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Microservices
The next step in architecture?
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Agenda
• 16:00 – 16:30 Walk-in
• 16:30 – 17:15 Microservices: Roger
• 17:15 – 18:30 Vision and patterns MuleSoft
• 18:30 – 19:30 Dinner
• 19:30 – 20:30 Handson MuleSoft
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Microservices
• Definition
• Drivers
• Sizing
• MS vs SOA
• MS Ecosystem
• Decomposition
• Patterns and Anti-Patterns
• Frameworks and tooling
• Reference Architecture
• Microservices Conference Berlin 2018
• Takeaways
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What is a Microservice ?
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Resilient
Business
Capability
Container
DevOps
Loose
Coupling
Strong
Cohesion
Polyglot
Bounded
Context
Scaling
EDA
API
Cloud

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The presentation from our online webinar "Design patterns for microservice architecture". Full video from webinar available here: https://www.youtube.com/watch?v=826aAmG06KM If you’re a CTO or a Lead Developer and you’re planning to design service-oriented architecture, it’s definitely a webinar tailored to your needs. Adrian Zmenda, our Lead Dev, will explain: - when microservice architecture is a safe bet and what are some good alternatives - what are the pros and cons of the most popular design patterns (API Gateway, Backend for Frontend and more) - how to ensure that the communication between services is done right and what to do in case of connection issues - why we’ve decided to use a monorepo (monolithic repository) - what we’ve learned from using the remote procedure call framework gRPC - how to monitor the efficiency of individual services and whole SOA-based systems.

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( Microservices Architecture Training: https://www.edureka.co/microservices-... ) This Edureka's Microservices tutorial gives you detail of Microservices Architecture and how it is different from Monolithic Architecture. You will understand the concepts using a UBER case study. In this video, you will learn the following: 1. Monolithic Architecture 2. Challenges Of Monolithic Architecture 3. Microservice Architecture 4. Microservice Features 5. Compare architectures using UBER case-study

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The microservice architecture is growing in popularity. It is an architectural style that structures an application as a set of loosely coupled services that are organized around business capabilities. Its goal is to enable the continuous delivery of large, complex applications. However, the microservice architecture is not a silver bullet and it has some significant drawbacks. The goal of the microservices pattern language is to enable software developers to apply the microservice architecture effectively. It is a collection of patterns that solve architecture, design, development and operational problems. In this talk, I’ll provide an overview of the microservice architecture and describe the motivations for the pattern language. You will learn about the key patterns in the pattern language.

microservicesmicroservice architecturepattern language
History
• A group of architects cam together in Venice 2011 to discuss
the common architectural styles recently exploring
• In May 2012, the same group decided on “Microservices” as
the most appropriate name.
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Wat is a Microservice Architecture?
The microservice architectural style is an approach to developing a
single application as a suite of small services, each running in its
own process and communicating with lightweight mechanisms, often
an HTTP resource API.
These services are built around business
capabilities and independently deployable by fully automated
deployment machinery. There is a bare minimum of centralized
management of these services, which may be written in different
programming languages and use different data storage
technologies.
-- James Lewis and Martin Fowler
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“Microservices are small autonomous services that work
together” – Sam Newman
“Loosely coupled service-oriented architecture with bounded
contexts” – Adrian Cockcroft
“A microservice is an independently deployable component of
bounded scope that supports interoperability through message-
based communication.
Microservice architecture is a style of engineering highly
automated, evolvable software systems made up of capability-
aligned microservices.”
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Characteristics
• Componentization via Services
• Organized around Business Capabilities
• Products not Projects
• Smart endpoints and dumb pipes
• Decentralized Governance
• Decentralized Data Management
• Infrastructure Automation
• Design for failure
• Evolutionary Design Martin Fowler
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YouTube Link: https://youtu.be/xuH81XGWeGQ ** Microservices Architecture Training: https://www.edureka.co/microservices-... ** This Edureka's video on Microservices Design Patterns talks about the top design patterns you can use to build applications. In this video, you will learn the following: 1:29 Why do we need Design Patterns? 3:41 What are Design Patterns? 4:28 What are Microservices? 6:00 Principles behind Microservices 10:24 Microservices Design Patterns Follow us to never miss an update in the future. YouTube: https://www.youtube.com/user/edurekaIN Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Castbox: https://castbox.fm/networks/505?country=in

