Survey Sees AI Coding Creating Need for More Software Engineers
A GitLab survey of 3,266 DevSecOps professionals shows AI is boosting code creation but increasing the need for skilled engineers, compliance challenges and human oversight.
How Hyperconnected AI Development Creates a Multi-System Secret Sprawl
If you’ve been building artificial intelligence (AI) tools lately, you’ve probably noticed something: Your development workflow has become incredibly connected. Tools such as model context protocol (MCP) sit at the center of it all, acting as the ‘brain’ that orchestrates how your large language model (LLM)-powered projects talk to databases, cloud services, APIs, design tools and messaging platforms. This hyperconnectivity makes rapid integration possible. We can now spin up […]
GitOps in the Wild: Scaling Continuous Delivery in Hybrid Cloud Environments
A deep dive into scaling GitOps for hybrid and multi-cloud environments, exploring architecture, governance, security, observability and real-world enterprise practices.
AI-Driven Performance Testing: A New Era for Software Quality
Discover how AI and large language models (LLMs) are revolutionizing performance testing—shifting from reactive load testing to predictive, continuous assurance powered by intelligent agents and automation.
The Future of Observability: Predictive Root Cause Analysis Using AI
In the past few years, systems have become more complex than ever. Microservices, Kubernetes, cloud environments and distributed application programming interfaces (APIs) have changed how we build and manage software. However, this complexity has also made it harder to find the root cause when things go wrong. That’s where observability and artificial intelligence (AI) come together to change the game — helping us move from reactive monitoring to predictive root cause analysis (RCA). […]
Why Your SLO Dashboard is Lying: Moving Beyond Vanity Metrics in Production
Discover how redefining service level objectives (SLOs) around business impact — not vanity uptime metrics — reduced incidents by 75% and saved $2.3M in lost revenue.
Vibe Coding Can Create Unseen Vulnerabilities
Vibe coding uses AI to write software fast — but without developer oversight, it can introduce security flaws, technical debt and compliance risks.
Five Great DevOps Job Opportunities
DevOps brings you a weekly jobs report, including, this week, opportunities at Amentum, Oliver James and Morgan Stanley Services Group.
MIT Researchers Propose a New Way to Build Software That Actually Makes Sense
MIT researchers propose a new framework to make software clearer and safer by organizing code into “concepts” and “synchronizations” for better visibility.
AIOps for SRE — Using AI to Reduce On-Call Fatigue and Improve Reliability
Site reliability engineering (SRE) has become an emergent niche practice invented at Google to become a foundation of contemporary enterprise performance worldwide. With the continued growth of microservices, a multi-cloud infrastructure and continuous deployment pipelines adopted by organizations, the operational surface area has increased to the extent that human personnel cannot monitor and manage it in real time. The effectiveness […]
DevSecOps in Practice: Closing the Gap Between Development Speed and Security Assurance
In the world of modern software development, speed is king. Teams are under constant pressure to release features, fix bugs and stay ahead of competitors. Yet, as development velocity increases, so does the risk of introducing vulnerabilities — an inconvenient truth that security teams have been sounding alarms about for years. This tension between speed and […]
5 Pillars of Successful Web App Development
Today, building a high-quality and competitive web application requires more than just clean code, a user-friendly UX and good development practices. The success of such a project also hinges on creating a strategic approach and prioritizing components that bring long-term value to both your business and your customer. The following five aspects — security, performance, user-centricity, scalability and cross-platform compatibility — define an efficient, future-proof app that […]
From Code to Confidence: Building AI Apps That Earn User Trust
As 65% of users report issues with AI applications, trust has become the new UX battleground. Learn how developers can build fair, transparent, and reliable AI systems through human-centered testing, inclusive feedback loops, and continuous trust monitoring from day one.
Gain Control of Your Innovation With Low Code Technologies
Low-code development and orchestration are redefining how enterprises build, connect, and scale digital systems. Discover how platforms like RunMyProcess empower teams to create applications faster, automate workflows, and drive collaboration, agility, and profitability across the enterprise.
Observe Adds Two AI Agents to Improve Observability
Observe Inc. introduces the AI SRE Agent and o11y.ai Agent to its observability platform—empowering DevOps teams to automate incident triage, generate OpenTelemetry code, and query application performance using natural language for faster, smarter debugging.
Kong Adds MCP Support to Tool for Designing and Testing APIs
Kong Inc. has integrated Model Context Protocol (MCP) support into Insomnia 12, enabling DevOps teams to design, test, and secure MCP clients and servers for AI-driven APIs—reducing misconfigurations and enhancing compliance in rapidly evolving AI environments.
How AI Code Assistants Can Save 1,000 Years of Developer Time
AI code assistants like GitHub Copilot and IBM watsonx Code Assistant are transforming software development—automating routine tasks, improving code quality, and saving developers up to 200 hours a year. The result: faster delivery, higher innovation, and a real competitive edge.
How AIOps is Revolutionizing DevOps Monitoring in the Cloud Era
As cloud-native systems grow more complex, traditional monitoring falls short. AIOps brings AI, automation, and predictive insights to DevOps—enabling real-time detection, diagnosis, and resolution across distributed environments for faster, smarter operations.
The AI-Powered Evolution of Software Development
Artificial intelligence is revolutionizing software development—accelerating coding, improving quality, and enabling autonomous operations. From GitHub Copilot to AI-driven DevOps, businesses leveraging AI tools are building smarter, faster, and more adaptive applications.
Is There Still a Difference Between DevOps and AIOps?
DevOps transformed software delivery through speed and collaboration. AIOps takes it further—adding AI-driven insight, anomaly detection, and intelligent automation. Together, they form the next evolution of IT operations: smart, adaptive, and self-healing pipelines.
DevOps Workflow: The Key Elements and Tools Involved
What does a modern DevOps workflow look like? Click to learn about the essential elements, tools, and practices involved in the effective work process.
Your Next Secrets Leak is Hiding in AI Coding Tools
AI coding tools are accelerating secrets sprawl in Kubernetes workflows. Learn where leaks happen and how platform teams can contain the risk.
Cybersecurity Laws Will Shape the Future of DevOps
From the EU’s NIS2 Directive to U.S. SEC breach disclosure rules, cybersecurity regulation is accelerating faster than code releases. DevOps teams must evolve into RegOps—embedding compliance, traceability, and trust directly into their CI/CD pipelines. The future of DevOps isn’t just agile—it’s accountable.