Blue-Green Deployments for GCP Managed Instance Groups with Harness
Learn how to set up and execute zero-downtime blue-green deployments for Google Cloud Managed Instance Groups (MIG) using Harness Continuous Delivery.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on DevOps, CI/CD, Automation and related technologies.
(Tech Talk) Shipping with Context Knowledge Graphs as the Backbone of AI-First Software Delivery
Knowledge graphs are essential to solving the context bottleneck in AI-First software delivery, which occurs because workflows, policies, and dependencies are siloed and invisible to AI agents. In this Tech Talk, Prateek Mittal ((Product Director of AI Core and Data Platform at Harness)) discusses the key concepts: Knowledge Graphs vs. Observability: Observability tells you "what is happening," while knowledge graphs tell you "what does that mean" by modeling structured relationships. They work together to link live signals to affected services or SLAs.
Introducing Harness Artifact Registry | Unified. Secure. Built for the Future Artifact Management
Managing build artifacts today is harder than it should be. Fragmented tools, security blind spots, and disconnected developer workflows make it difficult to keep builds safe, consistent, and production-ready. In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, shows how Harness Artifact Registry unifies artifact management across the entire software delivery lifecycle — from creation to deployment — while improving security and developer experience.
We Built an MCP Server
When I joined Kubex last year, the company was already well aware of the growing power of Large Language Models. As a company focused on intelligent resource optimization for Kubernetes, GPUs, and cloud infrastructure, generative AI didn’t feel like a threat so much as a natural extension of where the industry was heading. Kubex had already invested heavily in machine learning, but it was becoming clear that foundation models could unlock an entirely new class of capabilities for our customers.
Top 9 Observability Tools for AI-Assisted Development & Deployment
AI-assisted development is rapidly becoming the default way software is built. Code generation, AI copilots, agentic pull requests, and automated refactoring are now embedded directly into engineering workflows. While this shift dramatically increases delivery speed, it also introduces a new operational reality: production systems are changing faster than humans can fully reason about them. This is where observability becomes mission-critical.
What AI Has Never Seen: The Context Gap in Code Generation
Your AI coding assistant has read the entire internet. It knows every programming language, every framework, every best practice documented in Stack Overflow answers and GitHub repositories. It can generate a REST API handler in seconds that looks perfect with clean code, proper error handling, following all the patterns. But here’s what it’s never seen: your production traffic. Data from a real API request. Someone filling out a form with messed up or incomplete data.
The economics of a sovereign cloud
The BCG recently released a report on the cost of cloud. The findings? Hyperscalers are charging up to 30% more for their sovereign-cloud offerings. It supports an earlier notion that if you want control, compliance, and jurisdictional certainty, you have to pay a premium. At Civo, we think that is broken. As data volumes grow and AI workloads become central to business strategy, the economics of cloud computing are being re-examined.
How Civo is building the "cloud the way you want it"
As we move through 2026, the global cloud landscape is being reshaped by the drive for digital independence first discussed at Civo Navigate India 2025. This keynote featuring Mark Boost, Dinesh Majrekar, Josh Mesout, and Ben Norris laid the groundwork for a future where organizations no longer have to choose between the scale of the public cloud and the security of a private environment.
5 Common DevOps Monitoring Challenges and Solutions
Modern DevOps faces tough monitoring challenges due to distributed systems, containers, and microservices. Key issues include fragmented visibility, alert fatigue, tool overload, pipeline blindspots, and cloud cost inefficiencies.
Monitoring Checklist for Cloud Infrastructure
Cloud monitoring is essential for tracking performance, security, and costs in dynamic environments. With 94% of enterprises using cloud services and 81% adopting multi-cloud setups, maintaining control is critical. Here's what you need to know.