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Most read news & articles within last 7 days
From the Horse’s Mouth: Anthropic Says AI Has Changed the SDLC
Alan Shimel | | agentic development, AI code review, AI coding agents, AI Governance, AI-assisted development, AI-native SDLC, Anthropic, autonomous agents, CI/CD, Claude Code, Code Generation, developer productivity, devops, internal developer platforms, platform engineering, software delivery, software development lifecycle, software engineering, software security, software testingAnthropic’s AI-native SDLC playbook argues that faster coding is shifting the bottleneck to planning, testing, governance, deployment and operations ...
Observability 2.0: Why DevOps Teams Are Moving From Monitoring to Intelligent System Understanding
For a long time, monitoring just meant staring at dashboards and waiting for something to flash red. Engineers tracked things like CPU usage, memory, response times, error rates, and uptime. If a ...
Observability’s Gaslighting Problem: “Send Less Data” Isn’t a Strategy
Noam Levy | | agentic development, AI agents, AI-assisted development, cardinality, data retention, developer observability, devops, incident response, logs, metrics, observability, observability costs, observability strategy, Runtime Visibility, software reliability, SRE, telemetry, Telemetry Optimization, telemetry sampling, tracesA familiar pattern is emerging in observability conversations. As telemetry volumes grow and costs rise, the default recommendation is often to collect less data: Sample more, retain less, index selectively, filter earlier, ...
Your DevOps Pipeline Is Already a Sustainability Program
Srinath Gopinath | | CI/CD, Cloud Computing, Cloud Sustainability, devops, GreenOps, Sustainable EngineeringDuring my doctoral research on modern engineering practices and operational efficiency, one pattern kept surfacing that I did not expect to find. The engineering teams making the most measurable progress on sustainability ...
GitHub’s New Copilot Feature Takes the Guesswork Out of Picking AI Models
Tom Smith | | agentic AI, AI agents, AI coding assistants, AI cost optimization, AI Governance, AI model routing, Code Generation, developer tools, devops, github, GitHub Copilot, model selection, multi-model orchestration, platform engineering, Project HydraFusion, software developmentGitHub’s Project HydraFusion brings multi-model orchestration to Copilot, automatically routing coding tasks across AI models to balance quality, cost and complexity ...
Apica Adds AI Agents and MCP Server to Platform for Managing Telemetry Data
Apica today added an artificial intelligence (AI) agent and Model Context Protocol (MCP) server to version 3.0 of its Ascent platform for managing telemetry data pipelines. Andi Mann, chief product and technology ...
EU-Funded CodeSupply Offers Grants for Open Source Software Supply Chain R&D
Jaime Hampton | | CodeSupply, devsecops, grants and funding, NLnet Foundation, open source, software security, Software Supply ChainSoftware supply chain, security and compliance tools all depend on accurate information about the packages they analyze, but that data is often fragmented across multiple sources and can be difficult to access ...
GitHub Quietly Fixes One of Dependabot’s Oldest Headaches
GitHub Dependabot can now authenticate to GitHub-hosted package registries without personal access tokens, reducing credential management and supply chain security risk ...
Ten Great DevOps Job Opportunities
DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience. Our goal in these ...
AI Has Turned Verification Into the New DevOps Bottleneck
Alan Shimel | | AI agents, AI code generation, AI code review, AI coding, AI evaluation, AI in DevOps, CI/CD, continuous delivery, developer experience, developer productivity, devops, devops automation, platform engineering, pull requests, Release engineering, software delivery, software pipelines, The Great UnificationThe next DevOps challenge is not generating more software. It is proving, quickly and repeatedly, that a growing volume of machine-generated change is fit to ship ...
