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Tag: AI infrastructure

Your AI Agents Have a Blind Spot: What DevOps Teams Need to Know About Cross-LLM Security 

Your AI Agents Have a Blind Spot: What DevOps Teams Need to Know About Cross-LLM Security 

| | AI agents, AI infrastructure, Behavioral Monitoring, Cross-LLM Detection, Cybersecurity, devops, DevOps pipelines, incident management, Model-Aware Detection, Multi-LLM Environments, security best practices, Security Gaps, supply chain security, threat detection, vulnerability management
Explore the challenges of AI agents in DevOps pipelines, highlighting the importance of model-aware detection to improve security and reduce vulnerabilities ...
AI agents, SRE

Why Your AI Agent Strategy is Failing (and How to Fix It): The Microservices Playbook for AI Agents 

| | agentic AI, AI agent transparency, AI agent trust, AI agents, AI architecture, AI Governance, AI infrastructure, AI microservices, AI observability, AI ROI, autonomous agents, CIO AI strategy, Enterprise AI, enterprise AI strategy, LLM adoption, microservices architecture, monolithic AI agents
Despite billions in AI investment and countless vendor promises, most enterprises are still treating AI agents like glorified copilots rather than autonomous systems. After working with numerous enterprise customers implementing AI agents across various ...
The Future of DevOps Still Has a Pulse

The Future of DevOps Still Has a Pulse

| | agentic DevOps, AI (Artificial Intelligence), AI Governance, AI infrastructure, devsecops, kubernetes
Over the last few years, we have watched our industry get swept up in the promise of AI agents. The pitch is compelling: tell a system “Deploy this workflow and roll back ...
SRE, Elastic SRE chaos engineering LitmusChaos

From Cloud to Cognitive Infrastructure: How AI is Redefining the Next Frontier of SRE 

| | 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 evolution
As 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 ...
telemetry, devops, Grafana, APIs, Sumo, Veracode, telemetry data, New Relic, observability, Sawmills, AI, Mezmo, Cribl, telemetry data, Telemetry, Data, OpenTelemetry, observability, data, Good Cribl Splunk telemetry OpenTelemetry

The Agentic AI-Driven Future of Telemetry 

| | 10x investigators, agentic telemetry, AI infrastructure, AI observability, AI reasoning, AI scalability, AI-driven operations, AI-first architecture, autonomous agents, context fusion, contextual telemetry, human-in-the-loop, KubeCon + CNC NA 2025, MELT stack, metrics events logs traces, observability platforms, OCSF, OpenTelemetry, schema-agnostic architecture, telemetry normalization
Telemetry is evolving from passive data to AI-grade fuel. Learn how agentic telemetry fuses human and machine context to power self-healing, intelligent systems ...
AI coding, teams, vibecoding, shadow, vibecoding vibe, coding, GitHub, agents, Gemini, Canvas, Gemini, code, Augment Code, code, kernel compliance-as-code software secure software Terraform infrastructure

The Breakneck Future of Codegen: Why AI SWE Must Be Matched with AI SRE 

| | 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 debt
AI 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.  ...
IDPs, AIOps, AWS, MCP, developer, integration, software, investment, system, productivity, developer, development, software, system, Agile, and, IDP, practices, DevOps, open-source, CVE, Software, in-house development IDP developer, experience, software DevOps jobs secrets Libbpf BCC BPF kernel developer citizen secure software

Whose Ops is it Anyway? How IDPs, AI and Security are Evolving Developer Culture

| | AI and ML workloads, AI in DevOps, AI infrastructure, AI-driven operations, AIOps, automation in DevOps, continuous delivery, Cycloid plug-ins, developer experience, devops culture, devops evolution, DevOps scalability, DevOps security integration, DevOps transformation, devsecops, digital transformation DevOps, gitops, IDP, intelligent automation, internal developer platforms, MLOps, modern DevOps strategy, operational resilience, platform engineering, platform governance, secure CI/CD
It was only a few years ago that perhaps the biggest hurdle for DevOps advocates was convincing leadership that it was worth the investment. That conversation has since shifted. In most organisations ...