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Microservices for Java Architects
Given by Derek C. Ashmore
April 28-29
©2015 Derek C. Ashmore, All Rights Reserved 1
Who am I?
• Professional Geek
since 1987
• Java/J2EE/Java EE
since 1999
• Roles include:
• Developer
• Architect
• Project Manager
• DBA
• System Admin
©2015 Derek C. Ashmore, All Rights Reserved 2
Discussion Resources
• This slide deck
– http://www.slideshare.net/derekashmore
• Sample code on my Github
– https://github.com/Derek-Ashmore/
• Sample Java Microservice (Moneta)
– https://github.com/Derek-Ashmore/moneta
• Slide deck has hyper-links!
– Don’t bother writing down URLs
©2015 Derek C. Ashmore, All Rights Reserved 3
Agenda
The “What”
and “Why” of
microservices
Design
Considerations
and Patterns
Packaging
Options
Cross-cutting
concerns
When to use
microservices
Summary /
Q&A
©2015 Derek C. Ashmore, All Rights Reserved 4
What are Microservices?
• No concrete definition
• Common microservice traits
– Single functional purpose
• Most/all changes only impact one service
• Not dependent on execution context
– “loosely coupled”
– Independent process/jvm
– Standard Interface (typically Web Service/REST)
– Analogy: Stereo system, Linux utilities
©2015 Derek C. Ashmore, All Rights Reserved 5
Traditional Java EE Application Architecture
• Like a layer cake
• Highly cohesive
• Defined
dependencies
• Deployed as one
unit (war/ear)
• Limited Scalability
• Code Size
©2015 Derek C. Ashmore, All Rights Reserved 6
What is a Monolith?
• Hard to change
– QA test cycles are long
– Change causes unintended
consequences
• Hard to onboard new
developers
• Married to your technical
stack
• Harder to diagnose
bottlenecks and memory
issues
©2015 Derek C. Ashmore, All Rights Reserved 7
Microservices organize by domain
• Silo by business
competency
• Divide and Conquer
• How to divide is the
hard part
©2015 Derek C. Ashmore, All Rights Reserved 8
Microservices follow the Org Chart
• Conway’s Law
– Systems copy the
structure of the
organizations that build
them
• Why?
– Corps need one manager
in charge
– Reduces inter-group
conflict
©2015 Derek C. Ashmore, All Rights Reserved 9
Refactoring into Microservices
• Large benefits to
unified user
interface
• Databases
introduce
unwanted coupling
between services
©2015 Derek C. Ashmore, All Rights Reserved 10
Refactoring further
• Databases
physically
separated
• What to do with
common data
needs?
• Service call or
• Data copy
©2015 Derek C. Ashmore, All Rights Reserved 11
Alternate Database Strategy
• Centralized databases are hurdles for MS
– i.e. multiple apps use the same db
• MS-Central DB compromise
– Data items only maintained by *one* service
• All other services/apps consider that data item read-
only
• Helps data corruption investigations
©2015 Derek C. Ashmore, All Rights Reserved 12
No Lock-in
• Platform agnostic
• Fewer dependency
conflicts
• Still have cross-cutting
concerns
• “Toll” for first app
• Still have support
concerns
• Others need to be
able to support your
work
13©2015 Derek C. Ashmore, All Rights Reserved
Easier Management /
Higher Throughput
• Easier to manage large
numbers of developers
– Concentrate on
intelligently drawing
service boundaries
– Manage/enforce service
contracts
• Each service team works
independently
• Team independence leads
to higher development
throughput
©2015 Derek C. Ashmore, All Rights Reserved 14
Isn’t this SOA?
• Yes – More or less
• No concrete definitions
• SOA == dumb endpoints and smart routes
– ESB routes using Mule, Camel, etc.
– Transformations en route
• MS == dumb routes and smart end-points
– Simple routes
• Usually REST or Soap calls via http(s)
• Persistent queue route at it’s most complex
• Analogy: Electrical supply for Stereo
©2015 Derek C. Ashmore, All Rights Reserved 15
Agenda
The “What”
and “Why” of
microservices
Design
Considerations
and Patterns
Packaging
Options
Cross-cutting
concerns
When to use
microservices
Summary /
Q&A
©2015 Derek C. Ashmore, All Rights Reserved 16
Design considerations
• Service Boundaries (gerrymandering)
• Service call Failure / Unavailability
• Data Integrity
• Performance
©2015 Derek C. Ashmore, All Rights Reserved 17
Service Boundaries
• Core Services
– Services responsible for maintaining a specific business area data
– Usually named after Nouns
• Service is a system of record for a <blank>
– Student, Course, Classroom, etc.
• Process Services
– Services responsible for performing single complex tasks
– Usually represents an Action or Process
• Service is responsible for processing <blank>
– Student applications, Debt collection, etc.
