Video
Introducing Observe by Snowflake
Jeremy Burton, Snowflake GM of Observability, introduces a new model for observability built natively on the Snowflake lakehouse.
Observeby Snowflake
AI-powered observability at scale. Unify logs, metrics and traces on a cost-efficient Snowflake lakehouse, using an integrated AI SRE that helps resolve incidents faster.
BENEFITS
Troubleshoot fasterat lower cost
Programmable AI SRE
Run AI-driven observability where you work
The Observe AI SRE, CLI and MCP Server support developers, engineers, DevOps and SREs where they are, enabling custom agentic workflows.
Context Engineered for Accuracy
Get faster, more accurate answers grounded in your data
The Observability Context Graph maps semantics and relationships across logs, metrics and traces, extending to code and business context — so you get faster, more accurate reasoning.
Cost-Efficient Scale
Cut observability costs while scaling and retaining more data
Observe’s Telemetry Lakehouse Foundation, built on Snowflake, offers low-cost cloud storage and compute-storage separation to ingest, store and analyze more data at lower cost.
use cases
Observability engineered for scale
INVESTIGATE AND ROOT CAUSE FASTER
Reduce MTTR with AI SRE
- Investigate incidents, find root causes and get suggested fixes using natural language.
- Get more accurate answers with AI SRE, which applies context from the Observability Context Graph.
- Fewer engineers need to respond to incidents, and when they do, there’s no need to jump between tools and dashboards.
- Troubleshoot using AI SRE in the Observe UI or run agentic workflows via CLI or MCP Server with Claude or Cursor.
Search logs at scale
Analyze log data at a fraction of the cost
- Search and analyze logs without worrying about indexing, data tiering or retention limits.
- Ingest log data in any format — structured, semi-structured or unstructured.
- Generate unlimited log-derived metrics at no extra cost.
END-TO-END SERVICE VISIBILITY
Go from service issues to root cause in seconds
- Native OpenTelemetry provides automatic instrumentation and unified service discovery.
- Capture every trace without sampling or data loss for full-fidelity investigation.
- Move seamlessly from traces to correlated logs, metrics and infrastructure data to reduce manual effort.
REAL-TIME SYSTEM HEALTH
Correlate infrastructure signals to understand system behavior
- Capture metrics across cloud, Kubernetes, containers and serverless from 400+ pre-built integrations.
- Skip dashboard-building and reduce alert noise with out-of-the-box visualizations and contextual alerts.
- Pivot easily between infrastructure dashboards and correlated logs to troubleshoot and resolve incidents.
OPTIMIZE AI WORKLOADS
Operate AI applications and agents with confidence
- Trace AI requests from prompt to response across multi-step agentic workflows.
- Analyze token consumption to spot usage patterns and see where you can trim spend.
- Connect AI application performance to underlying infrastructure and services.
Resources
Explore more inObservability
GET STARTED
Take the next step with Observe by Snowflake
Start your free trial
Performance at scale
Faster troubleshooting
Lower cost with an open data lake
Snowflake for Observability
Frequently Asked Questions
Your top questions about getting started with Observe by Snowflake, answered here.
How does Observe relate to Snowflake’s AI Data Cloud?
Observe is an observability solution built on Snowflake's platform that helps teams troubleshoot faster at lower cost. Observe enables customers to bring all their telemetry (logs, metrics and traces) into a cost-efficient Snowflake lakehouse. Observe is now part of Snowflake.
Can I use Observe for data observability?
Observe is purpose-built for infrastructure and application observability (logs, metrics and traces from distributed systems) and is designed for SREs and software engineers. Observe’s tools complement Snowflake’s data observability capabilities like Snowflake Trail.
How is Observe by Snowflake different from other observability tools?
Observe stores all telemetry in a single telemetry data lake, which lowers cost at scale and enables greater retention times. Its context graph automatically connects related signals across data streams, so that both AI agents and humans can investigate more quickly and accurately using a unified model instead of switching between disconnected tools.
Can Observe help reduce observability costs?
Observe's Telemetry Lakehouse Foundation, built on Snowflake, helps customers to cost-effectively ingest, retain and analyze higher volumes of telemetry data with lower costs. Consolidating logs, metrics and traces at scale can often eliminate the need for multiple observability tools, reducing licensing costs and operational overhead.
Can Observe help me resolve incidents faster?
Observe's context graph automatically links related logs, metrics and traces, so that you can trace root causes without manually correlating data in separate tools. Combined with AI SRE, which can surface likely causes and recommend next steps, teams can significantly reduce investigation and incident resolution time.
Does Observe by Snowflake work with open standards like OpenTelemetry and Apache Iceberg?
Observe natively ingests any OpenTelemetry-compatible data and it works with telemetry stored in Iceberg tables. This open approach means you're never locked into a proprietary agent or format.
What is an AI SRE and how can it help teams resolve incidents faster?
Observe's AI SRE is an AI agent that uses the Observability Context Graph, a semantic model of relationships across both your telemetry and business data types, to get more accurate answers. Teams can troubleshoot more quickly using natural language to surface root causes and suggest next steps during incidents.