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Microservice
Framework /
Language
Database
REST REST
API
Bounded Context / scope
Microservice
Framework /
Language
Database
API
Bounded Context / scope
Microservice
Framework /
Language
Database
API
Domain Model Domain Model
Domain Model
Drivers
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Agility
Safety
Release Speed
ScalabilityExperimenting
Flexibility
Replaceability
Microservices
Drivers
Decentralized
Governance
What makes a good size?
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This document provides an overview of microservices architecture, including concepts, characteristics, infrastructure patterns, and software design patterns relevant to microservices. It discusses when microservices should be used versus monolithic architectures, considerations for sizing microservices, and examples of pioneers in microservices implementation like Netflix and Spotify. The document also covers domain-driven design concepts like bounded context that are useful for decomposing monolithic applications into microservices.

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This document provides an overview of microservices and monolithic architectures. It discusses how monolithic applications are self-contained and execute end-to-end tasks, while microservices are small, independent services that communicate to perform tasks. The document outlines characteristics of each approach and compares their advantages and disadvantages, such as improved scalability, deployment and innovation with microservices versus better performance with monolithic architectures. Examples of companies using microservices are also provided.

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“Size” of a Microservice
• LOC?
• One “entity”?
• Team size?
• API size?
• Deployment time?
• Sam Newman “small enough and no smaller”
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Decomposition
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Business
Capability
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Ubiquitous
Language
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Storming
Example (DDD)
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Entities
Aggregates
Object
Values
Business
Capabilities
Ubiquitous language
Interesting DDD methods
• Event storming
(See https://www.infoq.com/news/2014/06/dddx-brandolini-
eventstorming)
• Domain Story telling
(See https://www.infoq.com/news/2018/02/storytelling-domain-
contexts)
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This document provides an introduction to microservices. It begins by outlining the challenges of monolithic architecture such as long build/release cycles and difficulty scaling. It then introduces microservices as a way to decompose monolithic applications into independently deployable services. Key benefits of microservices include improved agility, scalability, and innovation. The document discusses microservice design principles like communicating over APIs, using the right tools for each service, securing services, and being a good citizen in the ecosystem. It provides examples of how to implement a restaurant microservice using AWS services like API Gateway, Lambda, DynamoDB and containers.

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1) Event-driven microservices involve microservices communicating primarily through events published to an event backbone. This loosely couples microservices and allows for eventual data consistency. 2) Apache Kafka is an open-source streaming platform that can be used to build an event backbone, allowing microservices to reliably publish and subscribe to events. It supports streaming, storage, and processing of event data. 3) Common patterns for event-driven microservices include database per service for independent data ownership, sagas for coordinated multi-step processes, event sourcing to capture all state changes, and CQRS to separate reads from writes.