– These services rely on core services
• Partitioning is an art
– Too few  same drawbacks as traditional architecture
– Too many  excessive network hops
©2015 Derek C. Ashmore, All Rights Reserved 18
Boundary Sanity Check
• Verbalize a mission statement in one sentence
in business terms
– Examples
• This service is the system of record for Student
information
• This service registers students for classes
• This service suspends students
• This service records student payments
• This service produces official transcripts
©2015 Derek C. Ashmore, All Rights Reserved 19
Context Independence Check
• Does your service have multiple consumers?
– Could it?
• Could your service execute as easily in batch as
online?
– If ‘No’, then you’re making context assumptions
• Warning Signs
– Spending time analyzing service call flow
• Your services likely make context assumptions
– Agonizing over which service should do a given
activity
• Maybe you need a new service
©2015 Derek C. Ashmore, All Rights Reserved 20
Microservices are not about size
©2015 Derek C. Ashmore, All Rights Reserved 21
….. Microservices are about having a single business purpose!
Designing for Failure
• Dependent services could be down
– Minimize human intervention
– Fail sooner rather than later
– Horizontal scaling / clustering is your first line of defense
– Coding patterns can help as a backup
• Common Patterns:
– Retry
– Circuit Breaker
– Dispatch via Messaging
©2015 Derek C. Ashmore, All Rights Reserved 22
Retry Pattern
©2015 Derek C. Ashmore, All Rights Reserved 23
• Best for asynchronous tasks
• Limit the number of tries
• Use sleep interval between tries
• Only addresses temporary outages
• Sample Retry Pattern implementation here.
• Tooling Support:
– Apache CXF supports Retry
– Spring Batch RetryTemplate
– Apache HttpClient (Example here)
Circuit Breaker
©2015 Derek C. Ashmore, All Rights Reserved 24
Circuit Breaker (continued)
• Objective: Error out sooner
– Conserves resources
– Automatically “recovers” after a time period
• Modeled after home circuit
• Works on thresholds
– Number of errors required to trip circuit
– Amount of time required to attempt retry
• Has Hysterix support
• Best embedded in interface clients / delegates
• More information here.
• Sample Circuit implementation here.
©2015 Derek C. Ashmore, All Rights Reserved 25
Dispatch via Messaging
©2015 Derek C. Ashmore, All Rights Reserved 26
• Place work instruction on persistent queue
• If receivers are down, work stacks in queue
• Work throttled by number of receivers
• Queue can be JMS or AMQP
• Tooling Support:
– JMS Api (easy API – many use natively)
– Spring JMSTemplate or RabbitTemplate (producer)
Designing for Performance
• More network traffic
– Make services course-grained
– User Interfaces need a general manager
– Horizontal or Vertical Scaling helps
• Common Patterns:
– Back-ends for Front-ends (a.k.a. API Gateway)
– Dispatch via Messaging
– Expiring Cache
©2015 Derek C. Ashmore, All Rights Reserved 27
Back-ends for Front-ends
©2015 Derek C. Ashmore, All Rights Reserved 28
Back-ends for Front-ends
(continued)
• Consolidates service calls for the browser
– Enhances performance
• Open web often not as performant as local LAN
• Also known as “API Gateway”
• Implications
– Don’t expose microservices directly to the
browser
©2015 Derek C. Ashmore, All Rights Reserved 29
Expiring Cache
©2015 Derek C. Ashmore, All Rights Reserved 30
Expiring Cache (continued)
• Look up data once and cache it
– Evict data from the cache after a defined time period
– Sometimes known as “Cache Aside”
– Reduces network calls for data
– Trades memory for speed
– More information here
• When to use
– Only use with static data
– Different clustered nodes “could” have different data for a short
time
• Tooling Support:
– I recommend Google Guava
– EHCache, Gemfire, and other tools available
©2015 Derek C. Ashmore, All Rights Reserved 31
Designing for Integrity
• Services are context independent
– Have no knowledge of how/when they are executed
• One service == One Transaction
– Two-phase commits/rollbacks are a much larger problem
• Common Patterns:
– Custom Rollback
• Write your own reversing transaction
©2015 Derek C. Ashmore, All Rights Reserved 32
Custom Rollback
©2015 Derek C. Ashmore, All Rights Reserved 33
Custom Rollback (continued)
• Reverses a transaction previously posted
• Only use this for multi-service transactions
– Keeping the transaction within one service is
preferred
• This pattern is completely custom
– No special product support available
• More information here
©2015 Derek C. Ashmore, All Rights Reserved 34
Special Problems
• Versioning
– Issues same as more traditional applications
– “Breaking” vs. “Non-Breaking” changes
• Feature “additions” usually are “Non-Breaking”
• Trend away from breaking changes
– Versioning is a last result
• It greatly increases number of contract tests
• Backward compatibility not always obvious to developers
• Prefer header versioning to URL versioning
• Explicitly error out for versions no longer supported
• More info here
©2015 Derek C. Ashmore, All Rights Reserved 35
Special Problems (continued)
• External Calls to 3rd Party Products
– Wrap external interfaces with a separate service
– Product upgrades or changes should only affect
the interface service
– Log all requests/responses
©2015 Derek C. Ashmore, All Rights Reserved 36
Common code between services?
