Operations | Monitoring | ITSM | DevOps | Cloud

Cribl On Your Coffee Break Episode 15 - Routes, part 4 and Cribl Packs

Welcome to the end of week 3 of series to help you get started with the Cribl platform. We’re still talking about routing, but through the lens of Cribl Packs, a way of supercharging your path to getting your data in and through Cribl. 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...

Cribl On Your Coffee Break Episode 14 - Routes, part 3: One-to-Many

Welcome to the 14th installment in our series to help you get started with the Cribl platform. Here, we continue our conversation about Cribl routes and routing techniques 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...

Cribl On Your Coffee Break Episode 13 - Routes, part 2: Many-to-one

Leon is back from the BlackHat conference and it shows (or at least it SOUNDS like it). Despite a little bit of laryngitis, today he’s continuing the exploration of routing by focusing on taking multiple sources of data and using routes to send them to a particular destination. 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...

How backend functions extend Cribl Apps: Scheduling, local testing, and logs

See how backend functions extend Cribl Apps with live data retrieval, scheduled jobs, local testing, deployment validation, and logging. In this walkthrough, Giovanni Mola shows developers how to connect app data sources such as Jira and news feeds, manage schedules, preview functions locally, verify a live deployment, and inspect emitted logs in Cribl Search.

Cribl On Your Coffee Break Episode 4 - Gathering REST data

In the 4th installment of our series, Leon looks at Cribl’s ability to collect REST API data. 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...

Cribl On Your Coffee Break Episode 3 - Configuring Prometheus Remote-Write

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...

Cribl On Your Coffee Break Episode 2 - Setting up Syslog

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...

Cribl On Your Coffee Break Episode 1

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.

Introducing APEX: Adversarial Pattern Extraction and Correlation

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.