Logs without schemas, indexes or limits
Store all logs in one place, query them in seconds and link them automatically to traces, metrics and problems
Rethinking log management: from index to context
Why index-free storage cuts cost and speeds up analysis.
Read nowLog analytics in context instead of in silos
Obseria Lake stores logs schema-free, links them automatically to every other signal and makes them queryable in seconds.Schema-free and index-free
Ingest logs of any structure without parser maintenance, reindexing or storage tiers. Schema-on-read enables queries nobody anticipated at ingest time.
Queries in seconds, on petabytes
The Obseria Query Language (OQL) combines filters, aggregations and joins across logs, traces and metrics. Results on billions of lines in seconds.
Automatic context
Every log line is linked to host, container, service, trace and problem, without tagging schemes or manual stitching.
38% lower log cost
With Obseria Pipeline, Lumen Retail keeps only relevant logs and cut cost despite 3× the volume.
Read the Lumen story20 s instead of 20 minutes per query
Cobalt Insurance replaced an index-based log stack and accelerated compliance analysis 60-fold.
Read the Cobalt story100% of logs in trace context
Granit Public automatically links logs from 40 government procedures to transactions.
Read the Granit story0 parsers to maintain
Aurora Media eliminated 300 Grok patterns and ingests logs schema-free.
Read the Aurora storyEmpower your business with AI-driven observability
Harness trusted answers instead of alert floods, for measurable business outcomes at scale
Explore the Obseria approachFrom signal to answer in three steps
- Step 1
Ship logs your way
Send logs via OpenTelemetry, Fluent Bit, Vector, syslog or cloud integrations. No parsers or index definitions required.
- Step 2
Filter and enrich
Obseria Pipeline drops noise, masks PII and adds Kubernetes and trace context before storage.
- Step 3
Query in seconds
Search and aggregate billions of lines with OQL and jump from any log line to its trace, host or problem.
What's included
- Schema-on-read, no indexes
- Petabyte-scale queries in seconds
- Automatic trace and topology context
- PII masking and field-level access
- Retention up to ten years
- Log-based alerts and anomaly detection
Products around Log Analytics
Obseria Lake
Index-free, schema-free storage for logs, events, traces and metrics.
Obseria Pipeline
Filter, enrich, mask and route logs at ingest. Keep only the signal.
Obseria Query Language
One query language for logs, traces, metrics and business data.
Log-based alerts
Alerts on patterns, anomalies and absence of logs with clear error messages.
Security Analytics
Analyze audit and access logs for threat detection and compliance.
Obseria Intelligence
Detect log anomalies automatically and link them to root causes.
Log analytics use cases with Obseria
From alert to log line in one click
Every problem in Obseria links directly to the relevant logs, filtered by time, service and trace. No searching for request IDs, no switching between tools.
See the problem workflowKeep the signal, not the noise
Obseria Pipeline filters debug logs, deduplicates repetitions, masks PII and routes compliance logs to low-cost long-term storage. You pay only for what you keep.
See pricingRetain audit logs immutably
Immutable retention for up to ten years, field-level access control and GDPR-compliant masking. Queries for auditors in seconds instead of days.
Security and TrustContainer logs with pod, deployment and node
Logs from Kubernetes are automatically enriched with metadata and mapped to the topology. Crash loops and OOM kills appear with the container's last log lines.
Kubernetes integrationWorks with your stack
Connect the technologies you already run. 700+ integrations, discovered and put into context automatically.
Leading organizations that run on Log Analytics
Get started with Log Analytics training and documentation
Log Analytics FAQ
Log management covers collecting, storing, searching and analyzing log data from applications, infrastructure and cloud services. Modern log analytics links logs automatically to traces, metrics and topology instead of indexing them in isolation.
Indexes have to be defined at ingest, maintained and rebuilt on change. Obseria Lake instead uses columnar, compressed storage with schema-on-read: every query is possible without knowing in advance which fields matter.
30 days by default, configurable up to ten years for compliance requirements. Retention can be controlled per bucket and log source.
OpenTelemetry, Fluent Bit, Fluentd, Vector, Logstash, syslog, Kubernetes, Docker, AWS CloudWatch, Azure Monitor, Google Cloud Logging as well as file and journal logs via the Obseria Agent.
By ingested and stored log lines, not by bytes or hosts. Whatever Obseria Pipeline drops costs nothing.
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