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Cloud / Microservices / DevOps
 Architecture Considerations
o Strategic Goals and Vision
o Architectural Principles to guide development
o Defining boundaries of modules / microservices
 Declaring a bounded context
 Chattiness / coupling
 Expressiveness of model
 Feature roadmap
o Design and Delivery Practices
 Required Standards
 Monitoring
 Interfaces
 Architectural Safety
 Reusable Service Archetypes / Code Libraries
o Iteration – redoing code to become more elegant, vs. striving for a perfect
solution from the start. Not to be confused with slicing, as in Agile.
 Cloud
o Programmable infrastructure that you can introspect and make strong
assertions about
o On-demand capacity
o Built on commodity hardware/software
o Competition between cloud platforms is driving down cost
 Penalty of lock-in is outweighed by cost reduction curve
 Service Design Best Practices
o Loose Coupling
o High Cohesion
o Bounded Contexts
o Single-Responsibility Principle
o Stateless to support horizontal scalability
o Hide implementation details
 Service Integration
o Technology-agnostic APIs
 JSON / XML
 Protocol Buffers
 REST and HATEOAS
 Spring abstractions
o Request/Response vs. Asynchronous Event-Based Communication
 Choreographed architecture preferred over Orchestration
 Inform each part of the system through message bus
o Versioning
 Semantic Versioning (MAJOR, MINOR, PATCH)
 Version in endpoint URL
 Version in request header
o API Gateways
 Portability layer for forwards/backwards compatibility
o Strangler Pattern
 Abstraction layer on top of legacy systems
o Discovery and Coordination
 Netflix Eureka
 Optimized for AWS
 Placed behind AWS ELB
 Mid-tier round-robin load balancer
 Optional Sidecar for non-JVM apps
 Consul
 DNS
 ZooKeeper
 Metadata in AWS
 Testing
o Unit Tests / TDD
 Spock
o Service Tests – Mock/Stub downstream collaborators
o Consumer-Driven Tests
o End-to-End Tests
o Testing in Production
 Blue/Green Deployment
 Canary Releases
 Rolling Upgrades
 A/B Testing
 Indeed Proctor
 Feature Toggles
o MTBF / MTTR
 Deployment
o Continuous Integration
o Build Pipeline
o Images as Artifacts / Immutable Servers
 Docker containers
 Spin up new instance instead of modifying existing.
 “Cattle” vs. “Pet” servers
 Ephemeral infrastructure
o Environment Definitions
o Rollout Plan
o Rollback Plan
 Logging of audit metadata to reverse actions
o AWS CloudFormation
 Security
o SSO Gateway / Identity Provider
o Service-to-Service Auth.
 oAuth 2.0 / JSON Web Token (JWT)
 Network Segmentation
 HTTP(S) Basic
 X.509
 API Keys
o Multi-tenancy
o Concerns
 Man-in-the-Middle attack
 Confused Deputy Problem
 Scaling
o Circuit Breakers
o Bulkheads
o Idempotency
o Immutable Data Structures
o Load Balancing
o Worker-based systems
o Data Access Strategies
 Scaling for reads
 Scaling for writes
 Caching
 CQRS / Event Sourcing
 Explicitly modeling events and state change
 Derive current state from series of events
 Actor model
o CAP Theorem
 Sacrificing Consistency
 Sacrificing Availability
 Sacrificing Partition Tolerance
 Monitoring
o Failure Detection
o Performance Degradation Detection
 Latency
 Throughput
 Utilization
o Capacity Planning
o User Interaction
o Intrusion Detection
o Process Mining
o Tools
 Icinga / Nagios
 Graphite / Grafana
 Logstash
 Splunk / ElasticSearch
 AWS CloudWatch
 Netflix Architecture
o Disk inside EC2 instances
o Triple-replicated Cassandra
o Ribbon/Karyon
o Eureka instance in each availability zone
 ZooKeeper “too consistent”
 API versioning
o Hystrix circuit breakers
o Customer-facing apps optimized for ‘AP’
o Business apps optimized for ‘CA’
o Security Monkey
 NoSQL - “Not only SQL”
o Cassandra
o MongoDB
o Couchbase
o Neo4j

