Full-Stack Application Deployment Cheat Sheet

Updated 2026-04-24

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Full-stack application deployment is the process of making software applications available to end-users by moving code from development environments to production infrastructure. It encompasses everything from build automation and container orchestration to monitoring, security, and rollback strategies. In modern cloud-native architectures, deployment is no longer a one-time event but a continuous, automated process that must balance speed, reliability, and cost-efficiency. A critical mindset shift: every deployment decision affects availability, performance, and operational overhead — making deployment strategy as important as the code itself.

What This Cheat Sheet Covers

This topic spans 25 focused tables and 201 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Deployment StrategiesTable 2: Container Orchestration PlatformsTable 3: Service Mesh SolutionsTable 4: CI/CD Pipeline ToolsTable 5: Infrastructure as Code (IaC) ToolsTable 6: GitOps ToolsTable 7: Serverless Deployment PlatformsTable 8: Cloud Deployment Platforms (PaaS)Table 9: Container Registry ServicesTable 10: Load Balancing SolutionsTable 11: Database Migration ToolsTable 12: Secrets Management ToolsTable 13: Monitoring and Observability ToolsTable 14: Health Check and Probe TypesTable 15: Scaling ApproachesTable 16: Rollback StrategiesTable 17: CDN and Edge DeploymentTable 18: SSL/TLS Certificate ManagementTable 19: Deployment Security PracticesTable 20: Deployment Metrics and SLOsTable 21: Deployment Documentation TypesTable 22: Cost Optimization StrategiesTable 23: Disaster Recovery ApproachesTable 24: API Gateway SolutionsTable 25: Artifact Versioning Strategies

Table 1: Deployment Strategies

Strategy	Example	Description
Blue-Green Deployment	Two identical environments (blue and green); switch traffic instantly between them	• Maintains two complete production environments, enabling instant rollback by switching load balancer routing • zero downtime but doubles infrastructure costs.
Canary Deployment	Route 10% of traffic to new version, monitor metrics, then gradually increase	• Releases updates to a small subset of users first, catching issues early with limited blast radius • allows data-driven rollout decisions based on real user feedback.
Rolling Deployment	Update pods/instances one at a time: `kubectl set image deployment/app app=v2` Gradually replaces old with new	• Incrementally updates instances without downtime • minimal resource overhead but slower rollout and potential version inconsistency during transition.
Feature Flag Deployment	Deploy code with features disabled, enable via runtime flags	• Decouples deployment from release, allowing instant feature activation or deactivation without redeployment • enables targeted rollouts and A/B testing.

Table 1: Deployment Strategies

Strategy	Example	Description
Blue-Green Deployment	Two identical environments (blue and green); switch traffic instantly between them	• Maintains two complete production environments, enabling instant rollback by switching load balancer routing • zero downtime but doubles infrastructure costs.
Canary Deployment	Route 10% of traffic to new version, monitor metrics, then gradually increase	• Releases updates to a small subset of users first, catching issues early with limited blast radius • allows data-driven rollout decisions based on real user feedback.
Rolling Deployment	Update pods/instances one at a time: `kubectl set image deployment/app app=v2` Gradually replaces old with new	• Incrementally updates instances without downtime • minimal resource overhead but slower rollout and potential version inconsistency during transition.
Feature Flag Deployment	Deploy code with features disabled, enable via runtime flags	• Decouples deployment from release, allowing instant feature activation or deactivation without redeployment • enables targeted rollouts and A/B testing.