Tag: AI infrastructure
What the Microservices Era Can Teach Us About AI
Mark Fussell | | agent identity, agent observability, agent runtime, agentic AI, agentic durable execution, AI agents, AI architecture, AI Governance, AI infrastructure, AI security, autonomous agents, cloud-native AI, distributed systems, durable execution, LLM observability, microservices, Open Standards, platform engineering, vendor lock-in, workflow orchestrationAI agents are not just microservices with LLMs attached. Their long-running, non-deterministic workflows demand durable execution, per-step identity, governance and observability ...
Microsoft’s GitHub Hit by Major Outage as AI-Driven Demand Strains Infrastructure
Jon Swartz | | AI infrastructure, AI workflows, API, copilot, Downdetector, github, GitHub Actions, GitHub outages, GitHub Pages, Government, microsoft, Microsoft Teams, Rubrik, zero-trustGitHub, the Microsoft Corp.-owned code hosting platform serving more than 180 million developers, is still reeling from a widespread outage on Monday that severely disrupted software development pipelines globally. The hours-long incident ...
LiteLLM Attack Affected 2,500 Companies, 434,000 CI/CD Pipelines: CloudSEK
Jeff Burt | | AI infrastructure, AI supply chain attacks, AI-driven CI/CD pipelines, Aqua Security Trivy, CloudSEK, code repositories, FBI, information stealing, LiteLLM, malware, Mini Shai-Hulud, PyPi, TeamPCPThe massive supply-chain attack that compromised LiteLLM in the spring affected more than 2,500 companies and exposed about 434,000 CI/CD pipelines, with victims ranging from top-tier IT and AI companies to cybersecurity ...
So Agentic Systems Are Messing Up Your SLO Framework
Saqib Jan | | agent monitoring, agentic AI reliability, Agentic Systems, AI agent SLOs, AI infrastructure, AI observability, behavioral correctness, behavioral drift, error budgets, inference reliability, nondeterministic AI, platform engineering, Probabilistic Systems, probabilistic tracing, semantic similarityTraditional SLOs cannot show whether AI agents are behaving correctly. Platform teams need layered metrics for infrastructure, inference and behavioral reliability ...
The Death of the Four Golden Signals: Designing Telemetry for Non-Deterministic Infrastructure
Jyostna Seelam | | AI architecture, AI compliance, AI Governance, AI guardrails, AI infrastructure, AI monitoring, AI observability, AI operations, AI operations strategy., AI performance metrics, AI platform monitoring, AI reliability, AI resilience, AI safety, AI SLIs, AI SLOs, AI system reliability, AI telemetry, AI trust, Enterprise AI, generative AI monitoring, guardrail intervention rate, hallucination detection, LLM monitoring, LLM observability, modern SRE, non-deterministic systems, Observability Engineering, OpenTelemetry, platform engineering, production AI, RAG observability, RAG systems, semantic drift, site reliability engineering, SRE, time to first token, token throughput, TTFT, vector database monitoringIn complex software systems, our traditional definition of operational health has always been comfortably binary. For over a decade, site reliability engineering (SRE) teams have relied on the industry-standard ‘Four Golden Signals’ ...
Why Enterprise AI Infrastructure Is Becoming a DevOps Problem
Most enterprise AI projects start with retrieval. You connect Jira, Confluence, SharePoint, and Slack. Maybe a few internal databases nobody has touched in five years. You tune embeddings, optimize chunking, wire up ...
IREN to Acquire Mirantis to Reduce IT Infrastructure Management Friction
IREN Ltd, a provider of cloud infrastructure services, today revealed its intent to acquire Mirantis, a provider of open source OpenStack and Kubernetes software that is deployed in both cloud computing and ...
Your AI Agents Have a Blind Spot: What DevOps Teams Need to Know About Cross-LLM Security
Arun Sanna | | 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 managementExplore the challenges of AI agents in DevOps pipelines, highlighting the importance of model-aware detection to improve security and reduce vulnerabilities ...
Why Your AI Agent Strategy is Failing (and How to Fix It): The Microservices Playbook for AI Agents
Lokhesh Ujhoodha | | 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 agentsDespite 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
Anshul Sharma | | agentic DevOps, AI (Artificial Intelligence), AI Governance, AI infrastructure, devsecops, kubernetesOver 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 ...
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 ...
The Agentic AI-Driven Future of Telemetry
Perry Correll | | 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 normalizationTelemetry is evolving from passive data to AI-grade fuel. Learn how agentic telemetry fuses human and machine context to power self-healing, intelligent systems ...
