Development operations, CI/CD, and automation
Found 190 articles
Explore advanced patterns for creating scalable Page Object Models that thrive in extensive test environments, enhancing maintainability and efficiency.
Understanding context engineering is essential for optimizing production agentic systems and overcoming recurring failures.
Real-world challenges in agentic AI deployments highlight the need for rigorous runtime control systems to mitigate unexpected behaviors.
Microsoft Foundry IQ redefines semantic search by incorporating nuanced reasoning, enabling complex queries for improved data retrieval and analysis.
Kata Containers 4.0 introduces a Rust-based runtime, optimizing memory safety and efficiency for AI agent sandboxing in Kubernetes environments.
Despite being largely replaced by Agile, the Waterfall model still subtly influences software development practices in many organizations.
Agentic SRE enhances site reliability engineering by integrating AI agents to autonomously manage reliability tasks, empowering teams to respond effectively.
When integrating AI outputs into workflows, it's essential to treat them as user input, not definitive solutions, to avoid unintended errors.
Spec-driven development faces ongoing issues, revealing that specifications alone won't ensure accuracy without real-time updates from developers.
A recent demo showcases AI's potential for rapid code deployment, yet a seasoned developer remains skeptical about its practicality and impact.
Exploring the distinct security concerns of agent platforms reveals critical differences between the tool and sandbox layers.
Ryan Gold, the Cardinals' VP of player personnel, has been suspended indefinitely by the NFL for violating gambling rules, with plans to appeal the decision.
AI agents often make decisions without traceable reasoning; understanding their thought processes is vital for effective deployment and oversight.
CI/CD pipelines may indicate success, but they lack the ability to verify ongoing alignment with organizational needs.
Entain is restructuring its workforce, cutting around 500 jobs as it navigates rising UK tax pressures affecting the gambling industry.
A new DevOps agent aims to automate incident remediation by using internal wiki runbooks, reducing reliance on engineers at critical hours.
Modern applications are embracing polyglot persistence, blending various database models to meet diverse data needs and drive efficiency.
Teams can enhance their AI governance by documenting their decisions in an AI Working Agreement, ensuring clarity and consistency in workflows.
Explore how PAL, Tracer, and Clipboard can transform Pega debugging from guesswork into a precise performance optimization process.
100% code coverage often misleads teams; it reflects executed lines, not reliable test outcomes, leading to costly gaps in quality assurance.