DevOps-Security-Agent-Skills

Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster. Build reliable, observable, and retriable workflows for production AI systems.

Implement multi-layer LLM caching with exact match, semantic similarity, and provider-side prompt caching. Reduce API costs by 30–70%, cut latency, and improve throughput using Redis, GPTCache, and provider caching APIs.

Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.

Design and operationalize SRE dashboards that surface reliability, latency, error, saturation, and capacity signals across services. Use when building observability views for SLOs, incident response, and executive reliability reporting.

Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.

Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and performance tuning for production RAG and semantic search workloads.

Harden OpenClaw self-hosted environments with baseline host controls, auth tightening, secret handling, network segmentation, and safe update/rollback workflows. Use when deploying OpenClaw in home labs, startups, or production-like local AI infrastructure.

Implement centralized audit logging and SIEM integration. Configure log retention and security monitoring. Use when implementing audit trail requirements.

Configure AWS CloudTrail for audit logging. Set up organization trails and event analysis. Use when auditing AWS activity.

Configure Azure Monitor and Activity Log for auditing. Set up diagnostic settings and log analytics. Use when auditing Azure activity.

Configure GCP Cloud Audit Logs for compliance. Set up log routing and BigQuery analysis. Use when auditing GCP activity.

Develop business continuity plans and impact analysis. Implement BCP testing and communication procedures. Use when building organizational resilience.

Implement disaster recovery strategies and runbooks. Configure RPO/RTO targets and failover procedures. Use when planning for business continuity.

Implement incident management processes and escalation procedures. Configure on-call schedules and post-incident reviews. Use when managing production incidents.

Create operational runbooks and standard operating procedures. Document troubleshooting guides and recovery procedures. Use when documenting operational knowledge.

Implement FedRAMP requirements for federal cloud services. Configure NIST 800-53 controls and continuous monitoring. Use when providing cloud services to US federal agencies.

Implement GDPR data protection requirements. Configure consent management, data subject rights, and privacy by design. Use when processing EU personal data.

Implement HIPAA security and privacy rules. Configure PHI protections and BAA requirements. Use when handling healthcare data.

Implement ISO 27001 Information Security Management System. Configure ISMS controls and risk management. Use when implementing enterprise security frameworks.

Implement PCI DSS requirements for payment card data. Configure cardholder data environment and security controls. Use when processing payment cards.

Implement SOC 2 Trust Services Criteria. Configure security, availability, and processing integrity controls. Use when achieving SOC 2 certification.

Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.

Maintain IT asset inventory and configuration management database. Track hardware, software, and cloud resources. Use when managing IT assets.

Implement change management processes. Configure CAB reviews, change windows, and rollback procedures. Use when managing production changes.

Implement policy as code with OPA, Sentinel, and Kyverno. Automate policy enforcement in CI/CD and infrastructure. Use when enforcing compliance through automation.

Implement vendor risk management programs. Assess third-party security and maintain vendor inventory. Use when managing supplier security.

Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.

Build AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety regressions.

Build production LLMOps platforms with CI/CD, model promotion workflows, evaluation gates, rollback, and governance across cloud and self-hosted inference.

Establish model registry standards, governance controls, metadata schemas, approvals, and lifecycle policies for enterprise AI deployments.

Monitor and evaluate RAG systems with retrieval quality metrics, groundedness checks, hallucination detection, and continuous regression testing.

Create reproducible development environments with Dev Containers, Nix flakes, and Devbox for consistent toolchains across teams. Use when onboarding developers, standardizing build environments, or eliminating "works on my machine" problems.

Use eBPF for deep kernel-level observability — trace syscalls, network flows, and application behavior without code changes using Cilium, Tetragon, and bpftrace.

Instrument applications and infrastructure with OpenTelemetry for unified traces, metrics, and logs. Use when implementing distributed tracing, service-level troubleshooting, or vendor-neutral observability.

Build internal developer platforms (IDPs) with self-service infrastructure, golden paths, and developer portals using Backstage, Crossplane, and score.

Reduce AWS spend with rightsizing, autoscaling, commitment planning, and storage lifecycle policies. Use when running FinOps reviews, lowering cloud bills, or improving cost-per-request metrics.

Manage EC2 instances, AMIs, and auto-scaling groups. Configure security groups, key pairs, and instance types. Use when deploying compute resources on AWS.

Deploy containers on ECS and Fargate. Configure task definitions, services, and load balancing. Use when running containerized workloads on AWS.

Manage IAM users, roles, and policies. Implement least-privilege access and security best practices. Use when configuring AWS identity and access management.