• Yes, but….
– Version it; services make decision as to when to
upgrade
– Changes to common code can’t require the
deployment of multiple services
• That ‘common code’ needs to be its own separate
service
• Tends *not* to have business logic as that can change
and impact multiple services
©2015 Derek C. Ashmore, All Rights Reserved 37
Agenda
The “What”
and “Why” of
microservices
Design
Considerations
and Patterns
Packaging
Options
Cross-cutting
concerns
When to use
microservices
Summary /
Q&A
©2015 Derek C. Ashmore, All Rights Reserved 38
Packaging Support
• Microservices are deployed as a process
– For Java, embedded containers are easy
– Spring Boot
– Dropwizard
• Docker – standardizes the process deployment
and environment
©2015 Derek C. Ashmore, All Rights Reserved 39
Spring Boot
• Packages Java EE application into *one* deployment jar
– java –jar myApp.jar
• Support for health checks and other admin add ons via ‘Actuator’
add-on
• Supports either Jetty or Tomcat
• Best for ‘Spring-mvc’ apps
– For non-spring apps, it’s swimming upstream
• Required artifacts
– Maven
• spring-boot
• spring-boot-starter-jetty (tomcat is available)
• spring-boot-starter-actuator (optional – health checks, etc.)
– Application class with public static void main()
• Configuration coded (usually into the application class)
• Will read application.properties (app-specific properties)
©2015 Derek C. Ashmore, All Rights Reserved 40
Spring Boot Actuator
• Actuator automatically adds endpoints
– Health (needs configuration)
– Metrics
– Mappings
– Trace
– Env
©2015 Derek C. Ashmore, All Rights Reserved 41
Dropwizard
• Packages Java EE application into *one* deployment jar
– java –jar myApp.jar server myConfig.yaml
• Provides file configuration options (yaml format)
– Database connection pools
– Logging config
– Port and other container specs
• Provides easy metrics/healthcheck support
• Uses Jetty
• Required artifacts
– Application class (with main())
– Maven: dropwizard-core, maven-shade-plugin
©2015 Derek C. Ashmore, All Rights Reserved 42
Docker
• Is a “mini VM”
• runs a linux kernal
• Compare to
shipping container
• Standard
“connections” to
outside world
• Supported formally
by Oracle, Tomcat,
Jboss, and many
more
43©2015 Derek C. Ashmore, All Rights Reserved
Package Once, Run Anywhere!
Why Docker?
• Docker is Win-Win
– Easier for OPS and system administrators
• All software looks the same
• Standard interface for disk and network resources
– Containers can be “linked”
• Inherently automated
– Easier for developers
• Fewer environment difference issues
• Less to communicate to OPS / system administrators
• Easy to leverage work of others (docker-hub)
– If you haven’t tried Docker yet – you should!
©2015 Derek C. Ashmore, All Rights Reserved 44
Sample Java/EE Microservice
• Moneta – Greek goddess of ‘memory’
– Open source: https://github.com/Derek-Ashmore/moneta
• Objective:
– Provide a RESTful Web Service interface to a relational database
• Feature set:
– Provides generic ‘core’ services
– Returns Json-formatted data
– Supports startRow and maxRows query options
– Supports a security call-out
– Built-in Dropwizard, Spring Boot, and War-file deployments
• Sample contract spec – currently read-only (writes in progress)
– /moneta/topics – lists ‘topics’ of information
• E.g. – Topic Customer configured
– /moneta/topic/customers?startRow=5&maxRows=25
– /moneta/topic/customer/111-222-333
©2015 Derek C. Ashmore, All Rights Reserved 45
Agenda
The “What”
and “Why” of
microservices
Design
Considerations
and Patterns
Packaging
Options
Cross-cutting
concerns
When to use
microservices
Summary /
Q&A
©2015 Derek C. Ashmore, All Rights Reserved 46
Cross-cutting Concerns
• Transaction tracking
• Security
• Contract Testing
• Same as traditional applications
– Health checks
– Logging consolidation
– Performance measurement
©2015 Derek C. Ashmore, All Rights Reserved 47
Correlation IDs
• Provides context for
service calls or user
actions
• Track using HTTP
Header
• Log it on all messages /
error reports
• Include it on all service
calls or message
dispatches
• Code sample here
• Spring Boot support has
been requested
48©2015 Derek C. Ashmore, All Rights Reserved
Security
©2015 Derek C. Ashmore, All Rights Reserved 49
Security (continued)
• Keep User-level security to the UI
• Microservice security in layers
– Layer 1 – Network routing enforcement
• Limit access only to within the firewall
• Limit access to specific hosts or subnets
– Layer 2 – Use Service Accounts
• Similar to database access
©2015 Derek C. Ashmore, All Rights Reserved 50
Contract Testing
• Critical for MS architectures
– Contract changes can break other services
– Bulkhead for rogue developers
– Makes individual services more disposable
• Consumer-based testing
• Tooling support
– Apache HttpClient
– SoapUI
– ActiveMQ for JMS (embedded broker)
©2015 Derek C. Ashmore, All Rights Reserved 51
Agenda
The “What”
and “Why” of
microservices
Design
Considerations
and Patterns
Packaging
Options
Cross-cutting
concerns
When to use
microservices
Summary /
Q&A
©2015 Derek C. Ashmore, All Rights Reserved 52
When to consider MS
• Starting out with MS isn’t recommended unless
– Parts of the application will have extremely high volume
• Need to scale a portion of the application differently
• Note: MS isn’t all or nothing!
