If you’re using Linux, I’m sure you bumped into journald: it’s what most distros use by default for system logging. Most applications running as a service will also log to the journal. So how do you make use of these logs to: In this post, we’ll answer all the above and more. We will dive into the following topics: There are lots of other options to centralize journal entries, and lots of tools to help.
What is the most important feature an Express.js application can have? Maybe using sockets for real-time chats or GraphQL instead of REST APIs? Come on, tell me. What’s the most amazing, sexy, and hyped feature you have in your Express.js application? Want to guess what mine is? Optimal performance with minimal downtime. If your users can’t use your application, what’s the point of fancy features?
Where are Docker container logs stored? There’s a short answer, and a long answer. The short answer, that will satisfy your needs in the vast majority of cases, is: From here you need to ship logs to a central location, and enable log rotation for your Docker containers. Let me elaborate on why with the long answer below.
There are 1.3 billion websites out there in the great unknown and it’s hard not to think about what makes them different from one another. Why do users flock to one website and ignore the other completely? One major differentiator is, of course, content. I’m not going to dwell on what type of content is better. Another reason why users stick to one website over another is the user experience. Today we’ll be looking at a third major differentiator: Website Performance.
Have you ever grown tired of running the same kubectl commands again and again? Well the good folks over at the Kubernetes team understand you. With the addition of custom resources and the operator pattern, you can now make use of extensions, or addons as I like to call them, to the Kubernetes API that help you manage applications and components. Operators follow Kubernetes principles including the control loop.
eBPF has revolutionized the observability landscape in the Linux kernel. Throughout our previous blog post series, I covered the fundamental building blocks of the eBPF ecosystem, scratched the surface of XDP and showed how closely it cooperates with the eBPF infrastructure to introduce a fast-processing datapath in the networking stack. Nevertheless, eBPF is not exclusive to kernel-space tracing.
If you’re running Solr and have to troubleshoot it (or maybe you just want a good overview!), then you’d probably want to collect logs, configs, maybe a snapshot of metrics and some system data, like top or netstat. We created a small tool for this exact task, creatively named solr-diagnostics. It’s been out there for almost two years, and we found it useful in our Solr consulting and production support engagements. So we thought it’s about time to spread the word.
In Part 1 we’ve described what container monitoring is and why you need it. Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and the applications they run. These servers and applications running on them are typically very static, with very long uptimes.
Even though containers have been around for ages, it wasn’t until Docker showed up that containers really became widely adopted. Docker has made it easier, faster, and cheaper to deploy containerized applications. However, organizations that adopt container orchestration tools for application deployment face new maintenance challenges.
Working with Java applications has a lot of benefits. Especially when compared to languages like C/C++. In the majority of cases, you get interoperability between operating systems and various environments. You can move your applications from server to server, from operating system to operating system, without major effort or in rare cases with minor changes.