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Cloud Microservices DevOps Architecture

  • 1. Cloud / Microservices / DevOps  Architecture Considerations o Strategic Goals and Vision o Architectural Principles to guide development o Defining boundaries of modules / microservices  Declaring a bounded context  Chattiness / coupling  Expressiveness of model  Feature roadmap o Design and Delivery Practices  Required Standards  Monitoring  Interfaces  Architectural Safety  Reusable Service Archetypes / Code Libraries o Iteration – redoing code to become more elegant, vs. striving for a perfect solution from the start. Not to be confused with slicing, as in Agile.  Cloud o Programmable infrastructure that you can introspect and make strong assertions about o On-demand capacity o Built on commodity hardware/software o Competition between cloud platforms is driving down cost  Penalty of lock-in is outweighed by cost reduction curve  Service Design Best Practices o Loose Coupling o High Cohesion o Bounded Contexts o Single-Responsibility Principle o Stateless to support horizontal scalability o Hide implementation details  Service Integration o Technology-agnostic APIs  JSON / XML  Protocol Buffers  REST and HATEOAS  Spring abstractions o Request/Response vs. Asynchronous Event-Based Communication  Choreographed architecture preferred over Orchestration  Inform each part of the system through message bus o Versioning  Semantic Versioning (MAJOR, MINOR, PATCH)  Version in endpoint URL  Version in request header o API Gateways  Portability layer for forwards/backwards compatibility
  • 2. o Strangler Pattern  Abstraction layer on top of legacy systems o Discovery and Coordination  Netflix Eureka  Optimized for AWS  Placed behind AWS ELB  Mid-tier round-robin load balancer  Optional Sidecar for non-JVM apps  Consul  DNS  ZooKeeper  Metadata in AWS  Testing o Unit Tests / TDD  Spock o Service Tests – Mock/Stub downstream collaborators o Consumer-Driven Tests o End-to-End Tests o Testing in Production  Blue/Green Deployment  Canary Releases  Rolling Upgrades  A/B Testing  Indeed Proctor  Feature Toggles o MTBF / MTTR  Deployment o Continuous Integration o Build Pipeline o Images as Artifacts / Immutable Servers  Docker containers  Spin up new instance instead of modifying existing.  “Cattle” vs. “Pet” servers  Ephemeral infrastructure o Environment Definitions o Rollout Plan o Rollback Plan  Logging of audit metadata to reverse actions o AWS CloudFormation  Security o SSO Gateway / Identity Provider o Service-to-Service Auth.  oAuth 2.0 / JSON Web Token (JWT)  Network Segmentation  HTTP(S) Basic  X.509  API Keys
  • 3. o Multi-tenancy o Concerns  Man-in-the-Middle attack  Confused Deputy Problem  Scaling o Circuit Breakers o Bulkheads o Idempotency o Immutable Data Structures o Load Balancing o Worker-based systems o Data Access Strategies  Scaling for reads  Scaling for writes  Caching  CQRS / Event Sourcing  Explicitly modeling events and state change  Derive current state from series of events  Actor model o CAP Theorem  Sacrificing Consistency  Sacrificing Availability  Sacrificing Partition Tolerance  Monitoring o Failure Detection o Performance Degradation Detection  Latency  Throughput  Utilization o Capacity Planning o User Interaction o Intrusion Detection o Process Mining o Tools  Icinga / Nagios  Graphite / Grafana  Logstash  Splunk / ElasticSearch  AWS CloudWatch  Netflix Architecture o Disk inside EC2 instances o Triple-replicated Cassandra o Ribbon/Karyon o Eureka instance in each availability zone  ZooKeeper “too consistent”  API versioning o Hystrix circuit breakers
  • 4. o Customer-facing apps optimized for ‘AP’ o Business apps optimized for ‘CA’ o Security Monkey  NoSQL - “Not only SQL” o Cassandra o MongoDB o Couchbase o Neo4j