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Data
• What is the data representing in a particular domain context?
Boundaries: DDD Entities, Value objects and Aggregates.
i.e. Book in seach context is Title
and in Order is titles+copies, so
entities mean different things !
• Transaction boundaries: smallest
unit of atomicity that you need
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Microservices “vs” SOA
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Microservices “vs” SOA
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SOA Microservices
Layering (utility, entity, task layers) No layering (on service level)
CDM Domain Models
http/soap, XML, WSDL , XSD REST/http, JSON, Polyglot
Composite orchestrations Event driven architectures
ESB Service Mesh
Value chain and business model is
changing the entire business process
Value chain and business model is about
efficiencies, small teams and DevOps
practices while eliminating cilos.
Focus on reusability Focus on usability and speed
Loose Coupling Loose Coupling
Dividing problem domain into services Dividing problem domain into services
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A brief overview of the significance of API Gateways in microservices architecture by providing Kong as an example. Slide 2: Monolith Vs Microservices Monolith: Pros- Simple to implement Less integration test - easy to test Easy to ship Fast development Cons- Violates Open-Close principle Nightmare when it comes to managing the code Difficult to enhance Bigger artifacts Hard to replace individual components like DB, Logger etc. Microservices- Pros- Easy to manage One reason to change Dynamic scaling Single responsibility Cons- Multiple points of failure Hard to test - rich integration tests required Heterogeneity in infrastructure Slide 3: API Gateway Pattern It is microservices design pattern. An API gateway is a service which is the entry point into the application from the outside world. It’s responsible for request routing, API composition, and other functions, such as authentication. There are a lot of issues when client is talking to multiple components to get the job done. These include multiple proxies at client side, different logic to handle different calls, client needs to know the implementation details of server. A much better approach is for a client to make a single request to what’s known as an API gateway. An API gateway is a service which is the single entry-point for API requests into an application. It’s similar to the Facade pattern from object-oriented design. Like a facade, an API gateway encapsulates the application’s internal architecture and provides an API to its clients. It might also have other responsibilities, such as authentication, monitoring, and rate limiting. These are also termed as BFF - Backend For Frontend Slide 4: API Gateway in Action It acts as a “backend for the frontend”. The clients do not know which services they are talking to. They communicate with a single interface - API Gateway. The gateway resolves the client requests and distributes them to respective services. Slide 7: Kong Architecture Kong is a cloud-native, fast, scalable, and distributed Microservice Abstraction Layer (also known as an API Gateway, API Middleware or in some cases Service Mesh). Made available as an open-source project in 2015, its core values are high performance and extensibility. Actively maintained, Kong is widely used in production at companies ranging from startups to Global 5000 as well as government organizations.

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Microservice
Ecosystem
Service
(micro)
Process
Tools
CultureOrganisation
Solution
(macro)
Microservices
Platform
SOA
• “Small” services
• Domain Drive Design
• Webservices
• CQRS
DevOps
• CI / CD
• Monitoring
• Automatic testing
• Deployments
Agile /
Organisation
• Small teams
• Small increments
• Fast delivery
• Culture
Cloud
• Containerization
• Horizontal scaling
• Deployments
Event Driven
Architecture
• Loose coupling
• Event sourcing
API Management
• REST API
• Routing
• API Gateway
• Orchestration
• Transformation
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Design Patterns
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Patterns and Anti-Patterns
Anti-Patterns
• Distributed Monolith (hype driven architecture)
• Decoupling Illusion (technical- does not match business separation)
• Micro Platform (standardization internal runtime aspects)
• Entity Service (too wide business entities)
• Anemic Service (solely data encapsulation)
• Unjustifed re-use (extremely generic utility functions)
• Domain-last approach (org structure around technical capabilities, not
business domain)
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Source: http://microservices.io/patterns
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Distributed Monolith
• Microservices gone bad
• System made up of arbitrarily sized, tightly coupled modules
communicating over network interfaces
(i.e. everything is DCOM object)
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Decoupling Illusion
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• Functional changes required by different stakeholders require changes
to overlapping services
• Too much focus on re-use

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This document discusses microservices and their evolution from monolithic applications. It defines microservices as the smallest deployable units that can function independently. The document outlines the benefits of microservices like improved agility, scalability and fault tolerance compared to earlier architectures like SOA. It also discusses some challenges of microservices like integration testing and service discovery. The document recommends approaches like automation, DevOps practices and service meshes to overcome microservices challenges. It advises that microservices are suitable when requirements involve frequent changes, time to market pressure or building cloud platforms.

