Operations | Monitoring | ITSM | DevOps | Cloud

Tracing is a critical part of monitoring application performance, especially as organizations shift to deploying services using distributed systems, serverless computing, and containerized environments. Teams need real-time, end-to-end visibility into all of the traces relevant to performance issues such as an application outage or an unresponsive service, but managing tracing costs often results in gaps in valuable tracing data.

It was a dark and stormy night. Not really, of course; it was warm and pleasantly mild (the weather never seems to co-operate on these occasions), but indulge me by imagining appropriate meteorological conditions for the spine-tingling story I’m about to relate. It was Morgan’s very first night on call, and they were a mite nervous, as you can imagine.

Whether you write code to save the bees, build the latest CMS, or teach others to become a developer: we’ve got your back. We’ve always offered AppSignal for free to maintainers and do-gooders who asked, such as Elixir School, Code::Stats and the MEANS Database. Starting today, we want to spread the word to all open-source maintainers and volunteer organizations that AppSignal is 100% free for them.

This article goal is to provide you guidance to start monitoring a small infrastructure, cluster monitoring and more complex topics won't be covered here. We also assume you are running instance on Amazon Web Services, Azure, Google Cloud, OVH, Scaleway... and we will not covering hardware monitoring like switch, routers, firewall...

Thanks to Linus Torvalds, the creator of not only Linux, but also the most popular version control system - Git, multiple developers can simultaneously work on the development of the same application, ramping up the speed of production. Git was revolutionary - it enabled developers to keep track of code changes and collaborate seamlessly across different projects.

Most of us have learned the hard way that it’s usually cheaper to fix something before it breaks and needs an expensive emergency repair. Because of that, I like to keep track of what’s happening in my house so I know as early as possible if something is wrong. As part of that effort, I have a temperature sensor in my attic attached to a Raspberry Pi, which Prometheus scrapes every 15 seconds so I can view the data in Grafana.

Sentry is excellent at capturing runtime errors in your applications. With the recent additions of performance monitoring and release health, it can further help as you build and ship code. Recently we used Sentry to ensure we didn’t break Sentry while doing a large refactor. When replacing an API or code path with a new implementation you’ll likely ‘deprecate’ the old path, but how do you know when that old path is finally not in use?

In 1927, the world was introduced to the origins of Artificial Intelligence (AI) in the form of a robot in the movie Metropolis. Throughout nearly a century since then, movies have continued to iterate on the complexities of AI, as both a fun take on it and serious commentary on the potential concerns and consequences. This is all well and good, but as AI has continued to evolve, we find ourselves asking, “how can we actually use this to make our lives easier?”

As a Senior Solutions Engineer helping customers deploy cloud-native technologies, I have been using Docker and Rancher for more than five years. Heck, I even helped steer Rancher for offline use when it was the 0.19 release. I have loved the product and company for YEARS. We all know how complicated it is to set up Kubernetes, and customers love Rancher because it simplifies that rollout.

Apache Hadoop is an open-source software framework that can process and distribute large data sets across multiple clusters of computers. Hadoop was designed to break down data management workloads over a cluster of computers. It divides data processing between multiple nodes, which manages the datasets more efficiently than a single device could. Here is our list of the best Hadoop monitoring tools.