Whether you want to create new services, decouple a few services from your overall architecture, or refactor an entire monolithic architecture into a microservice design pattern, this course quickly teaches you the practical toolset and skills to get up and running with microservices in your own systems. Loosely coupled components and services allow teams to deploy more freely and independently, with less risk to the architecture.
Class exercises use Java, but for private onsite deliveries, exercises can be done using your preferred language.
Who should attend
- System and software architects
- Developers
- Testers and QA teams
- Release engineers
- IT operations staff
- Site reliability engineers
- DevOps practitioners
- DBAs and data engineering teams
- Information Security Pros
Prerequisites
Programming experience is required. Exercises use Java, but for private onsite deliveries, exercises can be done using your preferred language.
Course Objectives
In this Course, You Will Learn How To:
- Adopt, plan or improve your transition to microservices
- Map technical practices to the business strategy behind microservices
- Navigate different tools for enabling microservices and how to use them
- Communicate with stakeholders, management, and teams regarding needs and expectations around microservices
- Get hands-on practice with Docker, Kubernetes, Jenkins, and JFrog tools for core microservices architecture
- Get hands-on practice with the toolchain in our real-world application labs
- Build more mature DevOps practices through microservice adoption
- Understand how to refactor monolithic systems into more modular, component-based systems
- Apply microservice use cases to continuous integration, delivery, and testing
- Enable more automated testing and self-service QA capability
Outline: Microservices Engineering Boot Camp (MICROENGINEER)
Part 1: Intro to Microservices
- Optimize for speed, not efficiency
- Case Study: General Electric
- Throughput
- Waste
Amazon Web Services Case Study (SOA/Microservices)
- Problem: Scaling the Organization and the ‘Big ball of mud’
- Conway’s Law
- Service Oriented Architecture
- Forced Self Service Mandate
- Result: Amazon dominance of cloud
- Result: High velocity at scale
Intro to Containers (encapsulation)
- What is Docker
- Exercise: Install Docker
- Exercise: Docker Hello World[/b]
- Docker ecosystem
- Docker concepts
- Container encapsulation/ideal use cases
-
- Encapsulation
- Speed
- Increased utilization of computing resources
- Benefits
- Configure once, run everywhere
- VM’s vs Container use cases
- Databases & stateless workloads
- Docker Architecture
- Exercise: Docker 101 – Web App
- Docker File System
- Docker Images
- Exercise: Stateless Web App
- Local Registry
- Data Volumes
- Exercise: Docker 201 – Compose Multi-tier app
- Continuous integration patterns
- Docker Security
- Continuous Integration
-
- Canary Release
- Blue Green Deployment
- A/B Testing
- Rolling Update
- Jenkins Plugin
Microservice challenge: Continuous Integration Service
- On-Premise
- Jenkins
- SaaS Service
- Shippable
- Jenkins
- TravisCI
- Exercise: Trigger build/tests from change
Part 2: Microservices in Development Uber Case Study
- 2000 services, 1000 engineers
- Tradeoffs
[*] Plus – overall development speed [*] Cons – technical challenges [/list]
Box Case Study
- Traditional service deployment with bare metal
- 10x faster workflow with DevOps practices
Microservice challenge: Image repository
- Docker repository development instance
- On-Premise Service
- Quay by CoreOS
- SaaS solution
-
- Docker Hub
- JFrog
- Exercise: Submit image to service
- Exercise: Pull image from service
Intro to Kubernetes (Containers at Google)
- Prerequisites
- Containers
- Linux Kernel Features
- Container User Experience
- New Container Capabilities
- Gaps using Containers in Production
Exercise: Kubernetes 100: Hello World
Core Concepts
- Cluster Orchestration
- Originated at Google
- Open Source
- Benefits
- Design Principles
Architecture
- Master/Node
- Kubectl
- Replication Controller
- Kubelet
- Kube-Proxy
- Persistent Volumes
- Etcd
- High Availability
- Exercise: Kubernetes 101: Stateless web app Kubernetes Features
- Pods
- Labels
- Services
- Namespaces
- Resource Quota
Exercise: Kubernetes 201: Guestbook app Part 3: Microservices in Production
- [list]
- Spotify Case Study 810 Services, 477 engineers
- Microservice challenge: Service discovery[/b]
- Skydns
- Consul
- Exercise: Resolve service with DNS
- Security[/b]
- Goals
- Roles
- Attribute Based Access Control
- Policies
- Service Accounts
- Secrets
- Forth Microservice challenge: Secrets[/b]
- Vault
- Kubernetes Secrets API
- Exercise: Kubernetes – Store database credentials in cluster
- Cluster Add-ons[/b]
- Cluster DNS
- Logging with Elasticsearch and Fluentd
- Container Level Monitoring
- cAdvisor
- InfluxDB
- Prometheus
- Exercise: WordPress on Kubernetes[/b]
- Managing state with disposable architectures[/b]
- Tradeoffs, standalone vs containerized databases
- AP Theorem
- SQL Databases
- NOSQL Databases
- Exercise: Cassandra on Kubernetes
- Practicing Failure
- Optimize MTTR
- Netflix Case Study
- Simian Army
- Graceful handling of failure
Part 4: Putting it all together Why Microservices?
- Scale an organization
- Tradeoffs
- Fault Tolerance
- Throughput
- Waste
Kubernetes Alpha Features
- Multi-Datacenter Control Plane
- RBAC/Multi-tenancy
Openshift/Mesos/Other PaaS platforms Exercise: Customize Microservice App Exercise: Scale app for simulated demand Review of Microservice Challenges
- Secure Images
- Highly available application
- Secrets
- Continuous Integration
- DNS Name resolution
