Tag: reliability engineering
The Four Knobs of AI Agent Reliability: A DevOps Perspective
AI agents aren’t chatbots—they’re systems that act. This guide cuts through the hype to show how DevOps teams can configure, trust, and run AI agents reliably in production ...
Lessons from 2025: The Year “Agent Mitigation” Became a Thing
Abigail Wall | | Agent Mitigation, AI agents, AI Best Practices, AI security, cloud infrastructure, Continuous Evaluation, Data Exfiltration, Environment Orchestration, Incident Analysis, incident management, incident response, Mitigation Strategies., Public APIs, reliability engineering, risk management, Security ControlsExplore the emergence of agent mitigation as a formal discipline in response to 2025's AI failures, highlighting best practices for secure and reliable AI agent deployment ...
From Reactive to Predictive: Capacity Planning Systems That Actually Work
Muhammad Yawar Malik | | capacity planning, cloud infrastructure, Predictive Analytics, reliability engineering, scalingI used to think capacity planning was about setting up CloudWatch alarms and hoping they'd fire before things broke. Spoiler: that's not capacity planning—that's just reactive firefighting with extra steps. Real capacity ...
Why Up to 70% of SRE Initiatives Stall Before They Scale — and How to Break the Plateau
Akash Thakur | | automation, cloud-native reliability, Cultural Change, DevOps transformation, error budgets, incident management, KPIs, leadership alignment, legacy bottlenecks, modernization barriers, observability, Operational Excellence, reliability engineering, site reliability engineering, SLOs, SRE, SRE adoption challenges, SRE maturity model, SRE plateau, SRE training, toil reductionMany SRE initiatives stall because organizations adopt the title without the principles. True SRE success requires leadership vision, cultural change, shared KPIs and continuous maturity measurement—not tools alone ...
SRE in the Age of AI: What Reliability Looks Like When Systems Learn
Muhammad Yawar Malik | | adaptive systems, AI observability, AI reliability, concept drift, data pipeline reliability, feedback loops, incident response, learning systems, ML operations, MLOps, model drift, model performance monitoring, reliability engineering, site reliability engineering in AI, SREAs AI and ML become core production components, SRE is evolving from managing deterministic systems to ensuring the reliability of dynamic, learning systems. New metrics, workflows, guardrails and cross-disciplinary practices are redefining ...
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 ...
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 ...
AIOps for SRE — Using AI to Reduce On-Call Fatigue and Improve Reliability
Ankur Mahida | | AI for IT operations, AI-driven operations, AIOps, alert fatigue, anomaly detection, automated remediation, cloud operations, devops, event correlation, incident management, IT observability, machine learning in IT, noise reduction, predictive maintenance, reliability engineering, root cause analysis, self-healing systems, site reliability engineering, SRE, SRE automationSite reliability engineering (SRE) has become an emergent niche practice invented at Google to become a foundation of contemporary enterprise performance worldwide. With the continued growth of microservices, a multi-cloud infrastructure and continuous deployment pipelines adopted by ...
