A blog site on our Real life experiences with various phases of DevOps starting from VCS, Build & Release, CI/CD, Cloud, Monitoring, Containerization.
Remember when DevOps was the revolutionary force transforming software delivery? Fast-forward to today, and a new shift is underway – Platform Engineering is taking center stage. But is this just another buzzword, or the natural evolution of modern tech infrastructure?
Continue reading “The Evolution of DevOps to Platform Engineering: A Must-Know for CTOs and CIOs”
Imagine starting a new coding project, but you have no folder structure-
Managing a large-scale Kubernetes cluster with hundreds or even thousands of services is a challenging yet rewarding endeavor. One critical aspect of achieving success at scale is designing a robust namespace strategy that balances isolation, security, and operational efficiency. In this blog, we’ll dive deep into various namespace design approaches, discuss real-world challenges, and provide practical examples and code snippets to help you decide which strategy fits your organization best.
Continue reading “Designing a Namespace Strategy for 1000+ Services in Kubernetes”
The Amazon EKS AutoScaler automatically adjusts the number of worker nodes in an Amazon EKS cluster based on resource utilization and scaling demands.
Before we started using EKS Cluster Autoscaler, managing node scaling in our Kubernetes cluster was a constant struggle. Here’s what we were dealing with:
High Costs: We had to keep extra EC2 nodes running all the time to avoid pod scheduling issues — even when they weren’t being used.
Pod Failures: If we tried to reduce node count to save money, pods would often stay Pending due to lack of resources.
Manual Work: Scaling nodes up or down was a manual task—time–consuming and error–prone.
Slow Deployments: During deployments or traffic spikes, our workloads would get stuck because there weren’t enough resources.
Unpredictable Demand: Our workloads change frequently, but our cluster capacity doesn’t— leading to overuse or underuse of nodes.
These challenges pushed us to explore Cluster Autoscaler, and it turned out to be a game–changer
Why Compare Confluent Kafka On-Premises, Confluent Kafka on Azure, and Azure Event Hubs?
When it comes to event streaming, choosing the right platform isn’t just a technical decision — it’s a strategic one. The wrong choice could leave you battling performance bottlenecks, spiraling costs, or operational headaches.
So, what’s the challenge?
Each solution — Confluent Kafka On-Prem, Confluent Kafka on Azure, and Azure Event Hubs — brings distinct strengths to the table. Understanding those differences is crucial to finding the perfect fit for your architecture.
