Operations | Monitoring | ITSM | DevOps | Cloud

In this blog, we compare Instana and Sysdig - two popular monitoring tools which claim to show APM metrics without need to instrument code.

In this blog, I will discuss about how to set up Prometheus and Grafana in EKS and how to monitor Python based applications using Prometheus.

As you’re juggling deployments, writing code, and attending meetings there’s not a great deal of time left for staying up to date with the latest trends in tech. The culture around performance is getting stronger — performance is absolutely a feature, yet the pressure is on to deliver more without sacrificing quality. The good news is that there are companies who have achieved their performance goals — and more.

“Change is the only constant in life.” This is a quote often attributed to the Greek philosopher, Heraclitus. In the world of application performance monitoring, you know this to be true. Things are always changing. New technologies force you to come up with new ways and processes for doing things. And new challenges force you to develop new methods of solving old problems. Performance monitoring is an old problem.

One of the joys of using the Ruby language is the many different ways that you can solve the same problem, it’s a very expressive language with a rich set of libraries. But how do we know which is the best, most efficient, use of the language? When we are talking about algorithms which are critical to the performance of your application, understanding the most efficient approach to take is essential.

The definition for APM (Application Performance Management) has evolved greatly over the past years. It has moved from specifically referring to the monitoring of an application’s experience, its code and the timing of its different building blocks, to a broader term that is used for anything related to the performance of the app. It also often includes all the related monitoring, log management and more.