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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 ...
How Hyperconnected AI Development Creates a Multi-System Secret Sprawl
Guillaume Valadon | | AI development security, AI secret leaks, API key sprawl, Claude Code security, Cursor IDE risks, database credential leaks, GitHub secret exposure, hyperconnected AI workflows, large language model security, leaked API keys, MCP configuration files, MCP security risks, mcp.json leaks, OWASP AI testing, secret scanning toolsIf 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 ...
GitOps in the Wild: Scaling Continuous Delivery in Hybrid Cloud Environments
Ankur Mahida | | continuous delivery, devops automation, drift detection, GitOps architecture, GitOps at scale, GitOps best practices, GitOps case study, GitOps challenges, GitOps governance, GitOps observability, GitOps security, hybrid cloud GitOps, hybrid cloud operations, infrastructure as code, Kubernetes delivery, multi-cloud DevOps, Open Policy Agent, policy as codeA deep dive into scaling GitOps for hybrid and multi-cloud environments, exploring architecture, governance, security, observability and real-world enterprise practices ...
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, ...
ClickOps, IaC and the Excluded Avocado Middle
Let’s start with a confession: I think Infrastructure-as-Code solves a lot of problems. Terraform, OpenTofu, Pulumi, all of it. IaC changed how we work. It gave us version control, audit trails, repeatability, ...
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 ...
Why Traditional SLOs Are Failing at Hyperscale: Building Context-Aware Reliability Contracts
Muhammad Yawar Malik | | adaptive reliability, AI-driven scaling, business-aligned reliability, context classification, context propagation, context-aware reliability, context-driven SLOs, cost reduction, devops, dynamic SLOs, gitops, hyperscale reliability, infrastructure optimization, multi-service reliability, observability, performance optimization, post-mortem analysis, predictive scaling, reliability budgets, reliability contracts, reliability engineering, reliability marketplace, site reliability engineering, SLA management, SLO optimization, SREDiscover how context-aware reliability contracts (CARC) redefine SLOs for hyperscale systems—optimizing uptime, reducing infrastructure spend by 33%, and aligning reliability with business value across user tiers, regions, and workloads ...
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 ...
Survey Surfaces Multiple DevOps Platform Migration Challenges
A survey of 300 enterprise IT and technology leaders published this week finds that while 85% work for organizations that have completed DevOps platform migrations in the last two years, only a ...
Bindplane Adds Ability to Automate Deployment of OpenTelemetry Collectors
Mike Vizard | | AI in observability, AI-powered monitoring, application instrumentation, devops automation, IT monitoring, large-scale telemetry, LLM observability, observability convergence, observability platform, OpenTelemetry management, telemetry at scale, telemetry automation, telemetry management, telemetry orchestrationBindplane introduces an ability to streamline large-scale OpenTelemetry collector deployments, enabling teams to reuse telemetry pipelines, and improve observability ...
Why Your SLO Dashboard is Lying: Moving Beyond Vanity Metrics in Production
Muhammad Yawar Malik | | API latency, business context, business metrics, business resilience, business-aligned SLOs, context-aware monitoring, customer impact, data-driven DevOps, devops, engineering reliability, enterprise customers, enterprise reliability, error budget management, error budgets, incident management, incident prioritization, observability, performance monitoring, reliability engineering, reliability framework, reliability strategy, revenue-weighted SLOs, service availability, Service Level Objectives, site reliability engineering, SLA optimization, SLIs, SLOs, SRE, uptime, uptime metrics, user segmentationDiscover how redefining service level objectives (SLOs) around business impact — not vanity uptime metrics — reduced incidents by 75% and saved $2.3M in lost revenue ...
