Operations | Monitoring | ITSM | DevOps | Cloud

In day 3 of our coffee break series, Leon continues to explore common observability data types and how to get them into Cribl. Today, we’ll look at setting up a simple Prometheus ingestion. By the time the month (and the series) is over, you will have a pretty good idea of what Cribl can do, and how to do it. You’ll also have consumed your body weight in caffeinated beverages...

In our second video Leon picks on Syslog (because honestly, it deserves it). Cribl is the perfect tool to whip that disorganized, loud, unruly mess of a data stream into shape. By the time the month is over, you will have a pretty good idea of what Cribl can do, and how to do it. You’ll also have consumed more caffeinated beverages than is strictly appropriate...

In this first episode (or at least the first REAL episode, yesterday’s “episode 0” doesn’t count) of Cribl on your coffee break, Leon does what we all do when we unwrap a shiny new data, telemetry, observability, or monitoring tool: He takes the shortest path to jamming some data into that thing and seeing what it looks like. Is it sophisticated? Nuanced? Well-thought-out? Hell no! But it scratches an itch. There will be time to do more real-world stuff tomorrow.

#observability #ai #agenticcoding

The bucket is right there and the function still cannot read it. AURA reads the failure, names the one missing action, and returns the policy to add. A permissions failure gives you the symptom and not the action name. The usual path is reading the error, guessing which actions the execution role is short, and widening the policy until the call goes through. Greg hands AURA a Lambda function that fails when it tries to reach an S3 bucket. AURA identifies the missing ListBucket permission on that particular bucket and returns the minimum policy needed to allow it.