Binary CI/CD pass/fail signals do not adequately represent release risk in complex enterprise systems, where context and impact matter more than execution status.
Three protocols are shaping how AI agents interact with tools, other agents, and users. Here's what each one does, how they fit together, and when to reach for which.
Legacy identity governance fails in modern cloud environments. Learn how event-driven, AI-assisted models improve access control and reduce security risks.
This article explores the rise of platform engineering, the Golden Path vs. Jungle Path model, and how agentic AI is automating infrastructure governance.
Strong QA is not checklist work. It combines investigation, analytical thinking, and technical communication to find failure paths early and improve the system over time.
AI is transforming multi-cloud integration with real-time, decentralized, secure systems — improving compliance, APIs, and scalability across industries.
Observability costs spiral when teams optimize for visibility, not cost. Fix it by making spend visible, sampling aggressively, and cutting low-value data.
We analyzed 1,000 data pipeline incidents across 500+ environments and found that code-related failures still account for ~10% of all data quality issues.
Demonstrates how to expose Spring Boot metrics with Prometheus and build Grafana dashboards to track memory usage and error rates for production-grade Java services.
CI/CD pipelines are essential, but they carry risks if not designed correctly. This post discusses common security mistakes and shares practices to avoid them.