September 2022 Summaries

Kubernetes can be used as a Continuous Integration/Continuous Delivery (CI/CD) platform, leveraging its scalability and flexibility to deploy CI/CD pipelines. A CI/CD pipeline is an automated set of processes that software developers use to write, merge, compile, test, and deploy code. Kubernetes CI/CD offers benefits such as simpler deployment, built-in scalability, extensive control, lower costs, and the ability to implement GitOps. To build a CI/CD pipeline on Kubernetes, one can either deploy conventional CI/CD tools or use "Kubernetes-native" CI/CD software that takes advantage of native Kubernetes features. Popular CI/CD tools for Kubernetes include Tekton. Best practices for CI/CD and Kubernetes include setting quotas and limits, creating separate namespaces, isolating CI/CD operations, enabling autoscaling, backing up data and configurations, and using observability platforms like groundcover to monitor performance. While every CI/CD pipeline may not need to run on Kubernetes, it can help boost efficiency, scalability, and control over software development and deployment processes.

Prometheus is a widely adopted open-source monitoring and alerting toolkit originally built by SoundCloud in 2012. It provides four key features: a time-series database, a robust query language called PromQL, a pull-mode "scraper" for retrieving and storing metrics, and an alerter component for customized notifications. Prometheus has become the de facto standard for monitoring Kubernetes applications, with many organizations using it to collect metrics from their infrastructure and services. However, as the size of observability environments grows, Prometheus faces challenges such as single-server architecture, memory utilization, long-term data storage, and lack of "hybrid observability". Several alternatives are emerging, including Grafana Mimir, VictoriaMetrics, Promscale, and Thanos, which aim to address these challenges with improved scalability, performance, and feature sets. As the landscape continues to evolve, it's essential for users to stay informed about new developments and potential successors to Prometheus in the observability space.

The concept of sidecars in containers and microservices has become widespread, but they may not be the best solution. Sidecars slow down applications and add complexity to managing communications between services. However, service meshes like Istio have made it easier to manage these challenges by providing a centralized means of governing services. But, service meshes suffer from two key problems: high resource consumption and slow performance. The sidecar pattern doubles the number of containers running, consuming more resources and increasing latency. In contrast, eBPF (Extended Berkeley Packet Filter) offers a better solution by allowing for hyper-efficient, secure, and dynamic code to run directly within the Linux kernel, eliminating the need for sidecars and reducing overhead. This approach would simplify service mesh management, increase visibility and control, and reduce performance costs, making it an attractive alternative to traditional service meshes like Istio.