Ch6
Delivering Microservices🔗
Automated Deployments🔗
In monoliths usually deployment is manual process, but microservices are deployed frequently and there are bunch of them, so manual process is not feasible.
Microservices requires Automated Deployments :
- Reliable and repeatable
- frequent deployments
- Continous Integration
- Release Pipelines : Build -> Unit Tests -> Deploy Microservices -> Service Tests -> Deploy to QA -> End-to-end test -> Release gate -> Deploy to Production
Deployment Environments🔗
Development : Debug Code
QA : End-to end test, manual testing, Pen testing, Performance testing
Production : per-customer, per-region
It is helpful to parameterize your deployments. Common way is json/yaml config files which explain whats different about environments.
Cloud Infrastructure Deployment, Terraform or Azure ARM Templates.
Base template + environment-specific override
Artifact Registries🔗
- Store Build artificats
- Deploy latest or previous version
- Docker Container Images
- Deploy to Kubernetes : (yaml config files, desired state)
Independent Upgrades🔗
Upgrading one microservice should not require microservices to be upgraded.
Upgrade Strategies :
- Stop v1, start v2 : short period of unavailability
- blue-green swap : run v1 & v2 simultaneously and swap traffic from v1 to v2 using load balancer (minimal downtime).
- rolling upgrade : there are several v1 instances running, removing one by one v1 instances and replacting with v2 (kubernetes is useful).
Monitoring Microservices🔗
What should we monitor ?
Host Metrices
- CPU percentages
- Memory Usage
- Configure alerts
Application Metrices
- HTTP requests
- Errors (401, 500)
- Queue Length (scale out or DDOS)
- Dead-letter queue
- Health checks
Logs
- Aggregated
- Standardize log output
- Kibana
- Application Insights
Take advantage of builtin monitoring and observability capabilities of your microservices hosting platform.