBy implementing best practices for High Availability and Fault\nTolerance, your organization achieves continuous operations for its\ncritical data workloads, enhancing user trust and business productivity.\nThis design philosophy protects your business processes from localized\ninfrastructure failures, transient network issues, and planned platform\nupdates, ensuring consistent and predictable performance. After\nimplementing these recommendations, you can claim that your data\nplatform is architected for continuous availability, providing a\nresilient foundation for your data-driven applications.\n\n### Recommendations\n\n**Availability Zones**\n\nSnowflake’s architecture is natively designed for high availability by\ndistributing its service across three independent Availability Zones\n(AZs) within a cloud provider's region. This built-in redundancy is\nfundamental to the platform's resilience, as it ensures that the failure\nof a single data center does not impact the availability of your data or\nthe service as a whole. We recommend you rely on Snowflake’s intrinsic\nmulti-AZ architecture for intra-region high availability, as this fault\ntolerance is managed automatically without requiring any customer\nconfiguration. For workloads that require an even higher level of\navailability beyond a single region, you should complement this native\nHA with a multi-region or multi-cloud disaster recovery strategy.\n\n**Lifecycle management (version upgrades & planned downtime)**\n\nSnowflake manages platform updates through a process of weekly,\nnon-disruptive releases, which are deployed transparently with zero\ndowntime for your workloads. This approach is critical for maintaining a\nhigh-availability posture, as it eliminates the need for\ncustomer-managed maintenance windows that would otherwise interrupt\nservice. We recommend you leverage Snowflake's zero-downtime upgrades\nfor your production accounts to ensure continuous operations. For\ncustomers with Enterprise Edition or higher, we advise designating\nnon-production accounts for [\u003Cu\u003Eearly access to new\nreleases\u003C/u\u003E](https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/intro-releases%23early-access-to-full-releases)\nto test for potential impacts on critical workloads before the\nproduction rollout.\n\n**Automatic query retries**\n\nThe Snowflake platform is designed to be fault-tolerant by automatically\nretrying certain query failures that occur due to transient,\nintermittent issues within the service, such as a temporary network\nfailure or a faulty compute instance. This built-in mechanism is\nimportant because it transparently handles temporary platform failures,\npreventing them from becoming user-facing errors and improving the\noverall reliability of your workloads. We recommend you rely on the\nnative automatic query retry feature to handle transient platform\nissues, which simplifies your application logic. For custom data\npipelines, you should supplement this by implementing your own retry\nlogic for failures outside the scope of automatic retries, such as using\nthe RETRY LAST option for a failed task graph.\n\n**Error handling**\n\nRobust error handling involves designing a centralized framework to\ncapture, log, and manage exceptions from all workloads, not just data\nloading. This is crucial for creating observable and resilient systems,\nas it provides a single source of truth for identifying, analyzing, and\nresponding to failures from any process, including data pipelines,\nstored procedures, or UDFs. We recommend you implement a standardized\nerror logging pattern, such as writing exceptions to a dedicated event\ntable. This approach ensures that all failures are captured\nconsistently, enabling automated alerting and providing a comprehensive\naudit trail for root-cause analysis and remediation.\n\n### How-To’s\n\n**Verify Your Snowflake Release:**\n\n1.  To check the current release version of your account, execute the\n    following SQL command: SELECT CURRENT_VERSION();\n\n2.  Review the monthly behavior change logs to stay informed of upcoming\n    updates.\n\n**Implement Centralized Error Handling:**\n\n1.  Create a standardized event table to log errors from various\n    sources:\n    ```\n    CREATE OR REPLACE TABLE my_event_table (\n      event_timestamp TIMESTAMP_LTZ,\n      error_source VARCHAR,\n      error_code VARCHAR,\n      error_message VARCHAR\n    );\n    ```\n\n3.  Within your custom procedures or data pipelines, use a `TRY...CATCH`\n    block to log exceptions to this central table before re-throwing the\n    error.\n\n4.  Set up a Snowflake Alert to monitor the event table for new entries\n    and trigger a notification, enabling proactive response to any\n    failure in your system.\n\n**Retry a Failed Task Graph:**\n\n1.  If a root task in a dependency tree fails, you can restart the run\n    from the point of failure.