• Warning signs for app that’s too large
– Unintended consequences after release
– High technical debt / design rot
– Release testing cycles abnormally large
– Need to coordinate large numbers of developers for a
single code base
• Large number == takes more than two pizzas to feed
©2015 Derek C. Ashmore, All Rights Reserved 53
Where’s the marketing fluff?
• Easier to manage
– Maybe
• You *must* be good at contract management
• You *must* be good at specifying precisely what a microservice
needs to do
• You *must* ensure that services make no assumptions on how
they get invoked
• Easier for developers to “understand” applications
– No – sorry
• It is easier to understand a particular ‘cog’ in the machine (e.g. the
function of one service
• It is *not* easier to understand how microservices fit together to
provide a particular piece of business functionality
©2015 Derek C. Ashmore, All Rights Reserved 54
Where’s the marketing fluff?
(continued)
• Increased Development Throughput
– Maybe
• Harder for business to ‘test’ a business function for a specific combination of
microservices
• Developers work on *one* service at a time.
• You *must* be good at error detection (unintended consequences)
• The more assumptions a service makes about its execution context, the more
unintended consequences (e.g. errors) you are likely to have on deployment
• Services become disposable and can be “replaced” instead of
“maintained / fixed”.
– Maybe
• It’s more easily replaced than when using traditional architectures
• Requires rigorous contract testing
– Can’t have the “replacement” act any differently than the original (except for the bug
being fixed, of course)
• Requires architecture support for cross-cutting concerns
– Can’t take a lot of time to implement / test
©2015 Derek C. Ashmore, All Rights Reserved 55
Common Mistakes
• Inappropriate Service Boundries
– Services that are not truly loosely coupled
• One change  Multiple services deployed
– Services that make ‘assumptions’ about execution
context
• Deployments cause unintended consequences
• Exposing MS to the browser
– Causes performance issues
– Use Back-ends for Front-ends
– Keep MS traffic behind the firewall and on a fast
network
©2015 Derek C. Ashmore, All Rights Reserved 56
Why Now?
• SOA an old idea
• Virtualization and Cloud advances (e.g. Docker, AWS,
etc.)
– Less dependent on server set-up
• Hardware cheaper than it’s ever been
– We’re not as concerned with the extra process overhead
for MS
• Infrastructure Automation advances
– Additional tooling support(e.g. Chef or Puppet)
– Easier to manage larger numbers of deployments
• Can you think of other possible reasons?
©2015 Derek C. Ashmore, All Rights Reserved 57
Future Directions
• What about Jigsaw?
– Java platform support for modularity
– Coming with Java9 (rumors are 2016)
• Early release is available
– Compared to Microservices
• More limited scaling flexibility
• More limited technical stack
• Chief benefit over MS is reduction in process memory
– Less important as memory is cheaper these days
©2015 Derek C. Ashmore, All Rights Reserved 58
Future Directions
• What about OSGi?
– OSGi supplies modularity to JVM
– Compared to Microservices
• More limited scaling flexibility
• More limited technical stack
• Chief benefit over MS is reduction in process memory
– Less important as memory is cheaper these days
– Low adoption to date
• Jobs oscillate around 0.01% (indeed.com)
• Google Trends shows steady decline
©2015 Derek C. Ashmore, All Rights Reserved 59
Future Directions (continued)
• Trend toward product releases designed to be
deployed as microservices
– Already seeing increase on GitHub
– Takes PAAS to a new level
• Will Microservices become main stream?
– Too early to tell
©2015 Derek C. Ashmore, All Rights Reserved 60
Further Reading
• Microservices reading list
– http://www.mattstine.com/microservices
• Microsoft’s Cloud Design Patterns
– https://msdn.microsoft.com/en-us/library/dn600223.aspx
• Moneta Java microservice example
– https://github.com/Derek-Ashmore/moneta
• This slide deck
– http://www.slideshare.net/derekashmore
©2015 Derek C. Ashmore, All Rights Reserved 61
Questions?
