- Microservices small targeted services
- Each service has its own repository
- Microservices are isolated from other services
- Should not be bundled with other services when deployed
- Microservices are loosely coupled
- When interacting with other services, should be done in a technology-agnostic manner
- ie - Restful web services - HTTP / JSON
With a Microservice Architecture:
- Applications are composed using individual microservices
- Each service will typically have its own database
- Each microservice is independently deployable
- Scaling of individual services is now possible
- CI/CD becomes easier since services are smaller and less complex to deploy
Benefits of Microservices
- Agility : one word for microservices
- Easy to understand & develop - Services are smaller and more targeted
- Software Quality - Since services are more targeted and have a limited scope
- Scalability - Independent services can be scaled up and down to the application’s demands.
- Reliability - Software bugs are isolated
- Technology flexibility - Services can be developed using any language or technology stack.
Cons of Microservices
- Integration testing can be difficult
- Deployments are more complex. Rather than one application to deploy, you now have many. Operational cost with each service - Each service is a small application
- Needs own repo, own deployment process, own database, etc
- Additional hardware resources - Additional services need additional hardware to run on
How ‘Big’ Should a Microservice Be?
- A microservice can be as small as a single API endpoint ie - ‘Get Orders’
- A microservice can be several or even dozens of API endpoints
- Guideline - Amazon’s Two Pizza Team - A microservice should be able to be supported be a team you can fed with two pizzas. (~12 people)
- Scalability - This can also be a consideration in the size of a microservice
- The higher the scalability, the more specialized the service should be
Comparison of Monolithic and MicroSercvices :
Important recipe of a microservices
API
Tracing
Monitoring
Logging
Discovery
Invocation
MyService
VERTX
Authentication
Pipeline
Elasticity
Residence
What is Gateway?
- Endpoint that is exposed to other services
- Can be internet for public APIs
- More likely to be internal
- Abstracts implementation of services
- Client calls URL, is unaware of routing taking place to run the instance
- Acts as roughly a proxy for network traffic
- Can also act as a load balancer
About Service Instances
- Expect to be running N number of services
- The exact number depends on reliability and load requirements
- Minimum might be 3, for high availability
- Some tools allow you to dynamically scale based on load or anticipated load
- Think Netflix at night
- In evenings, Netflix traffic is 1/3 of US internet traffic
- Netflix will scale up and down with the load
About Database Tier
- Typically one database per microservice
- Guideline - not a hard ‘rule’
- Highly scalable services will often have one transactional database
- And one or more read database (replicas)
- Organizations will often have more than one database technology
- Not uncommon to see the mix of SQL and NoSQL database technologies
Messaging
- A common pattern is to expose an API endpoint via a RESTFul API
- Dependent microservices are often message based
- Messages follow an event or command pattern
- Messaging allows for decoupling and scalability
- Messaging can be used to define a work flow
- New Order, Validate Order, Charge Credit Card, Allocate Inventory, Ship Order
Monitoring
Monitoring
https://gist.github.com/tyrell/5dOfe1003551dbe05112a64bd51a9c08
Heapster, Hawkular. Cassandra
https://docs.openshift.com/container-platform/3.5/scaling_performance/scaling_cluster_metrics.htmi
If you wish to try it minishift -metrics start
bit.ly/microservicesdeepdive
bit.ly/msa-instructions
bit.ly/javamicroservicesbook
bit.ly/reactivemicroservicesbook
bit.ly/mono2microdb
JVM + Docker FAIL bit.ly/jbcnconfJavaFail
https://github.com/redhat-helloworld-msa/goodbye
https://github.com/burrsutter/kube4docker
https://github.com/burrsutter/javadockerfail
More Advanced Topics
Domain Driven Design: Know your boundaries
HTTP/2 vs HTTP/1
GRPC or AMQP vs HTTP
Feature Toggles
A/B Testing
Sidecars & Service Mesh
CORS & Event Sourcing
Advanced Service Choreography
Logging
https://docs.openshift.com/container-platform/3.5/install_config/aggregate_logging.html
EFK
Elasticsearch - An object store where all logs are stored
Fluentd - Gathers logs from Nodes and feeds them to Elasticsearch
Kibana - A web UI for Elasticsearch
Tracing
Zipkin, Opentracing.io, Jaeger
http://opentracing.io/documentation/pages/supported-tracers
Opentracing.io is where it is all coming together. It gives you a common API to instrument
your code.
Zipkin was open sourced by Twitter (http://zipkin.io) - leverage Brave and Feign
Jaeger by the Uber team
Supported Tracers: http://opentracing.io/documentation/pages/supported-tracers
For more details : https://12factor.net/
