Observability Use Cases:
Solving Real-World IT Challenges

Ingest, storage, and index costs climb every time telemetry volume grows, and AI is accelerating that growth. Cribl filters, reduces, and routes data before it ever reaches an expensive tool, so you pay to analyze and store only what matters. Cost stays predictable even as your environment — and your AI footprint — keeps expanding.

LLMs, GPU workloads, and shadow AI generate telemetry fast, and most of it never reaches a single place to look at it. The Cribl App for AI Observability gives you one surface to see usage, cost, and risk across every model and team. No new collection project, no blind spots.

The next step in observability is agents that investigate and resolve issues on their own, not just proviedashboards for humans to read. Cribl Search and Cribl Apps give you a foundation built for that: structured, queryable telemetry that AI agents can reason over. Start with a pre-built app, or build the observability agent your team actually needs.

Application and infrastructure logs create noise and drive up storage costs, making it hard to surface what matters. Cribl filters and routes logs based on value, sending low-value data to cost-effective storage while keeping what you need for analysis and compliance. Cribl's new metric store gives that same control to your metrics, so logs and metrics both land in the right place at the right cost.

Diverse telemetry formats and proprietary agents complicate data collection and analysis across modern environments. By adopting OpenTelemetry, organizations standardize instrumentation and unify the collection of logs, metrics, and traces across platforms and vendors. This streamlines integration, reduces vendor lock-in, and builds a future-proof observability foundation.

Dynamic, containerized workloads in Kubernetes clusters are difficult to monitor and troubleshoot at scale, particularly across hybrid or multi-cloud deployments. Observability platforms collect, correlate, and analyze telemetry from Kubernetes, delivering end-to-end visibility and real-time alerting. Teams benefit from faster root cause analysis, improved uptime, and optimized resource usage in cloud-native environments.