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• Standardization of service internal runtime aspects
• (Perceived ) increased efficiency, but practically shared
dependencies on details, which increases the need for
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capabilities, not business domain
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Patterns
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over all aspects of a set of capabilities
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Sizing Patterns (small -> large)
• FaaS (Function as a Service, small, async, serverless)
• microSOA (small, self hosted containerized services, close)
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• Self-contained Systems (UI+DB)
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Tooling
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Hystrix
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Today, the large public Clouds - Azure and AWS - deploy at high-speed a diversity of services and features. Between Azure Functions, Event Grid, Azure VM Scale Sets, or Logic Apps, what to choose? Shall I go on Microservices? Event-Driven? Lambda Architecture? Deploy on Serverless? Containers? Modern Compute? Let's put a bit of order in all that. Enter the Modern Architecture, the foundation of all the new wave of Cloud services and not only. Session focused on application and infrastructure architecture, examples based on Cloud, perspectives and roadmap of the corresponding services at Microsoft.

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Type of tools
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Play framework, Lagom, Eventuate)
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Service Mesh
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No centralized integration/ESB layer but a set of (composite and
atomic) microservices. Service-to-service communication at the
microservices level.
Microservices toolsheet
• Sheet with reference architecture concepts and the
tools/frameworks/products available to fill in those concepts
• Feel free to contribute !
• https://docs.google.com/spreadsheets/d/1BAR2pZlaqNGAEAW
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Reference Architecture
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• Architecture /design / tools&framework sessions
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What’s next
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Not since the rise of Service Oriented Architecture (and the supporting Fusion Middleware technology) over a decade ago have we seen so much rapid change in terms of application and infrastructure architecture. Cloud, Microservices and DevOps are perhaps the most explicit examples – but many other developments in technology, architecture and even the industry at large have an impact on how enterprises consider and employ IT – such as machine learning, IoT, blockchain. In this session for (infrastructure, solution, application, enterprise, security, data) architects – we will present the main stories, roadmaps and technologies from Oracle OpenWorld 2017 (and JavaOne) that influence, shape and enable architecture. We will brainstorm together on the consequences of the new directions outlined by Oracle – and coming our way from other quarters. We are seeing a a lot of change. New opportunities arise – that may become challenges or threats if we fail to recognize and embrace the change in time. This session will help us all to get a better handle on the winds in enterprise IT in general and in Oracle land in particular. Among the topics we will present and discuss are: - The Only Way is Up – the inevitable and imminent move from on premises to the cloud, and upwards in the stack – from IaaS to SaaS - Security and Ops in a hybrid landscape (multiple clouds & on premises, multiple technologies & interaction channels) - Autonomous Database – what, when, how - Oracle’s cloud strategy, High PaaS and Low PaaS, Open [source] technology (star of the show: Apache Kafka) and the commodization of the traditional Oracle platform - Container and Cloud Native at Oracle Cloud (Docker, Kubernetes Container Platform, Wercker, Istio Service Mesh, CNCF) - Serverless - Java Reborn – for microservices and cloud, modularized (highlights from the JavaOne conference) - Disruptive: Blockchain, IoT, Machine Learning

