LOG USE CASES

Where are your logs slowing you down?

Centralize scattered records, investigate application failures or evaluate growing retention costs. Choose your first step around the problem you have.

Solve your log problem first

From scattered files to one operational memory

Build your first central log platform

Stop treating every incident like a file-system scavenger hunt. Bring application, host and container logs into one searchable on-prem workspace.

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Short-lived workloads, durable evidence

Troubleshoot Kubernetes and application failures

Follow errors across pods, services and hosts from a shared timeline—even after the workload that produced them is gone.

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Keep the evidence, reduce the machinery

Replace a costly or complex log stack

Move a high-volume or long-retention workload to an analytical foundation that combines text search and SQL without exporting your data.

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Extend your log coverage

Retain the trail without claiming a full SIEM

Centralize security and audit logs

Keep Windows Security, identity, database, cloud and network audit events searchable inside your environment.

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One retained signal path for incident evidence

Build a logs-first observability foundation

Collect operational events through the tools you already use, retain changing context and investigate with search and SQL from one data foundation.

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Supporting capabilities

Raw event in, reviewable pipeline out

Onboard unfamiliar logs with AI assistance

Turn a representative JSON event into a reviewable Doris schema and collector configuration without handing AI uncontrolled production access.

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Continuous events, current state, immediate serving

Turn logs into current operational analysis

Analyze error rates, service trends and operational events on the same SQL foundation. Real-time analytics extends your central log investigation workflow.

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Open lake storage, real-time analytical paths

Bring historical data into log investigations

Query existing lake data alongside operational logs when an investigation needs historical context. Lakehouse access supports the core log workflow.

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Structured facts, text and vectors in one retrieval path

Provide relevant log evidence to AI workflows

Query logs, operational facts and documents within time and access boundaries. Supply AI applications with a bounded, inspectable set of evidence.

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LET’S TALK ABOUT YOUR LOGS

Where are your logs slowing you down?

Tell us about your current tools and the problem you want to solve. We’ll agree the next step: a product walkthrough or a technical evaluation with one source.