• Derek Ashmore:
– Blog: www.derekashmore.com
– LinkedIn: www.linkedin.com/in/derekashmore
– Twitter: https://twitter.com/Derek_Ashmore
– GitHub: https://github.com/Derek-Ashmore
– Book: http://dvtpress.com/
©2015 Derek C. Ashmore, All Rights Reserved 62
May 14-15, 2015
http://www.chicagocoderconference.com/

More Related Content

Microservices for Java Architects (Madison-Milwaukee, April 28-9, 2015)

  • 1. Microservices for Java Architects Given by Derek C. Ashmore April 28-29 ©2015 Derek C. Ashmore, All Rights Reserved 1
  • 2. Who am I? • Professional Geek since 1987 • Java/J2EE/Java EE since 1999 • Roles include: • Developer • Architect • Project Manager • DBA • System Admin ©2015 Derek C. Ashmore, All Rights Reserved 2
  • 3. Discussion Resources • This slide deck – http://www.slideshare.net/derekashmore • Sample code on my Github – https://github.com/Derek-Ashmore/ • Sample Java Microservice (Moneta) – https://github.com/Derek-Ashmore/moneta • Slide deck has hyper-links! – Don’t bother writing down URLs ©2015 Derek C. Ashmore, All Rights Reserved 3
  • 4. Agenda The “What” and “Why” of microservices Design Considerations and Patterns Packaging Options Cross-cutting concerns When to use microservices Summary / Q&A ©2015 Derek C. Ashmore, All Rights Reserved 4
  • 5. What are Microservices? • No concrete definition • Common microservice traits – Single functional purpose • Most/all changes only impact one service • Not dependent on execution context – “loosely coupled” – Independent process/jvm – Standard Interface (typically Web Service/REST) – Analogy: Stereo system, Linux utilities ©2015 Derek C. Ashmore, All Rights Reserved 5
  • 6. Traditional Java EE Application Architecture • Like a layer cake • Highly cohesive • Defined dependencies • Deployed as one unit (war/ear) • Limited Scalability • Code Size ©2015 Derek C. Ashmore, All Rights Reserved 6
  • 7. What is a Monolith? • Hard to change – QA test cycles are long – Change causes unintended consequences • Hard to onboard new developers • Married to your technical stack • Harder to diagnose bottlenecks and memory issues ©2015 Derek C. Ashmore, All Rights Reserved 7
  • 8. Microservices organize by domain • Silo by business competency • Divide and Conquer • How to divide is the hard part ©2015 Derek C. Ashmore, All Rights Reserved 8
  • 9. Microservices follow the Org Chart • Conway’s Law – Systems copy the structure of the organizations that build them • Why? – Corps need one manager in charge – Reduces inter-group conflict ©2015 Derek C. Ashmore, All Rights Reserved 9
  • 10. Refactoring into Microservices • Large benefits to unified user interface • Databases introduce unwanted coupling between services ©2015 Derek C. Ashmore, All Rights Reserved 10
  • 11. Refactoring further • Databases physically separated • What to do with common data needs? • Service call or • Data copy ©2015 Derek C. Ashmore, All Rights Reserved 11
  • 12. Alternate Database Strategy • Centralized databases are hurdles for MS – i.e. multiple apps use the same db • MS-Central DB compromise – Data items only maintained by *one* service • All other services/apps consider that data item read- only • Helps data corruption investigations ©2015 Derek C. Ashmore, All Rights Reserved 12
  • 13. No Lock-in • Platform agnostic • Fewer dependency conflicts • Still have cross-cutting concerns • “Toll” for first app • Still have support concerns • Others need to be able to support your work 13©2015 Derek C. Ashmore, All Rights Reserved
  • 14. Easier Management / Higher Throughput • Easier to manage large numbers of developers – Concentrate on intelligently drawing service boundaries – Manage/enforce service contracts • Each service team works independently • Team independence leads to higher development throughput ©2015 Derek C. Ashmore, All Rights Reserved 14
  • 15. Isn’t this SOA? • Yes – More or less • No concrete definitions • SOA == dumb endpoints and smart routes – ESB routes using Mule, Camel, etc. – Transformations en route • MS == dumb routes and smart end-points – Simple routes • Usually REST or Soap calls via http(s) • Persistent queue route at it’s most complex • Analogy: Electrical supply for Stereo ©2015 Derek C. Ashmore, All Rights Reserved 15
  • 16. Agenda The “What” and “Why” of microservices Design Considerations and Patterns Packaging Options Cross-cutting concerns When to use microservices Summary / Q&A ©2015 Derek C. Ashmore, All Rights Reserved 16
  • 17. Design considerations • Service Boundaries (gerrymandering) • Service call Failure / Unavailability • Data Integrity • Performance ©2015 Derek C. Ashmore, All Rights Reserved 17
  • 18. Service Boundaries • Core Services – Services responsible for maintaining a specific business area data – Usually named after Nouns • Service is a system of record for a <blank> – Student, Course, Classroom, etc. • Process Services – Services responsible for performing single complex tasks – Usually represents an Action or Process • Service is responsible for processing <blank> – Student applications, Debt collection, etc. – These services rely on core services • Partitioning is an art – Too few  same drawbacks as traditional architecture – Too many  excessive network hops ©2015 Derek C. Ashmore, All Rights Reserved 18
  • 19. Boundary Sanity Check • Verbalize a mission statement in one sentence in business terms – Examples • This service is the system of record for Student information • This service registers students for classes • This service suspends students • This service records student payments • This service produces official transcripts ©2015 Derek C. Ashmore, All Rights Reserved 19
  • 20. Context Independence Check • Does your service have multiple consumers? – Could it? • Could your service execute as easily in batch as online? – If ‘No’, then you’re making context assumptions • Warning Signs – Spending time analyzing service call flow • Your services likely make context assumptions – Agonizing over which service should do a given activity • Maybe you need a new service ©2015 Derek C. Ashmore, All Rights Reserved 20
  • 21. Microservices are not about size ©2015 Derek C. Ashmore, All Rights Reserved 21 ….. Microservices are about having a single business purpose!