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• Microservices Maturity Model
• Consumer Driven Contracts
• Frontend modularisation needs innovation
• Organisational structures (team sizes)
• Event Sourcing
• Handling data (sharing / transactions (Sagas))
• Security (OpenID, OAuth2, JWT)
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Takeaways
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• Microservices is (still) not the holy grail !
• Don’t fall into trap of the anti-patterns
• Don’t fall into the trap of hype and available tools and
frameworks
• Microservices is no mainstream and commodity. Tools are not
always production ready
• Microservices architecture is NOT easy
• Define what you try to achieve
• Add it to your bag of architecture tools
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Backup slides
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Resources
• https://martinfowler.com/microservices/
• http://microservices.io/patterns/microservices.html
• http://api.co/msabook
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Books
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Componentization via Services
A component is a unit of software that is independently
replaceable and upgradeable.
libraries are components that are linked into a program and
called using in-memory function calls
services are out-of-process components who communicate with
a mechanism such as a web service request, or remote procedure
call.
One main reason for using services as components (rather than
libraries) is that services are independently deployable.
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Organized around Business Capabilities
Conway’s Law:
Any organization that designs a system (defined broadly) will
produce a design whose structure is a copy of the organization's
communication structure.
-- Melvyn Conway, 1967
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Organized around Business Capabilities (2)
The microservice approach to division is different, splitting up
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user-interface, persistant storage, and any external collaborations)
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Products not Projects
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Smart endpoints and dumb pipes
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• The smarts live in the end points that are producing and
consuming messages; in the services.
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Decentralized Governance
• So less standardization on platforms and technology
( costs !)
• Use right tool for the job
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Bounded Context
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Infrastructure automation
• CD/CI
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Design for Failure
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Evolutionary Design
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replacement and upgradeability
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that's a sign that they should be merged.
• Avoid versioning (be tolerant)
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Monolith sv Microservices
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1. Hardware
Bare metal, AWS EC2, Google Cloud Platform,
Azure.
Resource abstraction: Docker, Apache Mesos
Configuration management, Provisioning,
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Network, DNS, service discovery, service
load balancing, messaging
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Development tools, test/package/build/release,
deployment pipeline, logging and monitoring
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configurations
mei ’18 67
Layer 4: Microservices
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How to decompose?
• Business Capabilities
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structured (Conway’s law)
• Domain-Driven Design (DDD) subdomain
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Introduction to Microservices

