Today we’ve announced that we’ve officially added eBPF instrumentation to extend container observability with Sysdig monitoring, security and forensics solutions. eBPF – extended Berkeley Packet Filter – is a Linux-native in-kernel virtual machine that enables secure, low-overhead tracing for application performance and event observability and analysis.

Good news everyone! Or at least for all users of Raspberry Pi and the Raspbian operating system! We now provide official packages for Raspbian on ARM chips. You can find those packages on packages.icinga.com.

Within a Linux network or development system, launching a limited set of applications or services (often known as microservices) in a self-sustaining container or sandboxed environment is sometimes necessary. A container enables administrators to decouple a specific set of software applications from the operating system and have them run within a clean, minimal, and isolated Linux environment of their own.

Speed up your IBM Power servers like never before. In IBM Power System environments, processing time is costly and is measured in work units. A CPU hog on any Linux server can become expensive. Under-provisioned systems react slowly on queries from business applications, which then cause undesired end user or processing delays. As IBM Power servers typically run business critical workloads, response time and availability is key.

eBPF tracing is a broad and deep subject, and can be a bit daunting at first sight. However, when Brendan Gregg issued the dictum “Perhaps you’d like a new year’s resolution: learn eBPF!”, I figured it was as good a time as any to do something fun with it. Here at Circonus, we’ve talked about eBPF previously, so I had a starting point to look for an interesting problem to solve.

NOTE: This is part 2 of a post on how to monitor your server. For pre-requisites and how to monitor a windows-based server, read the earlier blog post.

This recipe is similar to the previous rsyslog + Redis + Logstash one, except that we’ll use Kafka as a central buffer and connecting point instead of Redis. You’ll have more of the same advantages.