\n\n2.  Execute the following command, which will only re-run the failed\n    task and any of its downstream children: `EXECUTE TASK my_root_task\n    RETRY LAST;`\n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nHigh Availability and Fault Tolerance:\n\n- **Regional failure planning:** Have you confirmed that your business\n  continuity plan addresses inter-region failure, given that\n  intra-region HA is handled by Snowflake?\n\n- **Change management:** Do you have a process to review Snowflake's\n  monthly behavior change logs to proactively identify potential impacts\n  on your workloads?\n\n- **Application logic:** Are your custom applications and ETL/ELT tools\n  prepared to handle non-transient errors that are not automatically\n  retried by Snowflake?\n\n- **Data quality feedback loop:** Do you have an automated process for\n  reviewing, remediating, and reporting on records that were skipped or\n  rejected during data loading?\n\n## Data & object resiliency\n\n### Overview\n\nData and Object Resiliency provides critical safeguards against logical\ndata corruption, accidental deletion, or unauthorized changes, ensuring\nthe integrity of your data and the stability of your operational\nenvironment. This involves leveraging native Snowflake features like\nTime Travel for instant point-in-time recovery and object replication to\nprotect both your data and the account configurations that govern it.\nThe goal is to enable rapid, granular recovery from common operational\nfailures without invoking a full disaster recovery plan.\n\n### Desired outcome\n\nBy implementing a robust Data and Object Resiliency strategy, your\norganization significantly reduces the risk and impact of common\noperational failures, such as human error or application bugs. This\nensures the integrity of your critical data assets and the stability of\nyour governance and security posture, allowing you to confidently meet\noperational recovery objectives and minimize data-related incidents.\nAfter implementing these recommendations, you can claim that your data\nplatform is resilient to logical corruption and that you can restore\nboth data and critical account configurations to a known good state in\nminutes.\n\n### Recommendations\n\n**Data resiliency (Streams & Tasks replication)**\n\nData Resiliency focuses on replicating not just the data but also the\ndatabase-level objects that give it context and automate its lifecycle.\nThis is paramount because a replicated database is of limited use if the\nautomated pipelines that populate it or the governance policies that\nprotect it are missing upon recovery. We recommend that a failover group\nalways include schemas containing policy and pipeline objects - such as\nStreams, Tasks, and UDFs - to ensure that your data automation and\ngovernance logic is synchronized with your data, providing a complete\nand functional replica that can be activated quickly.\n\n**Account [\u003Cu\u003Eobject\nresiliency\u003C/u\u003E](https://docs.snowflake.com/en/user-guide/data-time-travel)\n(roles & users replication)**\n\nUse **failover groups** to replicate databases **and** account objects\nlike users, roles, warehouses with point‑in‑time consistency.This is\ncrucial for operational continuity, as your security framework (roles\nand users) and compute configurations (warehouses) are essential to\nmaking your data accessible and usable after a failover. We recommend\nyou replicate all critical account-level objects to your secondary\naccount using an FailoverGroup to ensure your security posture and\noperational configurations are available immediately, preventing delays\nand security gaps during a recovery event.\n\n**Time Travel**\n\nSnowflake [\u003Cu\u003ETime\nTravel\u003C/u\u003E](https://docs.snowflake.com/en/user-guide/data-time-travel)\nallows you to access historical versions of table data at any point\nwithin a defined retention period, which can be configured for up to 90\ndays. This feature is your first and fastest line of defense against\nlogical data corruption, such as accidental `UPDATE` or `DELETE` statements,\nas it enables instant, surgical recovery without restoring from\ntraditional backups. We recommend you configure an appropriate\n`DATA_RETENTION_TIME_IN_DAYS` for all critical production tables,\nbalancing your recovery needs with storage costs, and leverage the\nextended 90-day retention available in Enterprise Edition for your most\ncritical data assets.\n\n**Fail-safe**\n\nFail-safe provides a non-configurable, 7-day data recovery period that\nbegins immediately after the Time Travel retention period ends. It is a\nlast-resort recovery service, managed by Snowflake, designed to protect\nagainst catastrophic data loss from extreme operational failures. We\nrecommend you rely on Fail-safe as a final safety net and not as part of\nyour standard operational recovery procedures. Understand that recovery\nfrom Fail-safe is initiated via Snowflake Support; your primary and most\nimmediate recovery tool should always be Time Travel.