Data and their historical context
What did it look like last week?
- During troubleshooting or forensics, app developers and secops have need to compare behavior of systems at different times.
- But data are often only present for the moment, and not stored over time.
- If Long-time data aggregation is present, it is often inefficient due to missing cloud native and Kubernetes context.
- Also, a data lake can be overwhelming without pre-defined, helpful queries.
Observability platform Timescape
- Enhanced Kubernetes observability with historic network flows, syscalls, audit events, and much more.
- Time-ranged based filters.
- Historical flows, historical view integrated into the UI.
- Stores billions of events, with 250k events/s even on single-node DB.
- Pre-defined queries for typical analyst tasks
- Queries support L7 filters, CIDR ranges, etc.
- RBAC support.
A time machine for observability data with powerful analytics capabilities
- User-friendly and tenant-capable access to long-term analytics.
- Simplified troubleshooting and forensics.
- Analytical value right from the start due to pre-defined queries.
Want to learn more?
There is plenty more material available if you'd like to learn more.
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