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Comparing the ELK Stack vs. Observe for Observability at Scale
Learn why ELK's index-based architecture hits a wall at scale — and how Observe delivers better retention, lower cost and faster root cause analysis.
Use Case
Find answers fasterwith log management
Keep every log hot at scale. Search and analyze log data across your applications, infrastructure, security and business systems without worrying about indexing, data tiers or retention limits.
Overview
Retain and search logs without compromising on cost or scale
Log data grows fast and gets expensive even faster, forcing teams to sample, tier or delete the data they need most. Search, analyze and troubleshoot every log with Observe by Snowflake.
Collect everything, everywhere
Ingest structured, semi-structured and unstructured logs from cloud, Kubernetes and serverless sources. Scale on demand and absorb bursts without building pipelines.
Troubleshoot in near real time
Get to the root cause with full context. Search, filter and analyze logs the moment they arrive, then pivot from dashboards and traces to the exact logs behind an issue.
Keep your logs without worrying about cost
Retain logs for up to 13 months and keep them all instantly searchable. No tiers to manage, data to move or tradeoffs between compliance and budget.
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Benefits
Ingest, retain and analyze logsat any scale
Quick setup
Get started with log collection in minutes
- Collect logs across your entire stack with OpenTelemetry, Fluentd, Fluent Bit and a variety of integrations.
- Ingest any format — structured, semi-structured or unstructured — from any source.
- Scale on demand and absorb log bursts without building buffers or pipelines.
- Explore and transform data with a visual Query Builder or flexible query language, and let O11y Copilot write the queries for you.
Faster troubleshooting
Troubleshoot in near real time to reach the root cause faster
- Detect and troubleshoot issues in near real time with Live Mode.
- Search, filter and analyze logs with an intuitive Query Builder or advanced query language to enrich and transform event data.
- Correlate logs across sources on the Observability Context Graph and pivot from a service map to the logs behind an issue.
- Use the Observe AI SRE to investigate across logs, metrics and traces, then surface the root cause and next steps.
Retention and compliance
Keep every log without compromising on cost
- Retain logs as long as you need for compliance, at a nominal additional cost of $0.01 per GiB/month.
- Query all data at full speed. No hot, warm, cold or frozen tiers to manage.
- Skip the toil of moving data between tiers or rehydrating archives.
- Access historical logs on demand whenever compliance or investigations require them.
Log-derived metrics
Turn the logs you already have into the metrics you need
Derive custom metrics from the log attributes, patterns and content that matter to your business.
Extract any string from a log message with a point-and-click UI.
Generate virtually unlimited log-derived metrics for longer-term analysis at no extra cost.
Track trends over time without re-querying raw logs.
Dialpad accelerates troubleshooting for high-volume communications
Dialpad's platform handles millions of calls, texts and meetings a day, and reliability at scale is non-negotiable. With Observe uniting logs, metrics and traces in the Observability Context Graph, engineers can fix issues much faster.
Resources
Discover more about theObserve by Snowflake AI SRE
Get Started
Take the next stepwith Observe by Snowflake
Start your free trial
Performance at scale
Faster troubleshooting
Lower cost with an open data lake
Snowflake for Log Management
Frequently Asked Questions
Get quick answers to log management questions and learn how Observe by Snowflake helps teams collect, search and retain logs at scale.
What is log management?
Log management is how teams collect, store, search and analyze the log data generated across their applications, infrastructure, security tools and business systems. With Observe by Snowflake, teams can bring all their log data into one platform and keep it instantly searchable, so they can troubleshoot issues, investigate incidents and meet compliance needs without managing indexes or data tiers.
How does Observe collect log data?
Observe ingests logs through OpenTelemetry Collector, Fluentd, Fluent Bit and over 400 prebuilt integrations spanning cloud services, Kubernetes, containers and serverless environments. It accepts structured, semi-structured and unstructured data from any source, scales on demand and is built to absorb log bursts, so teams don't need to build buffers or pipelines to keep up.
How does Observe lower the cost of log storage?
Observe is built on the Telemetry Lakehouse Foundation, which separates storage from compute, so teams can retain logs long term at a nominal cost per GiB/month while keeping every log instantly searchable. There are no hot, warm, cold or frozen tiers to manage and no data to move, which removes both the cost surprises and the operational toil of traditional log platforms.
How does log management connect to the rest of Observe?
Logs in Observe don't sit in a silo. They're linked to metrics, traces and infrastructure through the Observability Context Graph, which maps how your services and systems relate. Teams can move from a service map or dashboard directly to the relevant logs, then bring in the Observe AI SRE to investigate across all telemetry and pinpoint the root cause faster.
