Operations | Monitoring | ITSM | DevOps | Cloud

For the world’s largest financial institutions, places like Citi and National Australia Bank, shipping code fast is just part of the job. But at that scale, speed is nothing without a rock-solid security foundation. It’s the non-negotiable starting point for every release. Most Harness users believe they are fully covered by our fine-grained Role-Based Access Control (RBAC) and Open Policy Agent (OPA).

This guide walks through practical ways to embed cost awareness directly into CI/CD workflows so development teams can make cost-informed decisions before deployment. You’ll learn how to implement automated cost feedback loops, introduce pipeline budget guardrails, and use Harness Cloud Cost Management to align DevOps velocity with FinOps accountability.

In Part 1, we argued that most dev teams start in the wrong place. They obsess over prompts, when the real problem is structural: agents are dropped into repositories that were never designed for them. The solution was to make the repository itself agent-native through a standardized instruction layer like AGENTS.md. But even after you fix the environment, something still breaks. The agent starts strong.

The pace of AI-assisted development has outgrown how most teams actually ship. Harness is closing that gap. Engineering teams are generating more shippable code than ever before — and today, Harness is shipping five new capabilities designed to help teams release confidently. AI coding assistants lowered the barrier to writing software, and the volume of changes moving through delivery pipelines has grown accordingly. But the release process itself hasn't kept pace.

Discover why Terraform has become a vendor lock-in risk with HashiCorp's licensing changes. This guide explores practical strategies to escape Terraform lock-in, including OpenTofu migration paths and how Harness IaCM enables vendor-neutral infrastructure management across multiple IaC tools.

Here's a scenario that probably sounds familiar: a developer needs a sandbox environment to test something. They file a ticket. Then they wait. And wait. Maybe a day goes by, maybe three. Meanwhile, your platform team is buried in provisioning requests, and somewhere, someone has already spun up an unsanctioned workaround that bypasses every governance policy you've put in place. It's a lose-lose. Developers lose velocity, platform teams lose their sanity, and security gaps quietly multiply.

The catastrophic TeamPCP exploit in March 2026 demonstrated that "open execution" models, in which third-party code runs with full privileges, have made CI/CD pipelines a primary target for global credential harvesting. There are better architectures. On March 19th, the risks of running open execution pipelines — where what code runs in your CI/CD environment is largely uncontrolled — went from theoretical to catastrophic.

This comprehensive guide covers the fundamentals of load testing, key differences from stress and performance testing, step-by-step execution methods, popular tools, and best practices to help teams build resilient systems with confidence. In today's always-on digital economy, a single slow page or unexpected crash during peak traffic can cost businesses thousands or even millions of dollars in lost revenue, damaged reputation, and frustrated customers.

Taking a look back over the last ten years in enterprise technology, paradigm shifts are occurring more frequently. For example, the maturity of DevOps/Platform Engineering and Cloud Native infrastructure has occurred. The new frontier depending where you are in adoption is AI. As your adoption and maturity curve progress, operationalizing these paradigms become important.

For the past few years, the narrative around Artificial Intelligence has been dominated by what I like to call the "magic box" illusion. We assumed that deploying AI simply meant passing a user’s question through an API key to a Large Language Model (LLM) and waiting for a brilliant answer.