CloudBees Smart Tests: AI-Driven Test Intelligence for Faster Software Delivery

CloudBees Smart Tests is an AI-powered test intelligence solution designed to optimize software testing processes by drastically reducing execution time and improving feedback speed. Built on advanced machine learning, it automates test triage, identifies flaky tests, and intelligently prioritizes test suites to deliver faster results. This solution helps teams reduce cloud computing costs by up to 3–5 instances per test hour and accelerates release velocity by up to 2x annually. Part of the CloudBees Unify platform, it integrates seamlessly with modern DevOps workflows, offering AI-driven test selection, intelligent scheduling, and automated failure insights. Ideal for engineering teams focused on continuous integration, delivery, and orchestration, CloudBees Smart Tests empowers developers to deliver high-quality software faster and more efficiently.

Key Features:

• AI-Driven Test Selection: Automatically identifies and runs the most relevant tests based on code changes.
• Test Triage Automation: Detects and categorizes test failures to reduce debugging time.
• Flaky Test Identification: Pinpoints unreliable tests to improve test suite stability.
• Intelligent Scheduling: Optimizes test execution order for faster feedback.
• Cloud Cost Reduction: Saves up to 3–5 cloud instances per test hour.
• Accelerated Release Velocity: Increases release speed by up to 2x annually.
• Automated Notifications: Sends real-time alerts on test failures and resolution insights.
• Integration with DevOps: Part of CloudBees Unify, supporting Agentic DevOps, CI/CD, and Release Orchestration.

Pricing: CloudBees Smart Tests is available through a subscription model as part of the CloudBees Unify platform. Pricing details are not publicly disclosed and are typically tailored to enterprise needs.

Conclusion: CloudBees Smart Tests is a powerful AI solution that transforms software testing into a faster, smarter, and more cost-effective process. By leveraging machine learning to optimize test execution and reduce overhead, it enables engineering teams to achieve higher velocity and reliability in their software delivery pipelines.