Tag: AI in DevOps
Survey Sees AI Coding Creating Need for More Software Engineers
Mike Vizard | | agentic AI, AI compliance challenges, AI in DevOps, AI in software development, AI tools adoption, AI-generated code vulnerabilities, developer upskilling, DevOps productivity, DevSecOps challenges, GitLab DevSecOps survey, platform engineering, SDLC automation, software engineer demand, technical debt from AI, vibecoding risksA 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 ...
AI-Driven Performance Testing: A New Era for Software Quality
Akash Thakur | | AI agents, AI defect detection, AI in DevOps, AI load testing, AI observability, AI performance testing, AI testing tools, continuous assurance, intelligent performance systems, LLMs in testing, ML-driven QA, next-gen performance testing, performance automation, performance engineering, performance engineers, performance lifecycle, performance monitoring, performance optimization, predictive performance analysis, predictive testing, requirements as code, self-healing systems, software reliability, SRE automation, testing transformationDiscover 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
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 ...
JFrog Adds Ability to Track Usage of AI Coding Tools
Mike Vizard | | AI API management, AI code auditing, AI coding tools, AI compliance tracking, AI Governance, AI in DevOps, AI model inventory, AI risk mitigation, AI-generated code, application security, code risk detection, devsecops, Large Language Models, LLM security, MLOps, SCA, secure coding practices, Shadow AI detection, software composition analysis, software provenance, Software Supply Chain Security, software vulnerabilities, source code scanningJFrog introduces AI-Generated Code Detection and Shadow AI Detection tools to identify AI-created code, track model usage, and enhance DevSecOps governance across software supply chains ...
Observe Adds Two AI Agents to Improve Observability
Mike Vizard | | AI debugging, AI in DevOps, AI observability, AI SRE Agent, AIOps, code instrumentation, developer productivity, devops automation, incident triage, MCP Server, Model Context Protocol, observability platform, OpenAI Codex, OpenTelemetry, SRE automation, Telemetry dataObserve 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, ...
The AI-Powered Evolution of Software Development
Vishwanath Krishnamurthy | | agentic AI, AI for developers, AI in DevOps, AI in software development, AI productivity tools, AI testing tools, AI-driven coding, AI-native applications, AI-powered development, AI. analytics, autonomous software operations, code optimization, devex, Future of Software Engineering, GitHub Copilot, intelligent automation, machine learning, OpenAI Codex, predictive maintenance, software qualityArtificial 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 ...
Context Engineering: The Next Frontier in AI-Driven DevOps
Arun Sanna | | agentic AI, AI in DevOps, AIOps, autonomous operations, context engineering, context-aware AI, devops, devops automation, Prompt Engineering, SREImagine 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 ...
From Cloud to Cognitive Infrastructure: How AI is Redefining the Next Frontier of SRE
Akash Thakur | | AI in DevOps, AI infrastructure, AI reliability, AI workloads, AI-driven SRE, cloud observability, cloud-native infrastructure, devops, GPU clusters, GPU utilization, hybrid AI systems, hybrid cloud, hybrid computing, intelligent operations, multi-cloud operations, site reliability engineering, SRE evolutionAs organizations embrace artificial intelligence (AI) workloads alongside traditional cloud systems, site reliability engineering (SRE) must evolve to manage an entirely new class of infrastructure — intelligent, hybrid and graphics processing unit ...
Harness Adds Vibecoding Tool to Migrate Databases Within DevOps Workflows
Mike Vizard | | AI in DevOps, AI-powered database migration, backward compatibility, CI/CD, compliance automation, database as code, database devops, database modernization, devops automation, Harness, Harness AI platform, Model Context Protocol Server, natural language interface, Oracle to Postgres migration, platform engineering, schema migration, Software Delivery Knowledge Graph, SQL automation, Stephen Atwell, vibecodingHarness adds an AI-powered vibecoding tool to automate database migrations via natural language, integrating seamlessly with its CI/CD DevOps platform ...
Before You Go Agentic: Top Guardrails to Safely Deploy AI Agents in Observability
Pankaj Thakkar | | agentic AI, AI audit trails, AI cost management, AI deployment controls, AI Governance, AI guardrails, AI in DevOps, AI observability safety, AI operations, AI policy validation, AI rate limiting, autonomous agents, data privacy, human-in-the-loop, KubeCon 2025, observability, OpenTelemetry, role-based access control, self-healing infrastructure, zero-trustObservability platforms are evolving from passive monitors to active participants. Agentic AI promises a self-healing infrastructure that detects anomalies and fixes issues before users notice, reducing resolution time from hours to minutes ...
The Breakneck Future of Codegen: Why AI SWE Must Be Matched with AI SRE
Anish Agarwal | | AI automation, AI code generation, AI in DevOps, AI infrastructure, AI observability, AI operations, AI reliability, AI SRE, AI-Driven Development, cloud-native systems, code duplication, distributed inference, GitHub Copilot, incident management, parallel reasoning, resilience engineering, site reliability engineering, software reliability, software vulnerabilities, technical debtAI codegen is transforming software development — but as speed and complexity increase, so does fragility. AI for site reliability will need to keep pace to avoid system breakdown and engineer burnout. ...
Grafana Labs Extends AI Capabilities of Observability Platform
Mike Vizard | | Adaptive Profiles, Adaptive Traces, AI for IT operations, AI in DevOps, AI incident management, AI observability, AI-driven observability, AIOps, Bring Your Own Cloud, BYOC, democratizing observability, DoD IL5, Grafana Cloud Knowledge Graph, Grafana ObservabilityCON 2025, incident remediation AI, IT root cause analysis, OpenTelemetry, RCA Workbench, root cause analysis, telemetry data analysisGrafana Labs this week made generally available an artificial intelligence (AI) agent, dubbed Grafana Assistant, for its namesake dashboard in addition to previewing Grafana Assistant Investigations, an AI incident management tool that ...
