Deployment & Operations

The moment AI-written code meets production is the moment the gates appear: a security scan blocks the deploy, an auditor wants evidence, the token bill spikes. These guides cover the operational layer that turns agent output into something you can safely ship and defend — security best practices, compliance automation, and cost optimization, plus the full tool-agnostic DevOps series below.

Guides

Security Operations Security best practices for AI-assisted development workflows

Compliance Automation Automate compliance checks and audits in your AI development pipeline

Cost Optimization Optimize costs across AI coding tools and cloud infrastructure

DevOps & Production Workflows

The deployment story continues in Shared Workflows with nine guides that cover the rest of the pipeline — CI/CD, containers, infrastructure, observability, and incidents:

Pipeline Automation with AI Change-aware builds, flaky-test triage, and safe progressive deploys

Docker and Kubernetes Containerization Hardened multi-stage Dockerfiles, OOMKilled debugging, and container MCP servers

Infrastructure as Code with AI Assistants Drive Terraform, CloudFormation, Pulumi, and CDK from natural language

Monitoring and Observability OpenTelemetry instrumentation, Grafana dashboards, alert rules, and the Sentry MCP

AI-Powered Incident Response Correlate alerts, run safe remediation, and generate post-mortems

Production Performance Optimization Diagnose production bottlenecks and tune them with AI workflows

Security Operations Automation Scanner CLIs in CI, vulnerability triage, and compliance evidence

Regulatory Compliance Automation Audit trails, policy enforcement, and SOC 2/HIPAA/GDPR compliance

Cloud Cost Management & FinOps Right-sizing, anomaly detection, cost allocation, and budget forecasting