  • 22. Designing for Failure • Dependent services could be down – Minimize human intervention – Fail sooner rather than later – Horizontal scaling / clustering is your first line of defense – Coding patterns can help as a backup • Common Patterns: – Retry – Circuit Breaker – Dispatch via Messaging ©2015 Derek C. Ashmore, All Rights Reserved 22
  • 23. Retry Pattern ©2015 Derek C. Ashmore, All Rights Reserved 23 • Best for asynchronous tasks • Limit the number of tries • Use sleep interval between tries • Only addresses temporary outages • Sample Retry Pattern implementation here. • Tooling Support: – Apache CXF supports Retry – Spring Batch RetryTemplate – Apache HttpClient (Example here)
  • 24. Circuit Breaker ©2015 Derek C. Ashmore, All Rights Reserved 24
  • 25. Circuit Breaker (continued) • Objective: Error out sooner – Conserves resources – Automatically “recovers” after a time period • Modeled after home circuit • Works on thresholds – Number of errors required to trip circuit – Amount of time required to attempt retry • Has Hysterix support • Best embedded in interface clients / delegates • More information here. • Sample Circuit implementation here. ©2015 Derek C. Ashmore, All Rights Reserved 25
  • 26. Dispatch via Messaging ©2015 Derek C. Ashmore, All Rights Reserved 26 • Place work instruction on persistent queue • If receivers are down, work stacks in queue • Work throttled by number of receivers • Queue can be JMS or AMQP • Tooling Support: – JMS Api (easy API – many use natively) – Spring JMSTemplate or RabbitTemplate (producer)
  • 27. Designing for Performance • More network traffic – Make services course-grained – User Interfaces need a general manager – Horizontal or Vertical Scaling helps • Common Patterns: – Back-ends for Front-ends (a.k.a. API Gateway) – Dispatch via Messaging – Expiring Cache ©2015 Derek C. Ashmore, All Rights Reserved 27
  • 28. Back-ends for Front-ends ©2015 Derek C. Ashmore, All Rights Reserved 28
  • 29. Back-ends for Front-ends (continued) • Consolidates service calls for the browser – Enhances performance • Open web often not as performant as local LAN • Also known as “API Gateway” • Implications – Don’t expose microservices directly to the browser ©2015 Derek C. Ashmore, All Rights Reserved 29
  • 30. Expiring Cache ©2015 Derek C. Ashmore, All Rights Reserved 30
  • 31. Expiring Cache (continued) • Look up data once and cache it – Evict data from the cache after a defined time period – Sometimes known as “Cache Aside” – Reduces network calls for data – Trades memory for speed – More information here • When to use – Only use with static data – Different clustered nodes “could” have different data for a short time • Tooling Support: – I recommend Google Guava – EHCache, Gemfire, and other tools available ©2015 Derek C. Ashmore, All Rights Reserved 31
  • 32. Designing for Integrity • Services are context independent – Have no knowledge of how/when they are executed • One service == One Transaction – Two-phase commits/rollbacks are a much larger problem • Common Patterns: – Custom Rollback • Write your own reversing transaction ©2015 Derek C. Ashmore, All Rights Reserved 32
  • 33. Custom Rollback ©2015 Derek C. Ashmore, All Rights Reserved 33
  • 34. Custom Rollback (continued) • Reverses a transaction previously posted • Only use this for multi-service transactions – Keeping the transaction within one service is preferred • This pattern is completely custom – No special product support available • More information here ©2015 Derek C. Ashmore, All Rights Reserved 34
  • 35. Special Problems • Versioning – Issues same as more traditional applications – “Breaking” vs. “Non-Breaking” changes • Feature “additions” usually are “Non-Breaking” • Trend away from breaking changes – Versioning is a last result • It greatly increases number of contract tests • Backward compatibility not always obvious to developers • Prefer header versioning to URL versioning • Explicitly error out for versions no longer supported • More info here ©2015 Derek C. Ashmore, All Rights Reserved 35
  • 36. Special Problems (continued) • External Calls to 3rd Party Products – Wrap external interfaces with a separate service – Product upgrades or changes should only affect the interface service – Log all requests/responses ©2015 Derek C. Ashmore, All Rights Reserved 36
  • 37. Common code between services? • Yes, but…. – Version it; services make decision as to when to upgrade – Changes to common code can’t require the deployment of multiple services • That ‘common code’ needs to be its own separate service • Tends *not* to have business logic as that can change and impact multiple services ©2015 Derek C. Ashmore, All Rights Reserved 37
