Tricentis Preps Wave of Additional AI Testing Capabilities
Tricentis is providing early access to multiple artificial intelligence (AI) capabilities that it is gearing up to roll out later […]
Copilot Code Reviews for Azure Repos (public preview)
Today, we’re announcing the public preview of GitHub Copilot Code Review for Azure Repos, making the feature available to all
Your AI Coding Budget Is Becoming a Variable Cloud Bill
Platform and DevOps teams spent a decade learning to manage cloud as a variable cost. Metered usage, spiky demand, spend
AI Can Generate Your Infrastructure. Can Your CI/CD Pipeline Trust It?
Ask a platform engineer how much of their Terraform, Kubernetes manifests or CI/CD YAML was drafted with an AI assistant,
Automated Diagnosis Isn’t Automated Understanding: What Postmortems Teach Us About Building Trustworthy Incident AI
Anyone who’s ever been on an on-call rotation knows the feeling. A dashboard lights up green to red across a
The Missing Runtime for Long-Running AI Agents
Enterprise AI agents need more than stronger models. They need durable execution environments that can coordinate multi-step workflows, survive failures,
Moving from Minimus to Docker Hardened Images
The hardened-images space gets better when more people are working on the problem, and Minimus has been a valuable part
Is Java Enterprise Ready for AI? Absolutely
AI is transforming software engineering. For enterprise Java developers, the key question is whether Java and Jakarta EE are prepared
The Blind Spot Between Back‐End Metrics and User Experience
Engineering teams often face a frustrating scenario when application performance monitoring (APM) shows perfect Apdex scores and negligible error rates,
CI/CD for AI-Enabled Applications: Why Traditional Deployment Pipelines Need to Evolve
Traditional CI/CD pipelines are optimized around a familiar assumption: source code changes, automated tests validate the change, a build artifact