Operations

12 articles
Token Budget The maximum number of tokens allocated for an LLM request or workflow, used to control costs, latency, and …Toil What toil is in the SRE context, how to identify it, and strategies for reducing operational burden through …Site Reliability Engineering (SRE) What SRE is, how it applies software engineering to operations, and key SRE practices for AI platform …Self-Healing Architecture - AI-Powered Automated Recovery Using AI to detect, diagnose, and automatically remediate infrastructure and application failures without …LLMOps - LLM Operations The practices, tools, and infrastructure for deploying, monitoring, and managing large language model …Kanban for AI Operations - Flow-Based Management Implementing Kanban for AI operations teams managing model deployments, monitoring, retraining, and incident …Error Budget What an error budget is, how it balances reliability with feature velocity, and how to implement error budget …Cloud Monitoring - Infrastructure and Application Observability Google Cloud Monitoring provides metrics collection, dashboards, alerting, and uptime checks for GCP …Case Pattern: AI Warehouse Optimization for a Distribution Company Architecture and lessons from deploying AI to optimize warehouse layout, picking routes, and labor allocation …AI Spark: AI-Powered Operational Anomaly Alerts Use AI to detect unusual patterns in operational metrics and generate contextual alerts that explain what …AI Spark: AI Workflow Bottleneck Detection Use AI to analyze process data and identify workflow bottlenecks, suggesting optimization opportunities …Operational Excellence (Well-Architected Pillar) The Well-Architected pillar covering runbooks, automation, observability, incident response, and continuous …