\n\n**Data recovery**\n\nData recovery is the practice of restoring data after an incident, which\nin Snowflake primarily involves using `UNDROP` commands or querying\nhistorical data via Time Travel. Having a clear, documented, and tested\nprocess for these actions is essential to executing them quickly and\ncorrectly during a high-stress incident. We recommend you develop and\ndocument specific operational runbooks for common data recovery\nscenarios, such as restoring a dropped table using `UNDROP` or correcting\na faulty data load using Time Travel's `AT | BEFORE` clause, and\nregularly test these procedures.\n\n### How-To’s\n\n**Use Time Travel to Correct an Error:**\n\n1.  Identify the query ID of the erroneous DML statement from the query\n    history.\n\n2.  Re-insert the correct data by querying the table from a point in\n    time before the error occurred:\n    ```\n    INSERT INTO\n        my_table\n    SELECT\n        *\n    FROM\n        my_table BEFORE(STATEMENT =\u003E '\u003Cquery_id_of_bad_dml\u003E');\n    ```\n\n**Restore a Dropped Object:**\n\n1.  To restore a recently dropped table, simply execute the\n    [\u003Cu\u003E`UNDROP`\u003C/u\u003E command](https://docs.snowflake.com/en/sql-reference/sql/undrop-table):\n    `UNDROP TABLE my_table`;\n\n2.  This command also works for schemas and databases.\n\n**Configure Extended Data Retention:**\n\n1.  For critical production databases, set the Time Travel window to its\n    maximum value (requires Enterprise Edition or higher).\n\n    Execute the command:\n    ```\n    ALTER DATABASE my_prod_db\n    SET DATA_RETENTION_TIME_IN_DAYS = 90;\n    ```\n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nData and Object Resiliency:\n\n- **Data retention policy:** Have you defined the required data\n  retention period for each critical table based on business\n  requirements and balanced it against storage costs?\n\n- **Object replication scope:** Have you identified all critical account\n  and database objects (including roles, users, tasks, and policies)\n  that need to be included in replication groups?\n\n- **Recovery runbooks:** Are your operational runbooks for common\n  recovery scenarios (e.g., `UNDROP`, Time Travel query) documented,\n  accessible, and regularly tested?\n\n- **Table type strategy:** Have you evaluated the use of `TRANSIENT`\n  tables for staging data to optimize storage costs by opting out of\n  Fail-safe protection? Furthermore, have you considered using `TEMPORARY`\n  tables for session-specific, intermediate data that requires no\n  recovery whatsoever, providing an additional layer of cost and\n  performance optimization?\n\n## Resilient data pipelines\n\n### Overview\n\nResilient Data Pipelines are the automated processes that reliably move\nand transform data from source to destination, engineered to withstand\nand recover from failures. This involves architecting for idempotency,\nensuring end-to-end data integrity, and replicating the pipeline's\ncomponents and state. The goal is to create a robust, self-healing data\nflow that consistently delivers timely and accurate data for analysis.\n\n### Desired outcome\n\nBy implementing resilient data pipelines, your organization builds trust\nin its data delivery systems, reduces operational overhead, and\naccelerates time-to-insight. This ensures that your data pipelines are\nnot brittle, but are robust systems that can automatically recover from\ntransient errors, prevent data duplication, and guarantee data\ncorrectness. After implementing these recommendations, you can claim\nthat your data lifecycle is managed by a reliable, automated, and\nfault-tolerant framework that consistently delivers high-quality data to\nthe business.\n\n### Recommendations\n\n**Pipeline object replication (Snowpipe, stages, file formats)**\n\nPipeline Object Replication involves replicating the configuration and\nmetadata of data ingestion components—such as Snowpipes, external and\ninternal stages, and file formats—to a secondary account. This is\ncritical for business continuity because a replicated database is of\nlimited value if the mechanisms to load new data into it are unavailable\nafter a failover. We recommend you include all production Snowpipe,\nStage, and File Format objects in your replication groups alongside\ntheir target databases to ensure a fully functional and ready-to-use\ndata ingestion capability in your secondary account. Furthermore, you\nshould periodically validate that the required permissions are granted\non these replicated objects to prevent access issues post-failover.