Hey folks. I've been setting up monitoring for our Cribl Stream deployment, and I keep circling back to a fundamental question: how do we effectively monitor Cribl's own health and log output without creating a circular dependency?
It feels like a classic chicken-and-egg scenario. If Cribl is processing all our observability data, and its own logs are part of that pipeline, what happens when Cribl has an issue? Do those internal logs just vanish into the void, making troubleshooting a black box?
In our setup, we're routing Cribl's internal logs (`cribl.log`, `metrics.log`) to a downstream destination like Splunk. But I'm thinking through the failure modes. If Cribl itself stalls or the worker process hosting the pipeline has problems, that log flow could stop. We'd be blind until we SSH in to check logs locally.
I'm curious how others have architect-ed this. Some specific points I'm pondering:
- Are you using a separate, independent agent (like Fluentd or Filebeat) on the Cribl nodes to ship those internal logs, completely outside of Cribl's own processing?
- Or do you rely on Cribl's own health metrics/API endpoints polled by an external system?
- Have you set up a dead-simple, high-priority pipeline that routes only Cribl's logs with minimal processing to ensure they get out?
Looking for practical experiences and what's proven robust in production. The goal is to avoid a situation where the tool meant to give us visibility becomes our biggest blind spot.
Keep it real, keep it kind.
We ran into this exact issue. The separate agent approach worked for us but introduced its own overhead.
We use a lightweight Vector sidecar on each Cribl node that tails `cribl.log` and `metrics.log`. It pushes directly to a small, separate S3 bucket designated for "infrastructure firehose" logs. This S3 bucket is then read by a second, independent Cribl deployment in another environment (our DR site) for processing. It's a bit of a Rube Goldberg machine, but it guarantees visibility.
The caveat is you now have to monitor Vector. We've found its resource footprint negligible, but it's another moving part. Relying solely on Cribl's health API left gaps for us, particularly with pipeline-specific errors that don't always surface there.
Numbers don't lie
That separate agent path is the only way to break the dependency loop, but you've nailed the core trade-off. You're now auditing your auditor.
The real test is whether that second, independent Cribl deployment in your DR site is truly autonomous. Does it have its own separate, minimal monitoring? If it's pulling from that S3 bucket but its own logs route back through the primary Cribl's pipeline, you've just created a longer, more complex loop.
We ended up with a similar Vector setup, but we send its logs to a completely separate vendor's telemetry endpoint. It's a hard requirement for us to avoid a single point of failure in the observability chain. Adds cost, but passes the audit.
Where is your SOC 2?