  • 1. Microservices The next step in architecture? mei ’18
  • 2. Agenda • 16:00 – 16:30 Walk-in • 16:30 – 17:15 Microservices: Roger • 17:15 – 18:30 Vision and patterns MuleSoft • 18:30 – 19:30 Dinner • 19:30 – 20:30 Handson MuleSoft mei ’18 2
  • 3. Microservices • Definition • Drivers • Sizing • MS vs SOA • MS Ecosystem • Decomposition • Patterns and Anti-Patterns • Frameworks and tooling • Reference Architecture • Microservices Conference Berlin 2018 • Takeaways mei ’18 3
  • 4. What is a Microservice ? mei ’18 4 Resilient Business Capability Container DevOps Loose Coupling Strong Cohesion Polyglot Bounded Context Scaling EDA API Cloud
  • 5. History • A group of architects cam together in Venice 2011 to discuss the common architectural styles recently exploring • In May 2012, the same group decided on “Microservices” as the most appropriate name. mei ’18 5
  • 6. Wat is a Microservice Architecture? The microservice architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API. These services are built around business capabilities and independently deployable by fully automated deployment machinery. There is a bare minimum of centralized management of these services, which may be written in different programming languages and use different data storage technologies. -- James Lewis and Martin Fowler mei ’18 6
  • 7. “Microservices are small autonomous services that work together” – Sam Newman “Loosely coupled service-oriented architecture with bounded contexts” – Adrian Cockcroft “A microservice is an independently deployable component of bounded scope that supports interoperability through message- based communication. Microservice architecture is a style of engineering highly automated, evolvable software systems made up of capability- aligned microservices.” mei ’18 7
  • 8. Characteristics • Componentization via Services • Organized around Business Capabilities • Products not Projects • Smart endpoints and dumb pipes • Decentralized Governance • Decentralized Data Management • Infrastructure Automation • Design for failure • Evolutionary Design Martin Fowler mei ’18 8
  • 9. Bounded Context / scope mei ’18 9 Microservice Framework / Language Database REST REST API Bounded Context / scope Microservice Framework / Language Database API Bounded Context / scope Microservice Framework / Language Database API Domain Model Domain Model Domain Model
  • 11. mei ’18 11 Agility Safety Release Speed ScalabilityExperimenting Flexibility Replaceability Microservices Drivers Decentralized Governance
  • 12. What makes a good size? mei ’18 12
  • 13. “Size” of a Microservice • LOC? • One “entity”? • Team size? • API size? • Deployment time? • Sam Newman “small enough and no smaller” mei ’18 13
  • 15. Example (DDD) mei ’18 15 Entities Aggregates Object Values Business Capabilities Ubiquitous language
  • 16. Interesting DDD methods • Event storming (See https://www.infoq.com/news/2014/06/dddx-brandolini- eventstorming) • Domain Story telling (See https://www.infoq.com/news/2018/02/storytelling-domain- contexts) mei ’18 16
  • 17. Data • What is the data representing in a particular domain context? Boundaries: DDD Entities, Value objects and Aggregates. i.e. Book in seach context is Title and in Order is titles+copies, so entities mean different things ! • Transaction boundaries: smallest unit of atomicity that you need mei ’18 17
  • 19. Microservices “vs” SOA mei ’18 19 SOA Microservices Layering (utility, entity, task layers) No layering (on service level) CDM Domain Models http/soap, XML, WSDL , XSD REST/http, JSON, Polyglot Composite orchestrations Event driven architectures ESB Service Mesh Value chain and business model is changing the entire business process Value chain and business model is about efficiencies, small teams and DevOps practices while eliminating cilos. Focus on reusability Focus on usability and speed Loose Coupling Loose Coupling Dividing problem domain into services Dividing problem domain into services
  • 22. Microservices Platform SOA • “Small” services • Domain Drive Design • Webservices • CQRS DevOps • CI / CD • Monitoring • Automatic testing • Deployments Agile / Organisation • Small teams • Small increments • Fast delivery • Culture Cloud • Containerization • Horizontal scaling • Deployments Event Driven Architecture • Loose coupling • Event sourcing API Management • REST API • Routing • API Gateway • Orchestration • Transformation mei ’18 22
  • 24. Patterns and Anti-Patterns Anti-Patterns • Distributed Monolith (hype driven architecture) • Decoupling Illusion (technical- does not match business separation) • Micro Platform (standardization internal runtime aspects) • Entity Service (too wide business entities) • Anemic Service (solely data encapsulation) • Unjustifed re-use (extremely generic utility functions) • Domain-last approach (org structure around technical capabilities, not business domain) mei ’18 24
  • 25. mei ’18 25 Source: http://microservices.io/patterns Chris Richardson
  • 27. Distributed Monolith • Microservices gone bad • System made up of arbitrarily sized, tightly coupled modules communicating over network interfaces (i.e. everything is DCOM object) mei ’18 27
  • 28. Decoupling Illusion mei ’18 28 • Functional changes required by different stakeholders require changes to overlapping services • Too much focus on re-use
  • 29. Micro platform • Standardization of service internal runtime aspects • (Perceived ) increased efficiency, but practically shared dependencies on details, which increases the need for communication mei ’18 29
  • 30. Entity Service • Service boundaries are chosen to encapsulate “wide” business entities • Perceived benefit of canonical models mei ’18 30
