Operations | Monitoring | ITSM | DevOps | Cloud

Implementing distributed tracing is fast becoming a fundamental expectation when building modern (distributed) systems. However, this is yet another thing for developers to learn, and configuring distributed tracing on Kubernetes is hard, right? Actually, no. Getting started with Jaeger on Kubernetes has never been easier.

Shipa, Corp., delivering a cloud native application management framework built to manage the full application lifecycle, today announced that it is open sourcing Ketch, Shipa’s deployment engine, under Apache License Version 2.0. This open source release is available on GitHub and follows the general availability launch of Shipa’s full application management framework in October.

On November 11, 2020, I had the pleasure of speaking with two incredible thought leaders in the DevOps space: Vivek Pandey, VP of Engineering at Shipa (https://www.shipa.io), and Patrick Deuley, Sr Product Manager at GitLab (https://www.gitlab.com). The topic of the discussion was “Monolith to Microservices,” and we covered three key areas: Starting out, Scaling and Developer Experience.

We created the Fleet Project to provide centralized GitOps-style management of a large number of Kubernetes clusters. A key design goal of Fleet is to be able to manage 1 million geographically distributed clusters. When we architected Fleet, we wanted to use a standard Kubernetes controller architecture. This meant in order to scale, we needed to prove we could scale Kubernetes much farther than we ever had.

If you’re an SRE or on a DevOps team working with Kubernetes and containers, you’ve undoubtedly encountered network connectivity issues with your microservices and workloads. Something is broken and you’re under pressure to fix it, quickly. And so you begin the tedious, manual process of identifying the issue using the observability tools at your disposal…namely metrics and logs.

The new Honeycomb Kubernetes agent is out! This post describes how infrastructure metrics contribute to observability, and then walks you through the steps to start sending your own Kubernetes data into Honeycomb. Follow the steps to start observing your infrastructure in production!