\n\n**Idempotent pipeline integration**\n\nAn idempotent pipeline is one where re-running an operation multiple\ntimes with the same input produces the same result, preventing data\nduplication or corruption. This architectural principle is paramount for\nbuilding reliable, self-healing pipelines, as it allows you to safely\nretry failed jobs without introducing data integrity issues. We\nrecommend you design all data loading and transformation logic to be\nidempotent, for example by using `MERGE` statements instead of simple\n`INSERT` statements. For streaming data, you should leverage features that\nprovide exactly-once semantics to ensure each event is processed\nprecisely one time.\n\n**Load history replication**\n\nLoad History Replication specifically replicates the metadata of files\ningested via Snowpipe to a secondary account. This is a crucial, yet\noften overlooked, component of a resilient data pipeline, as it prevents\nthe re-ingestion of already-processed files after a failover. Without\nthis history, a Snowpipe in a newly promoted primary account would\nre-process all existing files in a stage, leading to significant data\nduplication. Load History is automatically replicated as part of the\ndatabase that is being replicated in a failover group.\n\n**Exactly once delivery without data loss**\n\nAchieving exactly-once delivery is the gold standard for critical data\npipelines, guaranteeing that every record is processed precisely one\ntime, even in the face of failures and retries. This ensures the highest\nlevel of data integrity by preventing both data loss and data\nduplication, which is non-negotiable for financial reporting, regulatory\ncompliance, and other sensitive use cases. We recommend you combine\nidempotent DML logic, transactional controls, and robust error handling\nto architect pipelines that achieve exactly-once semantics. For\nreal-time ingestion, we advise using [\u003Cu\u003ESnowpipe\nStreaming\u003C/u\u003E](https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/snowpipe-streaming-overview),\nwhich is designed to provide these guarantees out of the box.\n\n### How-To’s\n\n**Add a Pipe to a failover group:**\n\n1.  Identify the database and schema containing the pipe you wish to\n    replicate.\n\n2.  Use the `ALTER FAILOVER GROUP` command to add the pipe's parent\n    objects to the group:\n    ```\n    ALTER FAILOVER GROUP my_fg\n    ADD my_db.my_schema.my_pipe TO REPLICATION_SCHEDULE;\n    ```\n\n**Write an Idempotent\n[\u003Cu\u003EMERGE\u003C/u\u003E](https://docs.snowflake.com/en/sql-reference/sql/merge)\nstatement:**\n\n1.  Use a `MERGE` statement to either insert new rows or update existing\n    rows based on a unique key, preventing duplicates on re-run.\n\n    Example:\n    ```\n    MERGE INTO target t\n      USING source s\n      ON t.id = s.id\n      WHEN MATCHED THEN UPDATE SET t.value = s.value\n      WHEN NOT MATCHED THEN INSERT (id, value) VALUES (s.id, s.value);\n    ```\n\n**Check Snowpipe load history:**\n\n1.  To validate that files have been loaded and to check for errors,\n    use the\n    [\u003Cu\u003E`COPY_HISTORY`\u003C/u\u003E](https://docs.snowflake.com/en/sql-reference/functions/copy_history)\n    function.\n\n    Example:\n    ```\n    SELECT\n      *\n    FROM TABLE(INFORMATION_SCHEMA.COPY_HISTORY(\n                  TABLE_NAME=\u003E'my_table',\n                  START_TIME=\u003EDATEADD(hours, -1, CURRENT_TIMESTAMP())\n              ));\n    ```\n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nbuilding resilient data pipelines:\n\n- **Pipeline inventory:** Have you identified and inventoried all\n  critical data pipelines and their constituent objects (pipes, stages,\n  tasks, streams) that need to be made resilient?\n\n- **Idempotency review:** Have you audited your existing ETL/ELT scripts\n  to ensure they are idempotent and will not cause data duplication if\n  retried?\n\n- **Error handling strategy:** Do you have a defined process for\n  handling files or records that consistently fail to load (a\n  \"dead-letter queue\" strategy) to prevent them from blocking the entire\n  pipeline?\n\n- **Dependency mapping:** For complex, multi-step pipelines using Tasks,\n  have you mapped all dependencies to ensure they are replicated and\n  will execute in the correct order after a failover?\n\n## Monitoring & operations\n\n### Overview\n\nMonitoring and Operations is the practice of maintaining the health,\nperformance, and reliability of your data platform in production. It\ninvolves establishing comprehensive observability into system behavior,\nimplementing proactive controls to manage resource consumption, and\noperationalizing your business continuity plans through rigorous\ntesting. A mature operational posture enables you to move from a\nreactive to a proactive state, identifying and mitigating issues before\nthey impact the business.