You’re responsible for administering hundreds to thousands of server endpoints deployed at your company. You receive daily requests from the application teams requiring agents be installed on new servers, from the compliance team tracking agent upgrades and from the operations team concerned logs and metrics are missing from the dashboards they’re monitoring. You review your workload and realize you must log into each individual server for every request you’ve received.

Data routing is a crucial but complex task for companies of all sizes. Ensuring that the right data is sent to the right tools can be a time-consuming and difficult process, and when things go wrong, it can have costly consequences. This is why having a robust data routing strategy is essential for any organization.

As mentioned in our documentation, Cribl Stream is built on a shared-nothing architecture. Each Worker Node and its processes operate separately and independently. This means that the state is not shared across processes or nodes.This means that if we have a large data set we need to access across all worker processes, we have to get creative. There are two main ways of doing this: In this blog, we’ll walk through how to deploy a Stream leader, Stream worker, and Redis containers via Docker.

Are you just getting started with Cribl Stream? Or maybe you’re well on your way to becoming a certified admin through our Cribl Certified Observability Engineer certification offered by Cribl University. Regardless, using Cribl Stream to send data from one source to many destinations is something you’ll want to try. So if you’re ready, read on!

The rise of modern applications has kicked basic monitoring tools to the curb. With observability, teams can proactively know, in real-time, what’s happening across the entire stack. Observability allows us to take a holistic view of our IT systems and learn about the current state based on the environment and the data it generates. But how do you properly implement observability? Here are 6 guiding principles to make sure your IT and DevOps teams are set up for success.

Cribl places high importance on its core values of Customer First, Always; Together; Curious; Irreverent but Serious, and Transparent. We strive to embody these values every day, and a particular customer issue recently enabled us to exemplify them to that customer. Recently, the Cribl Support, Software Engineering, and Product Management teams worked together with our largest Cribl Cloud customer to resolve throughput issues that arose when integrating Cribl.Cloud with Azure Event Hubs (EH).

Observability is a growing practice that provides many benefits to IT and DevOps teams. With greater visibility into their environments, teams can determine the state of the system, predict issues, and mitigate them before end users are impacted. Observability makes data more usable and in turn, businesses reap the benefits of having great insights. Are you on the fence on whether to get started with your own observability practice? Check out these 12 observability benefits and get started today!

What do you get when you throw 50,000 attendees together with Darth Vader and Obi-Wan Kenobi in Las Vegas? Lightsaber battles and demos from Cribl Jedis fighting for the liberation of customer data from vendor lock-in, of course! AWS re:Invent 2022 was a total hit this year and we had such a great time showcasing to AWS customers how easy it is to realize the full potential of the cloud by unlocking data first. The week was full of exciting new launches, talks, happy hours, and more!

Organizations have different data lakes they use to search, whether it is Splunk, Qradar, or Sumo Logic just to name a few. Exabeam (UEBA Advanced Analytics) sits on top of those existing data lakes and pulls specific sources by running continuous queries every few minutes into Exabeam. The image below shows a Splunk query to pull windows event logs into Exabeam Advanced Analytics over the port (8089). The query is complex.

When we created Cribl Search, we wanted to give systems administrators the ability to query data without having to spend resources on collection and processing first — but we didn’t stop there. With Search, we’re also making it possible to query all the data you’ve already collected, processed, and kept in places like object stores, file systems, analytics tools, S3 buckets, or other data stores.