Articles about Continuous Integration

AI-assisted tools like GitHub Copilot and Cursor are accelerating how fast developers write code — but most teams are still stuck in old testing workflows. The result? Pull requests are opened and merged without thorough testing, bugs slip into production, and QA becomes overwhelmed. This article explores the real reasons why developers avoid testing (hint: it’s not laziness), and shows how adding preview environments to every PR removes the friction. A must-read for startups moving fast with AI but falling short on quality.

Explore the best Heroku alternatives in 2024, with a focus on Bunnyshell's multi-cloud support, ease of use, and powerful automation. Compare top platforms like AWS, DigitalOcean, and Azure to find the perfect cloud solution for your needs.

Discover the most effective strategies for end-to-end testing in 2025. This whitepaper explores how modern engineering teams can improve software quality by shifting testing left, automating critical user flows, and using preview environments for every pull request. Ideal for CTOs and engineering managers leading fast-moving development teams.

End-to-end testing in microservices can make or break your release velocity. This comprehensive guide explores how engineering leaders can balance quality and speed in 2025 by rethinking E2E testing strategies. From orchestrating services and taming flaky tests to leveraging full-stack preview environments (with platforms like Bunnyshell) for every pull request, we delve into best practices to ensure your distributed system works flawlessly – without grinding development to a halt.

AI tools like Copilot and Cursor help developers move fast, but they also introduce fragile code that can quietly break CI pipelines. In this post, we explore why AI-generated code often passes unit tests but fails in integration - and how ephemeral preview environments per pull request can catch these issues before they escalate. Ideal for startups moving fast with AI and struggling with flaky pipelines, slow QA, or post-merge surprises.

Stop losing sprints to late-stage feature changes. Discover why 60% of features need significant revisions after PM review, and how forward-thinking product teams are seeing features as they're built—not weeks later in staging. Learn the real cost of delayed feedback and the solution that's cutting development time by 50%.

Looking for a Qovery alternative? Bunnyshell offers advanced cloud deployment features like Environment as Code, GitOps, and automated pipelines, making it the ideal solution for streamlining your DevOps process.

The AI era has redefined how we build software - faster iterations, smarter tools, and higher expectations. But with this acceleration comes complexity: heavy local workloads, risky merges, delayed feedback, and slow rollouts. In this new world of generative and agentic AI, traditional dev setups just can't keep up. That’s where Bunnyshell steps in. This guide explores five powerful ways Bunnyshell’s ephemeral environments empower teams to ship faster, test smarter, and deploy with confidence - turning the promise of AI-assisted development into a streamlined, production-ready reality.

Bunnyshell vs Render: Discover which platform suits your development workflow. We compare Bunnyshell’s AI-first ephemeral environments with Render’s easy-to-use PaaS approach—helping you choose the right tool for speed, scale, and smart testing.

Learn CI testing best practices that can enhance your software development process, along with key principles and benefits of adopting CI/CD pipelines.