Operations | Monitoring | ITSM | DevOps | Cloud

Need to monitor a UNIX-like system, but can’t install Netdata on it? With our SNMP collector and Net-SNMP, you can get basic system information with just a bit of relatively quick and easy configuration.

At observIQ, we use the OTel collector to collect host/container-level metrics and logs from our systems. But to get more detailed monitoring of our applications (APM), we use the OTel SDK and instrumentation libraries. This post aims to provide a quick start to setting up tracing exporting to a local Jaeger instance.

Log data is big data! But that’s not why it’s such a big deal. Log data can be really useful if you know what to do with it — which is where log analysis and analytics comes in. Let’s take a look at this valuable activity, starting with what log data can tell us and moving into how we can use analytics to inform business practices. (This article was written in collaboration with Muhammad Raza.)

At Cribl, we understand precisely what challenges our customers face when running complex searches, and the importance of getting exactly what they need with their queries. Cribl Search’s latest feature, Operator Preview, allows data analysts to test search operators without committing to a full search. It saves time, reduces costs, and streamlines your everyday data analysis.

Depending on your business, MTTR stands for mean time to repair or mean time to recovery – but it can also mean resolution, resolve, or restore. No matter how you define it, the basic measurement is the same: it’s the time it takes from when something goes down to when it is back and fully functional. This includes everything from finding the problem to fixing it. For ITOps teams, keeping MTTR to an absolute minimum is crucial.

The explosive growth of interconnected data across distributed systems has disrupted traditional development, DevOps, and ITOps practices and forced many organizations to rethink their cloud strategies. Higher-velocity feature development and more responsive support requests involve developers throughout the delivery cycle and require them to monitor and observe application behavior before releasing it to production.

This release is all about improving our Azure DevOps integration. According to our super sea-cret metrics, Azure DevOps is our users’ third most popular Git hosting service, after GitHub and Bitbucket. That explains why so many of you have sent in support tickets or submitted feature requests to make the integration with Azure match the excellent experience users have with our Bitbucket, GitHub, and GitLab integrations.