16 docs tagged with "scope:ops"

Guide for declaratively defining agent workflows like IaC and automating compliance

Agent operations KPIs including task success rate, tool-call accuracy, hallucination rate, cost per interaction, escalation rate, and Langfuse·OTel schema

Langfuse-based agent monitoring operations — monitoring architecture, key metrics, PromQL, alerting, and cost tracking (for tool comparison, see LLMOps Observability)

LLM Gateway-level Guardrails — PII redaction, prompt injection defense, content filtering, tool comparison, and Korean financial compliance mapping

AIDLC Checkpoint Approval gates and ISO 8601-based audit logs — Implementation guide for AIDLC audit trails in regulated industries

Guide to tuning Inference Gateway Cascade Routing classification thresholds, Canary rollout, Fallback, and cost drift alerts based on production traces

Guide to improving technical domain coding quality with LoRA Fine-tuning, VectorRAG, and GraphRAG — including FSI SI production scenarios

Compliance guide mapping SOC2, ISO27001, Electronic Financial Supervisory Regulation (전자금융감독규정), and ISMS-P to AI operations

Declarative AI agent management architecture and orchestration patterns in Kubernetes using Kagent

A framework guide covering the DRA core model (DeviceClass, ResourceClaim, ResourceSlice), resource types beyond GPUs (NICs, interconnects, FPGAs), and adoption criteria

Covers the 1-hour TTL constraint of EKS Kubernetes events, export pipeline design, and AI Agent query architecture based on the EKS and CloudWatch MCP servers.

LLMOps observability tool comparison — Langfuse·LangSmith·Helicone·CloudWatch selection criteria and hybrid architecture (for Langfuse operations, see Agent Monitoring)

Deploying Milvus vector database on Amazon EKS and integrating with RAG pipelines

Orchestrator-Worker, Voting, Debate, Hierarchical Supervisor patterns and LangGraph/CrewAI/AutoGen/Strands Agents SDK implementation

AI platform monitoring, observability, evaluation, compliance, and domain-specific operations guide

RAG pipeline quality evaluation and continuous improvement using Ragas