\n\n### Desired outcome\n\nBy implementing a robust Monitoring and Operations strategy, your\norganization achieves a state of proactive control over its data\nplatform, leading to increased stability, predictable performance, and\noptimized costs. This approach minimizes the frequency and duration of\nservice disruptions, ensures that recovery plans are effective, and\nprovides the necessary visibility to manage resources efficiently. After\nimplementing these recommendations, you can claim that your data\nplatform is actively managed, fully observable, and that your\norganization is prepared to execute its business continuity plans with\nconfidence.\n\n### Recommendations\n\n**Monitoring, alerting & observability**\n\nThis practice involves gaining deep insights into the health and\nperformance of your Snowflake environment. While monitoring tells you\n*what* is happening, observability helps you understand *why* it's\nhappening, enabling rapid root-cause analysis. This is critical for\nproactively detecting anomalies, performance degradation, or data\npipeline failures. We recommend you leverage the SNOWFLAKE.ACCOUNT_USAGE\nschema for historical analysis of query performance and credit\nconsumption, and implement [\u003Cu\u003ESnowflake\nAlerts\u003C/u\u003E](https://docs.snowflake.com/en/guides-overview-alerts) to\ntrigger timely, automated notifications for specific conditions,\nensuring your operations team is alerted to potential issues promptly.\n\n**Resource monitoring & quotas**\n\nResource Monitors are a critical governance control for managing credit\nconsumption by setting quotas on virtual warehouses and the account as a\nwhole. Their importance lies in preventing unexpected cost overruns from\nrunaway queries or misconfigured workloads and ensuring that compute\nresources are available for your most critical business processes. We\nrecommend you assign a\n[\u003Cu\u003Eresource-monitor\u003C/u\u003E](https://docs.snowflake.com/en/user-guide/resource-monitors)\nto all production virtual warehouses with clearly defined credit quotas\nthat align with your FinOps budgets. You should configure these monitors\nto send notifications at various consumption thresholds and to\nautomatically suspend the warehouse if the quota is exceeded, thereby\nproviding a crucial safety net for cost control and resource management.\n\n**Business Continuity planning & testing**\n\nA [\u003Cu\u003EBusiness\nContinuity\u003C/u\u003E](https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/business-continuity-disaster-recovery)\nplan is a documented strategy outlining how your organization will\nmaintain critical functions during and after a disruption. However, a\nplan is only reliable if it is regularly tested. This practice is\nessential for validating your technical recovery procedures, building\noperational \"muscle memory,\" and uncovering gaps in your strategy before\na real incident occurs. We recommend you formalize your Business\nContinuity and Disaster Recovery (BCDR) plans in accessible operational\nrunbooks. Crucially, you must establish a regular cadence for conducting\nDR drills—such as executing a failover of a non-production\nenvironment—to test your procedures, validate your RTO/RPO targets, and\nensure your operations team is prepared to respond effectively.\n\n### How-To’s\n\n**Create a resource monitor:**\n\n1.  Use the `CREATE RESOURCE MONITOR` command to define a credit quota and\n    notification thresholds.\n\n    Example:\n    ```\n    CREATE RESOURCE MONITOR my_monitor \n      WITH CREDIT_QUOTA = 1000 \n      TRIGGERS ON 75 PERCENT DO NOTIFY \n               ON 90 PERCENT DO SUSPEND \n               ON 100 PERCENT DO SUSPEND_IMMEDIATE;\n    ```\n\n2.  Assign the monitor to a warehouse:\n    ```\n    ALTER WAREHOUSE my_wh\n      SET RESOURCE_MONITOR = my_monitor;\n    ```\n\n**Set up a Snowflake Alert:**\n\n1.  Create an alert that checks for a specific condition on a schedule.\n\n    Example:\n    \n    ```\n    CREATE OR REPLACE ALERT long_running_query_alert WAREHOUSE = my_ops_wh SCHEDULE = '5 MINUTE'\n      IF (\n          EXISTS (\n              SELECT\n                  1\n              FROM\n                  SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY\n              WHERE\n                  EXECUTION_STATUS = 'RUNNING'\n                  AND START_TIME \u003C DATEADD(hour, -1, CURRENT_TIMESTAMP())\n          )\n      ) THEN CALL SYSTEM $SEND_EMAIL(...)\n    ```\n\n3.  Resume the alert to activate it: `ALTER ALERT long_running_query_alert RESUME;`\n\n**Check for failed Tasks:**\n\n1. To monitor the operational health of your data pipelines, use the [`TASK_HISTORY`](https://docs.snowflake.com/en/sql-reference/functions/task_history) function.