  • 38. Agenda The “What” and “Why” of microservices Design Considerations and Patterns Packaging Options Cross-cutting concerns When to use microservices Summary / Q&A ©2015 Derek C. Ashmore, All Rights Reserved 38
  • 39. Packaging Support • Microservices are deployed as a process – For Java, embedded containers are easy – Spring Boot – Dropwizard • Docker – standardizes the process deployment and environment ©2015 Derek C. Ashmore, All Rights Reserved 39
  • 40. Spring Boot • Packages Java EE application into *one* deployment jar – java –jar myApp.jar • Support for health checks and other admin add ons via ‘Actuator’ add-on • Supports either Jetty or Tomcat • Best for ‘Spring-mvc’ apps – For non-spring apps, it’s swimming upstream • Required artifacts – Maven • spring-boot • spring-boot-starter-jetty (tomcat is available) • spring-boot-starter-actuator (optional – health checks, etc.) – Application class with public static void main() • Configuration coded (usually into the application class) • Will read application.properties (app-specific properties) ©2015 Derek C. Ashmore, All Rights Reserved 40
  • 41. Spring Boot Actuator • Actuator automatically adds endpoints – Health (needs configuration) – Metrics – Mappings – Trace – Env ©2015 Derek C. Ashmore, All Rights Reserved 41
  • 42. Dropwizard • Packages Java EE application into *one* deployment jar – java –jar myApp.jar server myConfig.yaml • Provides file configuration options (yaml format) – Database connection pools – Logging config – Port and other container specs • Provides easy metrics/healthcheck support • Uses Jetty • Required artifacts – Application class (with main()) – Maven: dropwizard-core, maven-shade-plugin ©2015 Derek C. Ashmore, All Rights Reserved 42
  • 43. Docker • Is a “mini VM” • runs a linux kernal • Compare to shipping container • Standard “connections” to outside world • Supported formally by Oracle, Tomcat, Jboss, and many more 43©2015 Derek C. Ashmore, All Rights Reserved Package Once, Run Anywhere!
  • 44. Why Docker? • Docker is Win-Win – Easier for OPS and system administrators • All software looks the same • Standard interface for disk and network resources – Containers can be “linked” • Inherently automated – Easier for developers • Fewer environment difference issues • Less to communicate to OPS / system administrators • Easy to leverage work of others (docker-hub) – If you haven’t tried Docker yet – you should! ©2015 Derek C. Ashmore, All Rights Reserved 44
  • 45. Sample Java/EE Microservice • Moneta – Greek goddess of ‘memory’ – Open source: https://github.com/Derek-Ashmore/moneta • Objective: – Provide a RESTful Web Service interface to a relational database • Feature set: – Provides generic ‘core’ services – Returns Json-formatted data – Supports startRow and maxRows query options – Supports a security call-out – Built-in Dropwizard, Spring Boot, and War-file deployments • Sample contract spec – currently read-only (writes in progress) – /moneta/topics – lists ‘topics’ of information • E.g. – Topic Customer configured – /moneta/topic/customers?startRow=5&maxRows=25 – /moneta/topic/customer/111-222-333 ©2015 Derek C. Ashmore, All Rights Reserved 45
  • 46. Agenda The “What” and “Why” of microservices Design Considerations and Patterns Packaging Options Cross-cutting concerns When to use microservices Summary / Q&A ©2015 Derek C. Ashmore, All Rights Reserved 46
  • 47. Cross-cutting Concerns • Transaction tracking • Security • Contract Testing • Same as traditional applications – Health checks – Logging consolidation – Performance measurement ©2015 Derek C. Ashmore, All Rights Reserved 47
  • 48. Correlation IDs • Provides context for service calls or user actions • Track using HTTP Header • Log it on all messages / error reports • Include it on all service calls or message dispatches • Code sample here • Spring Boot support has been requested 48©2015 Derek C. Ashmore, All Rights Reserved
  • 49. Security ©2015 Derek C. Ashmore, All Rights Reserved 49
  • 50. Security (continued) • Keep User-level security to the UI • Microservice security in layers – Layer 1 – Network routing enforcement • Limit access only to within the firewall • Limit access to specific hosts or subnets – Layer 2 – Use Service Accounts • Similar to database access ©2015 Derek C. Ashmore, All Rights Reserved 50
  • 51. Contract Testing • Critical for MS architectures – Contract changes can break other services – Bulkhead for rogue developers – Makes individual services more disposable • Consumer-based testing • Tooling support – Apache HttpClient – SoapUI – ActiveMQ for JMS (embedded broker) ©2015 Derek C. Ashmore, All Rights Reserved 51
  • 52. Agenda The “What” and “Why” of microservices Design Considerations and Patterns Packaging Options Cross-cutting concerns When to use microservices Summary / Q&A ©2015 Derek C. Ashmore, All Rights Reserved 52
