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Dynatrace Acquires Arize as AI Agents Deepen the Observability Challenge
Dynatrace announced Thursday it has agreed to acquire AI observability company Arize in a $915 million cash and stock transaction. Rick McConnell, CEO of Dynatrace, said the company expects demand for AI ...
GitHub Copilot’s Latest Update Bets on Model Choice, Not Model Loyalty
Tom Smith | | Agent Plugins 1.0, AI agents, AI coding tools, Claude model switching, Copilot CLI, Copilot Memory, Copilot updates, developer tools, devops, GitHub Copilot, GitHub Copilot models, Kimi K3, MAI-Code-1.1-Flash, Ollama, platform engineering, VS Code 1.133GitHub’s latest Copilot updates add Kimi K3, MAI-Code-1.1-Flash, Agent Plugins 1.0, model switching, CLI improvements, and local Ollama support ...
Treat Business Workflow Changes Like Deployments
Marcelo Cedeño | | business automation, change management, CI/CD, devops, release management, workflow automationBusiness automation often reaches production without the release discipline applied to application code. A routing rule changes, an approval threshold moves, or an integration starts writing to a new system. The edit ...
Microsoft Decouples AI Agents From the VS Code Editor in Latest Release
Microsoft has shipped Visual Studio Code 1.133, and the headline change is architectural rather than cosmetic: AI agent sessions now run in a dedicated background process rather than within the editor's extension ...
Developer Resistance to AI Isn’t Fear – It is Identity
Lukasz Lazewski | | 1000x developer, agentic coding, AI adoption, AI agents, AI code review, AI coding tools, AI Orchestration, AI transformation, AI-assisted coding, AI-generated code, coding with AI, developer accountability, developer experience, developer identity, developer motivation, developer productivity, developer resistance to AI, developer trust in AI, developer workflow, Engineering leadership, Future of Programming, human-AI collaboration, software architecture, software developers, software engineeringDeveloper resistance to AI is less about job loss than a deeper shift from hands-on coding to supervising, validating and orchestrating AI-generated work ...
Production-Safe Testing: The Missing Piece in Most DevSecOps Strategies
Dharmesh Acharya | | application security, continuous security, devsecops, Production-Safe Testing, security testingMost DevSecOps teams invest heavily in security before deployment, yet attackers target the production environment where applications, APIs, and user behavior are constantly changing. If security validation stops before release, critical risks ...
Arm Adds AI Tool to Optimize Workloads Using Runtime Data
Arm has made available a Dynamic Insights tool that leverages artificial intelligence (AI) models to generate recommendations for optimizing software running on its processors using actual data collected at runtime. Alex Spinelli, ...
ProjectDiscovery Brings Open Source AI Testing to Vulnerability Discovery
ProjectDiscovery has made available an autonomous security testing platform that leverages an open source artificial intelligence (AI) testing framework to detect and validate vulnerabilities at a lower total cost. Company CEO Rishi ...
Reflex’s Newly Open-Sourced XY Library Offers Faster Python Charting
A newly open-sourced Python charting library, called XY, from Reflex offers an advantage few other charting tools provide: massive scalability. The library rethinks how to render a set of points on the ...
Reducing MTTR: A Practical Guide to Correlating Incidents with AIOps
Neel Shah | | AI for SRE, AI observability, AI-driven incident correlation, Aiden AI Copilot, Aiden for SRE, AIOps, alert correlation, alert fatigue, alert storms, automated remediation, automated root cause analysis, devops, Distributed Tracing, grafana, incident correlation, incident management, incident response, Jaeger, Loki, mean time to resolution, metrics logs traces, mttr, observability, ObserveNow, on-call automation, pattern-based correlation, Prometheus, root cause analysis, service dependency mapping, SRE automation, telemetry correlation, topology-aware correlationAI-driven incident correlation helps SRE and DevOps teams reduce alert noise, identify root causes faster and improve MTTR by connecting related metrics, logs and traces ...
Developer’s Checklist: How to Build an FHE Application
David Archer | | BFV, BGV, bootstrapping, Chebyshev approximation, ciphertext packing, CKKS, confidential computing, encrypted cloud computing, encrypted computation, encrypted machine learning, federated learning, FHE, FHE application development, FHE development checklist, FHE parameters, FHE performance, FHE testing, fixed-point arithmetic, fully homomorphic encryption, homomorphic encryption, multiplicative depth, Niobium FHE, noise budget, OpenFHE, polynomial approximation, privacy-preserving AI, privacy-preserving computing, secure computation, SIMD encryptionA practical guide to building fully homomorphic encryption applications, covering architecture, noise budgets, polynomial approximations, parameter choices, SIMD packing, testing and performance optimization ...
The Agent Proposes, the Pipeline Disposes: Controls for AI-Authored Change
Veera Ravindra Divi | | agent permissions, agentic coding, AI change control, AI code review, AI coding agents, AI Governance, AI pull requests, AI software development, AI-authored code, AI-generated code security, autonomous coding agents, bounded-write agents, change-budget gates, CI/CD security, human-in-the-loop, in-toto, independent evals, least-privilege, policy as code, protected paths, provenance attestation, provenance verification, Secure DevOps, signed attestations, Sigstore, SLSA, Software Supply Chain Security, staged autonomyWhen agents write code and open pull requests faster than humans can read them, ‘the diff looked fine’ stops being a control. The durable controls live outside the agent’s reasoning loop ...
