Cloud Cost Optimization Isn't Broken , The Approach Is
Cloud Cost Optimization Isn't Broken , The Approach Is.
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Architecting Trust: The Blueprint for a "Golden Standard" Software Supply Chain | Harness Blog
We’ve all seen it happen. A DevOps initiative starts with high energy, but two years later, you’re left with a sprawl of "fragile agile" pipelines. Every team has built their own bespoke scripts, security checks are inconsistent (or non-existent), and maintaining the system feels like playing whack-a-mole. This is where the industry is shifting from simple DevOps execution to Platform Engineering.
Backstage Alternatives: IDP Options for Engineering Leaders | Harness Blog
Backstage alternatives fall into three real choices: build and own a framework, buy a fully managed IDP product, or choose a hybrid path that reduces maintenance but keeps Backstage at the core. The trade-off is not "free vs paid" but engineering headcount, governance maturity, time to value, and how actionable your portal is across CI/CD, IaC, and environments. The best commercial IDPs go beyond catalog and documentation.
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.
(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.
Qwiet AI Is Now Harness SAST and SCA | Harness Blog
Modern application security is struggling to keep up with AI-driven development and cloud-native scale, especially when security feels bolted onto CI/CD instead of built in. Harness SAST and SCA bring AI-powered application security testing natively into the Harness platform, reducing noise and alert fatigue. By identifying only vulnerabilities that are actually reachable in production code, teams get findings they can trust and act on faster.
Harness AI January 2026 Updates: Human-Aware SRE and Smarter API and Application Security | Harness Blog
Harness AI is starting 2026 by doubling down on what it does best: applying intelligent automation to the hardest “after code” problems, incidents, security, and test setup, with three new AI-powered capabilities. These updates continue the same theme as December: move faster, keep control, and let AI handle more of the tedious, error-prone work in your delivery and security pipelines.
Build vs Buy IaC: Choosing the Right IaCM Strategy | Harness Blog
Have you ever watched a “temporary” Infrastructure as Code script quietly become mission-critical, undocumented, and owned by someone who left the company two years ago? We can all related to a similar scenario, if not infrastructure-specific, and this is usually the moment teams realise the build vs buy IaC decision was made by accident, not design.
How to Scale GitOps Without Hitting the Argo Ceiling | Harness Blog
The Argo ceiling is a predictable scaling challenge, not a failure of Argo CD or GitOps. As clusters and teams grow, visibility, governance, and orchestration fragment without a control plane. Script-heavy workflows and manual processes slow delivery and increase risk at scale. A GitOps control plane enables unified visibility, structured workflows, automated guardrails, and secure secret management. GitOps has become the default model for deploying applications on Kubernetes.