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.

How to Prepare for Human-in-the-Loop AI in Observability AI is rapidly reshaping IT operations, but pushing forward blindly introduces massive risks. To scale automation safely, your teams need the right foundation in place. Join SolarWinds experts for a tactical session on how to strengthen data quality, eliminate tool fragmentation, and establish clear governance guardrails. Discover how to confidently transition from human-managed workflows to safe, guided AI autonomy.

In this Black Hat talk, Nicole Beckwith introduces APEX (Adversarial Pattern Extraction and Correlation), a detection framework—not a Cribl product—that clusters TTP-based signals around entities to support behavioral detection. It is intended for security practitioners, SOC and detection teams, and threat hunters who want to learn how to use raw telemetry or OCSF data, TTP chaining, time windows, criticality, and cross-correlation to detect behavior beyond static indicators and rule-count coverage.