\n\n   Example: \n   ```\n   SELECT\n    *\n   FROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY(\n                    SCHEDULED_TIME_RANGE_START=\u003EDATEADD('hour',-1,CURRENT_TIMESTAMP()),\n                    RESULT_LIMIT =\u003E 100\n              )\n            )\n   WHERE STATE = 'FAILED';\n   ```    \n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nimplementing a mature Monitoring and Operations practice:\n\n- **Observability strategy:** Do you have a centralized dashboard for\n  monitoring key reliability metrics (e.g., query performance, warehouse\n  utilization, data loading errors)?\n\n- **Alerting channels:** Are your alert notification channels (e.g.,\n  email, PagerDuty) configured and integrated with Snowflake?\n\n- **Quota alignment:** Are your resource monitor quotas aligned with\n  your departmental budgets and FinOps strategy?\n\n- **BCDR documentation:** Is your Business Continuity plan documented,\n  accessible, and regularly reviewed by all relevant stakeholders?\n\n- **Testing cadence:** Have you defined and committed to a schedule for\n  conducting regular DR tests and \"game day\" exercises?\n\n## Disaster Recovery\n\n### Overview\n\nDisaster Recovery (DR) is a critical component of a comprehensive\nreliability strategy, focused on restoring data and service in the event\nof a large-scale failure. Snowflake provides a multi-layered approach to\nDR, ensuring comprehensive protection is readily available. This begins\nwith automatic **Cross-Zone** recovery, where the platform transparently\nhandles an availability zone outage at no additional cost. For broader\nincidents, customers can implement **Cross-Region** DR to fail over to\nanother region, or even **Cross-Cloud** DR to fail over to an entirely\ndifferent cloud provider for the highest level of resilience. A\nwell-architected DR plan leverages these capabilities to minimize data\nloss and downtime, ensuring business continuity for your most critical\nworkloads. For a detailed overview of the concepts and features\ninvolved, refer to Snowflake’s documentation on [\u003Cu\u003Ebusiness continuity\nand disaster\nrecovery\u003C/u\u003E](https://docs.snowflake.com/en/user-guide/replication-intro).\n\n### Desired outcome\n\nBy implementing a robust Disaster Recovery (DR) strategy, your\norganization ensures business continuity for critical data workloads,\nprotecting against regional outages and minimizing data loss. This\nallows you to confidently meet stringent Recovery Time Objectives (RTO)\nand Recovery Point Objectives (RPO), maintain customer trust, and uphold\nregulatory obligations even in the face of a major disruption. After\nimplementing these recommendations, you can claim that your data\nplatform is resilient and your business is prepared for catastrophic\nfailures, with a tested and reliable plan to restore service.\n\n### Recommendations\n\n**Failover groups**\n\nFailover groups are the foundational Snowflake concept for implementing\na robust DR strategy. They allow you to group databases and critical\naccount objects—such as users, roles, and resource monitors—and\nreplicate them as a single, consistent unit to a secondary account in\nanother region or cloud. This is paramount for ensuring that not just\nyour data, but your entire operational environment, can be recovered\nwith point-in-time consistency after a disaster, thereby minimizing both\ndata loss (RPO) and recovery time (RTO). We recommend you group critical\ndatabases and their associated account objects into Failover Groups to\nensure they are replicated and failed over together, maintaining both\ntransactional and operational integrity. Furthermore, you should\nconfigure a frequent replication schedule for these groups, aligned with\nyour business requirements, to minimize your RPO.\n\n**Client Redirect**\n\n[\u003Cu\u003EClient\nRedirect\u003C/u\u003E](https://www.google.com/search?q=https://docs.snowflake.com/en/user-guide/business-continuity-client-redirect)\nis a feature that provides seamless, automated failover for your\napplications and users. It works via a connection object that\nautomatically reroutes client application traffic from a primary account\nto a secondary account after a failover has been initiated, without\nrequiring manual changes to connection strings. This feature The\nimportance of this feature cannot be overstated, as it dramatically\nsimplifies the recovery process and reduces your RTO by eliminating the\ncomplex and error-prone task of reconfiguring every client application\nduring an outage. To leverage this capability, we recommend you\nimplement a connection object with Client Redirect enabled for all\nproduction applications. It is also critical to ensure that all client\napplications are configured to use the single connection URL provided by\nthis object, rather than direct account URLs, to guarantee the automated\nredirection is effective.\n\n**Failover commands (UI & SQL)**\n\nExecuting a disaster recovery plan is ultimately controlled by specific\nfailover commands, which are available through both the Snowsight UI and\nSQL. These commands are used to promote a secondary failover group to\nbecome the primary, thereby formally initiating the failover process.