  • 31. Anemic Service • Services designed solely encapsulate data, with logic in other layer mei ’18 31
  • 32. Unjustified re-use • Extremely generic utility functions to reduce logic redundancy • Leads to more complexity mei ’18 32
  • 33. Domain-last approach • Major driver for organisational structure is roles and technical capabilities, not business domain mei ’18 33
  • 34. Patterns • Decentralized domain focused cells with maximum authority over all aspects of a set of capabilities • Cross functional teams mei ’18 34
  • 35. Sizing Patterns (small -> large) • FaaS (Function as a Service, small, async, serverless) • microSOA (small, self hosted containerized services, close) • Distributed Domain-Driven Design (bounded context) • Self-contained Systems (UI+DB) • Monolith (1 application is ok) mei ’18 35
  • 38. Type of tools • Development (KumuluzEE , Springboot, NodeJs, Scala, Akka, Play framework, Lagom, Eventuate) • API (OpenAPI, WADL, Blueprint, RAML) • Database (Cassandra, Datomic, Mongo, Neo4J) • Gateways (Netflix Zuul, Jboss Netty, Twitter Finagle) • Monitoring (Twitter Zipkin, Netflix Hystrix) • Container management(Docker, Kubernetes, Mesos) • Communication (http, Kafka) • Service Mesh (HAProxy, traefik, NGINX, Istio, Linkerd) mei ’18 38
  • 39. Service Mesh mei ’18 39 No centralized integration/ESB layer but a set of (composite and atomic) microservices. Service-to-service communication at the microservices level.
  • 40. Microservices toolsheet • Sheet with reference architecture concepts and the tools/frameworks/products available to fill in those concepts • Feel free to contribute ! • https://docs.google.com/spreadsheets/d/1BAR2pZlaqNGAEAW q7qDyKM7xYlt3uhoHAmlnsau0gdw mei ’18 40
  • 47. • Architecture /design / tools&framework sessions • Workshops • Service Mesh • Micro frontends • Patterns (i.e. Sagas) • Kubernetes mei ’18 47
  • 49. • Microservices Maturity Model • Consumer Driven Contracts • Frontend modularisation needs innovation • Organisational structures (team sizes) • Event Sourcing • Handling data (sharing / transactions (Sagas)) • Security (OpenID, OAuth2, JWT) • Serverless (AWSLambda, functions, deployment model) mei ’18 49
  • 51. • Microservices is (still) not the holy grail ! • Don’t fall into trap of the anti-patterns • Don’t fall into the trap of hype and available tools and frameworks • Microservices is no mainstream and commodity. Tools are not always production ready • Microservices architecture is NOT easy • Define what you try to achieve • Add it to your bag of architecture tools mei ’18 51
  • 55. Componentization via Services A component is a unit of software that is independently replaceable and upgradeable. libraries are components that are linked into a program and called using in-memory function calls services are out-of-process components who communicate with a mechanism such as a web service request, or remote procedure call. One main reason for using services as components (rather than libraries) is that services are independently deployable. mei ’18 55
  • 56. Organized around Business Capabilities Conway’s Law: Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization's communication structure. -- Melvyn Conway, 1967 mei ’18 56
  • 57. Organized around Business Capabilities (2) The microservice approach to division is different, splitting up into services organized around business capability. (including user-interface, persistant storage, and any external collaborations) mei ’18 57
  • 58. Products not Projects • A team should own a product over its full lifetime • “You build, you run it” mei ’18 58
  • 59. Smart endpoints and dumb pipes • NO smart within communication mechanism (i.e. ESB) • The smarts live in the end points that are producing and consuming messages; in the services. mei ’18 59
  • 60. Decentralized Governance • So less standardization on platforms and technology ( costs !) • Use right tool for the job mei ’18 60
  • 61. Decentralized Data Management • Conceptual model of the world will differ between systems -> Bounded Context • Polyglot Persistence mei ’18 61
  • 62. Infrastructure automation • CD/CI • Automated test • Automated deployments mei ’18 62
  • 63. Design for Failure • Applications must be able to tolerate failures of services • Real-time monitoring (latency, throughput) mei ’18 63
  • 64. Evolutionary Design • Service decomposition as tool for flexibility and change • The key property of a component is the notion of independent replacement and upgradeability • If you find yourself repeatedly changing two services together, that's a sign that they should be merged. • Avoid versioning (be tolerant) mei ’18 64
  • 65. API Gateway vs Service Mesh mei ’18 65
  • 67. 1. Hardware Bare metal, AWS EC2, Google Cloud Platform, Azure. Resource abstraction: Docker, Apache Mesos Configuration management, Provisioning, monitoring and logging 2. Communication Network, DNS, service discovery, service load balancing, messaging 3. Application platform Development tools, test/package/build/release, deployment pipeline, logging and monitoring 4. Microservices Microservice itself and corresponding configurations mei ’18 67 Layer 4: Microservices Layer 3: Application platform Layer 2: Communication Layer 1: Hardware
  • 71. How to decompose? • Business Capabilities Guides the decomposition according to the way the business is structured (Conway’s law) • Domain-Driven Design (DDD) subdomain Provides a suite of tools and methodologies to reason about the underlying domain at hand. DDD Strategic Patterns guide the creation of a context map which forms the foundation of the decomposition mei ’18 71