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‍Flaky tests are automated tests that pass or fail inconsistently without changes to the code. In this guide, you’ll learn why flaky tests happen, how to detect them automatically in CI pipelines, and how modern platforms prevent them from slowing teams down. Your test went well three times yesterday. It didn't work this morning. You ran it again without changing anything, and now it works. Congratulations, you've just passed a flaky test, and now someone's day is going to be ruined.

A DevOps pipeline is a critical part of modern software delivery. It is a series of automated steps that move code from commit to production quickly, reliably, and consistently. At its core, a DevOps pipeline is a system that helps teams build, test, and release apps in an easier way. It cuts down on manual work and mistakes. This helps teams send out updates more often, make better software, and react quickly when the business needs change.

At SREday NYC 2026, the ShipTalk podcast welcomed Birol Yildiz, Co-founder and CEO of ilert, for a conversation about the next evolution of incident response. In the episode, ShipTalk host Dewan Ahmed, Principal Developer Advocate at Harness, spoke with Birol about how artificial intelligence is transforming reliability engineering—from simply assisting engineers during incidents to autonomously diagnosing and resolving outages.

Most engineering teams know the difference between “we have tests” and “we know we’re well-tested.” Your CI builds may be green, but without code coverage, it’s hard to prove how much of your code is actually exercised by automated tests. Code coverage measures what percentage of your code runs during tests (lines, branches, and functions), and when you wire it into CI gates, it becomes an enforceable quality signal and not a vanity metric.

Internal platform adoption usually doesn’t fail because developers “hate standards.” It fails because the platform doesn’t make their day easier. If your portal still means waiting, waiting on an environment, waiting on an approval, waiting on the platform team, it becomes one more tab that people stop opening. But if the platform lets engineers get the common stuff done quickly (with guardrails that keep things consistent), they’ll come back on their own.

‍ We've all been there. You push a PR, grab coffee, check Slack, maybe start a side conversation — and your build is still running. Multiply that across a team of 50 engineers, and you're looking at hours of lost focus every single day. Slow CI/CD builds don't just waste time. They generate a steady stream of "CI is slow" tickets that eat into your platform team's roadmap. Intelligent caching is one of the fastest ways to break that cycle.

Definition: Parallel execution in CI is the practice of running independent build, test, or deployment tasks concurrently to reduce feedback time, improve resource utilization, and control infrastructure costs. Developers often spend almost half their time waiting for builds that could be faster. Simply adding more resources is not enough. Real improvements come from planned parallelism, using concurrency together with test intelligence, caching, and strong governance.

Definition: CI pipeline optimization is the practice of reducing build and test time and the cost per build by running only what matters, reusing unchanged components, and enforcing standardized governance. Platform teams are wasting thousands of hours every year because their pipelines aren't working right. Developers wait 45 minutes for builds. Jenkins consumes 20% of your team's capacity on maintenance.