Microservices with Spring

Cloud and Kubernetes

About Cristiano Altmann

● Desenvolvedor de software +10 anos

● Ilegra desde novembro / 2016

● Interesse:

○ Microservices

○ Reactive services

○ Event source + cqrs

● https://www.linkedin.com/in/crisaltmann/

About José Porto

● Desenvolvedor de software +10 anos

● Ilegra desde agosto / 2016

● Interesse:

○ Microservices

○ Big Data

○ Functional Programming

● https://www.linkedin.com/in/jose-eduardo-porto/

Summary

● Motivations

● High level architecture

● Kubernetes

● Spring cloud

● Conclusion

Motivations

● Organizational

○ IT Delivery

○ Legacy system

○ Multiple squads, same software

● TI

○ Scale

○ Operational costs

● Business

○ Time to market

High Level Architecture

MS A MS B MS C

High Level Architecture

MS A MS B MS C

Kubernetes

Kubernetes is an open-source system for

automating deployment, scaling, and

management of containerized applications.

Kubernetes

● Create by Google

● Active community (RedHat, Google, …)

● Scheduler

● Hybrid (public or private cloud)

● API REST

Kubernetes - concepts

● Deployment

● Pod

● Service

● Node

● Replication controller

Kubernetes - Node

● Worker machine

● Where pods are running

Kubernetes - Deployment

● Configure a desired state

○ Number of replicas

○ Docker image

○ Readiness and liveness probe

○ Environment Variables

● Replica Controller read and control the cluster based on it.

● Namespace

Kubernetes - Deployment

Kubernetes - Pod

● Instance of a deployment

● Pod is the container in execution

● Replication Controller delete, restart and create pods

Kubernetes - Pod

● Instance of a deployment

● Pod is the container in execution

● Replication Controller delete, restart and create pods

Kubernetes - Deployment - Pod

Kubernetes - Service

● Pods are mortal

● Dynamic ip and port

● Select pod by label

● Load Balancer

● Provide external access

Kubernetes - Summary

Kubernetes - Zero downtime

● Readiness probe

● Liveness probe

Spring Cloud

MS A MS B MS C MS A MS B MS C

Spring Cloud

MS A MS B MS C MS A MS B MS C

Technologies

● Java 8

● Spring Boot

● NodeJS

Spring Cloud Netflix

● Dados gerais do netflix

Ribbon

● Integration with service discovery

● Fault tolerance

● Clients integrated with load balancers

● Implements Circuit Breaker pattern

● Support to protocols (HTTP, TCP, UDP)

● RoundRobinRule

● AvailabilityFilteringRule

● WeightedResponseTimeRule

Ribbon - Load Balanced Rules

Ribbon - Load Balanced

Service A

Service B

Service B

Ribbon - Load Balanced

Service A

Service B

Service B

Ribbon

Ribbon

Ribbon

Ribbon

Feign

● Connection to HTTP APIs

● Uses minimal overhead and code

● Abstraction for Ribbon and Hystrix

Feign

Feign

Feign

Hystrix

● Circuit break pattern

● Timeout

● Fallback

● Real-time operations

● Concurrency

Hystrix - Circuit Breaker

Hystrix

Service A Service B Service C

API

Browser Mobile

Hystrix

Service A Service B Service C

API

Browser Mobile

Fallback

Hystrix - Fallback Method

Hystrix

● Turbine stream

● Metrics from Dashboard

● Several indicators:

○ Circuit state

○ Latency

○ Request rate

○ Error percentage from 10 last requests

Hystrix - Config App

Hystrix - Stream

Hystrix - Dashboard

Spring Cloud Config

● Config model spring (application, profile, label)

● Multiple EnvironmentRepository

○ GIT

○ JDBC

○ Filesystem

○ Vault

● Authorization

● Lightweight

● REST API

Spring Cloud Config

● Fast and easy to deploy applications

● Metrics

● Resilience

● Easy monitoring

● Services separate by squad

● DevOps

● Delivery speed

Conclusions