Operations | Monitoring | ITSM | DevOps | Cloud

In the fast-paced world of software development, the need for effective tools that can streamline workflows is paramount. Yet, amidst a plethora of available options, engineering managers often face the conundrum of choosing between an Internal Developer Platform and an Internal Developer Portal. Both have their merits, but which one is the best fit for your organization? In this article, we'll delve into the core features, strengths, and limitations of each to help you make an informed decision.

If you’re thinking of running OpenSearch on Kubernetes, you have to check out the OpenSearch Kubernetes Operator. It’s by far the easiest way to get going, you can configure pretty much everything and it has nice functionality, such as rolling upgrades and draining nodes before shutting them down. Let’s get going 🙂

In the evolving landscape of software development, two terms frequently emerge: "Internal Developer Platform" (IDP) and "Internal Developer Portal". These terms are often used interchangeably, leading to confusion. In this article, we aim to differentiate the two and highlight their importance in modern software engineering.

In this article, we will be covering how to monitor Kubernetes using Graphite, and we’ll do the visualization with Grafana. The focus will be on monitoring and plotting essential metrics for monitoring Kubernetes clusters. We will download, implement and monitor custom dashboards for Kubernetes that can be downloaded from the Grafana dashboard resources. These dashboards have variables to allow drilling down into the data at a granular level.

This is the first post of a 2 part series where we will set up production-grade Kubernetes logging for applications deployed in the cluster and the cluster itself. We will be using Elasticsearch as the logging backend for this. The Elasticsearch setup will be extremely scalable and fault-tolerant. ‍

In this tutorial, we will learn about configuring Filebeat to run as a DaemonSet in our Kubernetes cluster in order to ship logs to the Elasticsearch backend. We are using Filebeat instead of FluentD or FluentBit because it is an extremely lightweight utility and has a first-class support for Kubernetes. It is best for production-level setups. This blog post is the second in a two-part series. The first post runs through the deployment architecture for the nodes and deploying Kibana and ES-HQ.

We kicked off the start of the Day 2 with our host Nigel Poulton as he prepared us with a quick rundown of the highlights from the first day before giving attendees a taste of what to expect from the rest of the event. After this point, Nigel brought Kelsey Hightower to the stage for his keynote session with Mark Boost and Dinesh Majrekar. If you missed our Day 1 recap, check it out here.

RabbitMQ is a messaging broker that helps different parts of a software application communicate with each other. Think of it as a middleman that takes care of sending and receiving messages so that everything runs smoothly. Since its release in 2007, it's gained a lot of traction for being reliable and easy to scale. It's a solid choice if you're dealing with complex systems and want to make sure data gets where it needs to go.