Operations | Monitoring | ITSM | DevOps | Cloud

In the early days, people debated how safe it was to store their money in the bank; now, we debate running databases on Kubernetes. Over the years, Kubernetes has evolved significantly, transforming into a capable platform for handling various workloads, including stateful ones. In this blog, I will consolidate some of the best arguments from both sides and provide you with some points to discuss with your team lead in your next conversation. It's an interesting topic with varying answers.

Security and compliance: Many industries, especially those governed by regulations like HIPAA, the PCI DSS, or the GDPR, require detailed logs for compliance and to trace security incidents. Troubleshooting and forensic analysis: If something goes wrong—whether due to accidental configuration changes or malicious activity—having detailed logs helps diagnose the root cause and quickly remediate it.

Prometheus is one of the most popular open-source monitoring and alerting tools. Setting up Prometheus with Docker Compose can make your monitoring stack easier to deploy and manage if you're running containerized applications. This guide will walk you through everything you need to get Prometheus up and running with Docker Compose, from installation to configuration and setting up basic alerts.

Kubernetes has been facilitating container orchestration for around a decade for both stateful and stateless application workloads. With the recent rise of AI and the advent of tools like Kubeflow and Argo Workflows, Kubernetes is also becoming a first-class citizen when it comes to running AI workloads. When you are training a model on K8s, you may be tweaking many parameters and have to test each of them one by one.

Over the past few years, Kubernetes (K8s) has become the preferred method of orchestrating containers and microservices. Its self-healing, high scalability, and open-source nature make it appealing to a wide range of users. However, deploying, running, and scaling containerized applications and microservices with Kubernetes can be challenging. The Kubernetes community keeps growing, but there still aren’t that many experienced K8s engineers.

Kubernetes has revolutionized cloud-native applications, but networking remains a crucial aspect of ensuring scalability, security, and performance. Default networking approaches, such as iptables-based packet filtering, often introduce performance bottlenecks due to inefficient packet processing and complex rule evaluations. This is where Calico eBPF comes into play, offering a powerful alternative that enhances networking efficiency and security at scale.

For many, Cloudflare provides an essential suite of network security tools that their organization integrates with deeply. One such tool is "Cloudflare Tunnel" - a secure way to connect resources to Cloudflare without a publicly routable IP address. When deploying sensitive applications to Cycle, Cloudflare Tunnel can be leveraged to ensure all traffic is routed through Cloudflare before reaching your environment's load balancer. This extra layer of security provides quite a few benefits.

As applications become more complex, managing containers efficiently is key to scaling and maintaining performance. Kubernetes (also known as K8s) automates this process, making it easier to handle scaling, failures, and uptime. If you're new to Kubernetes, understanding the platform and how it's used is essential for managing your applications seamlessly. Let’s dive in and explore how Kubernetes makes it all possible.

As generative AI tools like ChatGPT and Gemini continue to revolutionize the way we work, offering benefits such as increased efficiency and productivity, their adoption has seen a significant surge in workplaces throughout 2024, with 75% of employees globally reporting that they used AI tools at work, according to Gartner.