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Provision a fresh Docker Registry with Terraform, build your container image into it, and deploy to Kubernetes in one One pipeline. One click. It provisions a fresh Docker Registry with Terraform, builds your container image into it, and deploys that image to Kubernetes. Every run creates a uniquely named registry, so you never hit naming conflicts. Creating Docker registries by hand every time you spin up a new service or environment gets tedious fast.

Compare the best Kubernetes cost management tools for 2026, from Kubecost and OpenCost to CloudZero, on allocation depth, scale, and pricing model.

"Why do I need to give Flyway this extra database?" That's one of the most common blockers we hear from users setting up a Flyway project. Flyway has long had a concept of a build database or shadow database that is a dedicated sandbox database for Flyway to do background work in. It's required for Flyway to be able to simulate what running a set of migrations will do to a database.

We have all watched AI speed up the way we write software. With tools like Copilot and ChatGPT, developers can spin up boilerplate, write complex functions, or draft entire micro services in minutes instead of days. It feels like magic. But there is a silent catch that we do not talk about enough: writing the code is only Day 1. The real challenge is Day 2 operations, which is everything that happens after that code is deployed.

India is the world's fourth-largest economy and accelerating fast. Here's why it should be on your network roadmap. Few markets combine scale, speed, and government intent the way India does right now. With a digital economy on track to reach USD $1 trillion by 2030, hyperscalers committing tens of billions in fresh investment, and connectivity infrastructure undergoing a generational upgrade, India has become one of the most consequential expansion decisions a technology business can make.

Most of what runs on a modern platform is built to stay up. Applications serve requests, workers process queues, and managed services keep databases and caches available around the clock. But a meaningful share of the real work does not fit that always-on shape.

When I ask an AI agent to change code, I also want it to run the application and test what it changed. Asking it to write some tests is a start. But if it invents the expected responses from the same assumptions it used to write the code, those tests can miss the same mistake. Traffic replay gives the agent something concrete to test against: requests and responses captured from a working application.