AWS Extends Kiro AI Tool to Generate Higher Quality Code
Amazon Web Services (AWS) today with the general availability of its Kiro artificial intelligence (AI) coding tool added additional capabilities, including a version that can now be invoked via a command line interface (CLI). At the same time, Kiro now enables property-based testing (PBT) to measure whether the code generated matches the behavior defined in […]
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 […]
Chronosphere Adds AI Remediation Guidance to Observability Platform
Chronosphere this week previewed artificial intelligence (AI) capabilities that are embedded into its observability platform that, in addition to helping identify the root cause of an issue, also provides remediation suggestions. Additionally, the company made available a Model Context Protocol (MCP) Server through which AI coding tools and agents will be able to query observability […]
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). […]
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.
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 […]
Qovery Adds Multiple AI Agents to DevOps Automation Platform
Qovery has added multiple artificial intelligence (AI) agents to its DevOps automation platform that, in addition to responding to natural language prompts and executing complex operations, also anticipates the next step in a workflow. Company CEO Romaric Philogène said the AI DevOps Copilot family of AI agents automate a range of tasks, including provisioning environments, […]
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.
Tabnine Adds Agents Capable of Automating Workflows to AI Coding Platform
Tabnine introduces Tabnine Agentic, a new generation of AI agents that automate multi-step DevOps workflows including refactoring, debugging, and documentation. Built on Tabnine’s Context Engine, these agents bring governance, cost control, and compliance to AI-powered code development.
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.
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.
Context Engineering: The Next Frontier in AI-Driven DevOps
Imagine a world where your on-call alerts are not just a cryptic message, but a rich, contextualized story of what’s happening, why it’s happening, and how to fix it. This is the promise of context engineering, a concept poised to redefine the role of artificial intelligence in DevOps. While AI has long been touted as […]
GitHub Adds Platform for Managing AI Agents Embedded in DevOps Workflows
GitHub today launched a platform for managing artificial intelligence (AI) agent workflows across the entire software development lifecycle (SDLC). Announced at the GitHub Universe 2025 conference, Agent HQ makes it possible to unify the management of AI agents developed by not just GitHub but also third-party providers, including Anthropic, OpenAI, Google, Cognition and xAI. As […]
Survey Surfaces Impact AI Coding Tools Are Having on DevOps Workflows
A survey of 206 IT leaders and executives finds that, with the rise of artificial intelligence (AI) coding tools, more application development teams are devoting more time to reviewing rather than writing code. Conducted by Enterprise Management Associates (EMA) on behalf of Perforce, the survey finds 57% of developers now spend more time on code […]