Tag: artificial intelligence
CI/CD for AI-Enabled Applications: Why Traditional Deployment Pipelines Need to Evolve
Prem Kumar Gadhanki | | artificial intelligence, CI/CD, continuous delivery, devops, MLOps, software deliveryTraditional CI/CD pipelines are optimized around a familiar assumption: source code changes, automated tests validate the change, a build artifact is produced, and the application is promoted through environments. AI-enabled applications complicate ...
How to Avoid Repeating the “Automate Everything” Mistake Due to AI FOMO
Alexey Golubev | | AI engineering, AI FOMO, AI Governance, AI implementation, AI in DevOps, AI maturity model, AI productivity, AI ROI, AI SDLC maturity, AI strategy, AI tools, AI-Driven DevOps, artificial intelligence, Cursor, DevOps AI adoption, devops automation, GitHub Copilot, Kubernetes AI, software development lifecycleThe DevOps community has already experienced technological extremes. You might recall the time when automation was thought of as a panacea for all possible engineering issues, and the slogan “Automate Everything” was ...
Why Self-Healing Tests Need a Deployment Gate
Suneet Malhotra | | artificial intelligence, CI/CD, devops, Self-Healing Automation, software testing, test automationWhen an end-to-end test fails after a front-end change, the repair often looks routine. A class name changed. A button moved. A selector that used to be unique now matches two elements ...
The Rise of AI-Native DevOps: How AI Is Reshaping Software Delivery in 2026
For years, DevOps had a pretty straightforward mission: help teams ship reliable software faster by getting development and operations folks working together. Tools like automation, continuous integration, continuous delivery, infrastructure as code, ...
Atlassian Underpins Code Creation With New Agentic Insight Channels
Adrian Bridgwater | | artificial intelligence, automation, CI/CD, cloud, code, developers, devops, digital transformationAtlassian used its Team '26 user conference this month in Anaheim to explain how its platform has now further evolved to underpin the reality of what the company defines as the AI‑native ...
Survey: Java Developers Wrestling With Massive Amounts of Technical Debt
Mike Vizard | | AI coding tools, AI functionality, artificial intelligence, cloud computing costs, Common Vulnerability and Exposure (CVE), cost-driven migration, dead code, developer productivity, Java applications, Java developers, Java versions, Java Virtual Machine (JVM), language model integration., large data access, long-term support, migration to OpenJDK, observability, OpenJDK, Oracle pricing concerns, security features, technical debt, vulnerabilitiesA global survey of 2,039 Java developers published today finds 63% reporting that dead and unused code adversely affects their team’s productivity, with 22% describing the impact of that technical debt as ...
The Future of Observability: Predictive Root Cause Analysis Using AI
Karthikeyan Uthirapathy | | AI in DevOps, AI observability, AI-driven RCA, AI-powered monitoring, anomaly correlation, anomaly detection, artificial intelligence, automated incident response, cloud environments, devops, distributed systems, intelligent observability, kubernetes, logs metrics traces, machine learning, microservices, observability tools, Predictive Analytics, predictive monitoring, predictive root cause analysis, proactive observability, rca, self-healing systems, system reliabilityIn 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 ...
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 ...
How Software Engineers and Students Use AI to Move Faster than Ever (Without Breaking Things)
Vivek Vaidya | | agentic AI, AI adoption, AI and students, AI coding tools, AI collaboration, AI engineers, AI evolution, AI in education, AI in software development, AI in universities, AI innovation, AI revolution, AI skills, AI skills gap, AI startups, AI Tools for Developers, AI transformation, AI workforce adaptation, AI-native companies, AI-native design, AI-native learning, AI-powered development, AI/ML, artificial intelligence, augmented development, augmented intelligence, Cursor, developer productivity, digital transformation, Enterprise AI, future of work, human-AI collaboration, LLMs, machine learning, super{set}, VC investment in AIWe’re living through the AI revolution — or more accurately, the age of augmented intelligence. From agentic AI tools transforming software development to AI-native education shaping the next generation, super{set} explores how ...
Why Software Migrations Fail: It’s Not the Code
The future of software migration lies not just in AI and automation, but in embracing the human elements that make these transitions sustainable ...
AI in Government: Why Flexibility Matters More Than Ever
Dr. Darren Pulsipher | | ai, AI Developers, artificial intelligence, Federal Technology, Government TechnologyThe early blooms of AI experimentation showed the new, promising ways of streamlining government operations. Now comes the real work of cultivating environments where AI can take root and thrive. ...
Five Powerful Ways AI Is Transforming the DevOps Playbook
The DevOps playbook is rapidly transforming because of recent advancements in artificial intelligence (AI) ...
