paas

## What I do - Deploy applications to PaaS platforms - Configure managed services and databases - Implement auto-scaling and high availability - Set up CI/CD for PaaS deployments - Manage application performance - Optimize PaaS costs ## When to use me - When focusing on code, not infrastructure - When building web applications quickly - When needing managed databases - When implementing auto-scaling - When reducing operational overhead - When building cloud-native applications ## Key Concepts ### Heroku Deployment ```yaml # app.json - Heroku Review Apps { "name": "myapp", "buildpacks": [ { "url": "heroku/python" } ], "environments": { "review": { "addons": ["heroku-postgresql:hobby-dev"], "environment": { "LOG_LEVEL": "DEBUG" }, "formation": { "web": { "quantity": 1, "size": "hobby" } } }, "production": { "addons": ["heroku-postgresql:standard-0"], "formation": { "web": { "quantity": 2, "size": "performance-m" } } } } } ``` ### AWS Elastic Beanstalk ```yaml # .ebextensions/python.config option_settings: aws:elasticbeanstalk:container:python: WSGIPath: application:application aws:elasticbeanstalk:environment:proxy:staticfiles: /static: static aws:autoscaling:asg: MinSize: 2 MaxSize: 10 aws:autoscaling:trigger: MeasureName: CPUUtilization UpperThreshold: 80 LowerThreshold: 20 ``` ### Azure App Service ```yaml # azure-pipelines.yml trigger: main pool: vmImage: 'ubuntu-latest' variables: azureSubscription: 'Azure-Service-Connection' appName: 'myapp' runtime: 'python' version: '3.11' stages: - stage: Build jobs: - job: BuildJob steps: - task: UsePythonVersion@0 - script: | pip install -r requirements.txt pip install pytest pytest tests/ - task: ArchiveFiles@2 inputs: rootFolder: '$(System.DefaultWorkingDirectory)' archiveFile: '$(Build.ArtifactStagingDirectory)/$(Build.BuildId).zip' - publish: $(Build.ArtifactStagingDirectory)/$(Build.BuildId).zip artifact: drop - stage: Deploy jobs: - deployment: DeployJob environment: 'production' strategy: runOnce: deploy: steps: - task: AzureWebApp@1 inputs: azureSubscription: $(azureSubscription) appType: 'webApp' appName: $(appName) package: '$(Pipeline.Workspace)/drop/**/*.zip' ``` ### GCP App Engine ```yaml # app.yaml runtime: python311 env: standard instance_class: F2 automatic_scaling: min_instances: 1 max_instances: 10 target_cpu_utilization: 0.65 min_latency: '500ms' inbound_services: - warmup liveness_check: path: /_ah/health check_interval_seconds: 30 timeout_seconds: 4 failure_threshold: 2 success_threshold: 2 readiness_check: path: /_ah/ready check_interval_seconds: 5 timeout_seconds: 4 failure_threshold: 2 success_threshold: 1 env_variables: LOG_LEVEL: 'INFO' DATABASE_URL: 'postgres://...' beta_settings: cloud_sql_instances: 'project:region:instance' ``` ### Cloud Run Deployment ```yaml # cloudrun.yaml apiVersion: serving.knative.dev/v1 kind: Service metadata: name: myapp annotations: run.googleapis.com/launch-stage: BETA spec: template: metadata: annotations: autoscaling.knative.dev/minScale: "1" autoscaling.knative.dev/maxScale: "10" spec: containers: - image: gcr.io/project/myapp:latest ports: - containerPort: 8080 resources: limits: cpu: "1000m" memory: "512Mi" env: - name: PORT value: "8080" startupProbe: httpGet: path: /_ah/health initialDelaySeconds: 0 periodSeconds: 10 timeoutSeconds: 1 failureThreshold: 3 ``` ### PaaS Comparison | Platform | Languages | Database | Scaling | Best For | |----------|-----------|----------|---------|----------| | Heroku | All | Add-ons | Auto | Quick deployment | | AWS EB | All | RDS, ElastiCache | Auto | AWS integration | | Azure App Service | .NET, Node, Python | SQL, Cosmos | Auto | Enterprise .NET | | Cloud Run | All | Cloud SQL | Auto | Containers | | Vercel | Node, Go, Python | External | Auto | Frontend/JAMstack | ### Key Benefits - **Managed Runtime**: Don't manage OS or middleware - **Auto-scaling**: Handle traffic spikes automatically - **Managed Services**: Databases, caches, queues - **CI/CD**: Built-in deployment pipelines - **Monitoring**: Integrated logging and metrics - **Security**: Patched and secured platforms