  • 53. When to consider MS • Starting out with MS isn’t recommended unless – Parts of the application will have extremely high volume • Need to scale a portion of the application differently • Note: MS isn’t all or nothing! • Warning signs for app that’s too large – Unintended consequences after release – High technical debt / design rot – Release testing cycles abnormally large – Need to coordinate large numbers of developers for a single code base • Large number == takes more than two pizzas to feed ©2015 Derek C. Ashmore, All Rights Reserved 53
  • 54. Where’s the marketing fluff? • Easier to manage – Maybe • You *must* be good at contract management • You *must* be good at specifying precisely what a microservice needs to do • You *must* ensure that services make no assumptions on how they get invoked • Easier for developers to “understand” applications – No – sorry • It is easier to understand a particular ‘cog’ in the machine (e.g. the function of one service • It is *not* easier to understand how microservices fit together to provide a particular piece of business functionality ©2015 Derek C. Ashmore, All Rights Reserved 54
  • 55. Where’s the marketing fluff? (continued) • Increased Development Throughput – Maybe • Harder for business to ‘test’ a business function for a specific combination of microservices • Developers work on *one* service at a time. • You *must* be good at error detection (unintended consequences) • The more assumptions a service makes about its execution context, the more unintended consequences (e.g. errors) you are likely to have on deployment • Services become disposable and can be “replaced” instead of “maintained / fixed”. – Maybe • It’s more easily replaced than when using traditional architectures • Requires rigorous contract testing – Can’t have the “replacement” act any differently than the original (except for the bug being fixed, of course) • Requires architecture support for cross-cutting concerns – Can’t take a lot of time to implement / test ©2015 Derek C. Ashmore, All Rights Reserved 55
  • 56. Common Mistakes • Inappropriate Service Boundries – Services that are not truly loosely coupled • One change  Multiple services deployed – Services that make ‘assumptions’ about execution context • Deployments cause unintended consequences • Exposing MS to the browser – Causes performance issues – Use Back-ends for Front-ends – Keep MS traffic behind the firewall and on a fast network ©2015 Derek C. Ashmore, All Rights Reserved 56
  • 57. Why Now? • SOA an old idea • Virtualization and Cloud advances (e.g. Docker, AWS, etc.) – Less dependent on server set-up • Hardware cheaper than it’s ever been – We’re not as concerned with the extra process overhead for MS • Infrastructure Automation advances – Additional tooling support(e.g. Chef or Puppet) – Easier to manage larger numbers of deployments • Can you think of other possible reasons? ©2015 Derek C. Ashmore, All Rights Reserved 57
  • 58. Future Directions • What about Jigsaw? – Java platform support for modularity – Coming with Java9 (rumors are 2016) • Early release is available – Compared to Microservices • More limited scaling flexibility • More limited technical stack • Chief benefit over MS is reduction in process memory – Less important as memory is cheaper these days ©2015 Derek C. Ashmore, All Rights Reserved 58
  • 59. Future Directions • What about OSGi? – OSGi supplies modularity to JVM – Compared to Microservices • More limited scaling flexibility • More limited technical stack • Chief benefit over MS is reduction in process memory – Less important as memory is cheaper these days – Low adoption to date • Jobs oscillate around 0.01% (indeed.com) • Google Trends shows steady decline ©2015 Derek C. Ashmore, All Rights Reserved 59
  • 60. Future Directions (continued) • Trend toward product releases designed to be deployed as microservices – Already seeing increase on GitHub – Takes PAAS to a new level • Will Microservices become main stream? – Too early to tell ©2015 Derek C. Ashmore, All Rights Reserved 60
  • 61. Further Reading • Microservices reading list – http://www.mattstine.com/microservices • Microsoft’s Cloud Design Patterns – https://msdn.microsoft.com/en-us/library/dn600223.aspx • Moneta Java microservice example – https://github.com/Derek-Ashmore/moneta • This slide deck – http://www.slideshare.net/derekashmore ©2015 Derek C. Ashmore, All Rights Reserved 61
  • 62. Questions? • Derek Ashmore: – Blog: www.derekashmore.com – LinkedIn: www.linkedin.com/in/derekashmore – Twitter: https://twitter.com/Derek_Ashmore – GitHub: https://github.com/Derek-Ashmore – Book: http://dvtpress.com/ ©2015 Derek C. Ashmore, All Rights Reserved 62 May 14-15, 2015 http://www.chicagocoderconference.com/