\nHaving a clear, well-understood, and tested procedure for using these\ncommands is critical for a swift and successful recovery during a\nhigh-stress incident. We recommend you document the exact SQL failover\ncommands (e.g., `ALTER FAILOVER GROUP... PRIMARY`) in your operational\nrunbooks and grant the necessary privileges to a limited set of\nauthorized personnel to prevent accidental activation. Additionally,\nyour operations team should be familiarized with both the UI-based and\nSQL-based failover procedures as part of your regular DR testing to\nensure they can execute them efficiently under pressure.\n\n**Backup & replication**\n\nA comprehensive [\u003Cu\u003Edata\nprotection\u003C/u\u003E](https://docs.snowflake.com/en/user-guide/data-cdp)\nstrategy must address both large-scale disasters and more common\noperational failures. This is achieved by combining physical replication\nfor disaster recovery with logical backups for operational recovery.\nWhile cross-region replication is essential for surviving a regional\noutage, it is not a substitute for protecting against human error or\ndata corruption. Snowflake’s architecture provides powerful tools for\nboth scenarios. We recommend you complement your cross-region\nreplication strategy with a regular, automated process for creating\nzero-copy clones of critical databases. These clones serve as highly\nefficient, point-in-time logical backups that can be used for rapid\noperational recovery, development, and testing without incurring\nsignificant storage costs. You can alternatively leverage Snowflake\nSnapshots to periodically create and expire immutable backups. Finally,\nyou must verify that your backup and replication processes preserve your\nRole-Based Access Control (RBAC) and governance policies to ensure\nsecurity and compliance are maintained post-recovery.\n\n### How-To’s\n\n**Implement Failover Groups:**\n\n1.  Identify critical databases and account objects (users, roles,\n    warehouses, etc.) required for business continuity.\n\n2.  Create a [`FAILOVER GROUP`](https://docs.snowflake.com/en/sql-reference/sql/create-failover-group) in your primary account that includes these\n    objects.\n\n3.  Create a secondary `FAILOVER GROUP` in your DR account as a replica\n    and set a refresh schedule (e.g., `REPLICATION_SCHEDULE = '10 MININUTE'`).\n\n**Configure Client Redirect:**\n\n1.  Create a [`CONNECTION`](https://docs.snowflake.com/en/sql-reference/sql/create-connection) object in your primary account.\n\n2.  Enable [`CLIENT_REDIRECT`](https://docs.snowflake.com/en/user-guide/client-redirect) for that connection object.\n\n3.  Update all client application connection strings to use the new\n    connection URL (e.g.,\n    `\u003Corganization_name\u003E-\u003Cconnection_name\u003E.snowflakecomputing.com`).\n\n**Establish logical backup procedures:**\n\n1.  Identify critical tables or databases that require frequent,\n    point-in-time backups for operational recovery.\n\n2.  Create a Snowflake Task to automatically execute a `CREATE TABLE...\n    CLONE` statement on a defined schedule (e.g., daily).\n\n3.  Implement a data retention policy for these clones to manage storage\n    costs.\n\n### Tradeoffs & Considerations\n\nUse the following checklist to assess your organization's readiness for\nimplementing a disaster recovery strategy:\n\n- **Business impact analysis:** Have you identified your most critical\n  data workloads and quantified the business impact of an outage?\n\n- **RTO/RPO definition:** Have you defined and documented the Recovery\n  Time Objective (RTO) and Recovery Point Objective (RPO) for each\n  critical workload?\n\n- **DR site selection:** Is your secondary Snowflake account located in\n  a separate geographic region or on a different cloud provider to\n  protect against large-scale failures?\n\n- **Testing cadence:** Have you established a regular cadence for\n  conducting DR drills to test your failover procedures and validate\n  your RTO/RPO targets?\n\n- **Runbook availability:** Are your DR plans, including specific\n  failover commands and personnel contact information, documented in an\n  accessible operational runbook?\n",":type":"text/x-markdown","multiValue":false},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image",":type":"text/plain","multiValue":false}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],":items":{},":itemsOrder":[],"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-0dfccea123","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-9e0949d6c6",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-0306af2861","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-06-17",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-c08f6a8f56","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. 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