How Small Can Java Microservices Be?

If you compromise you can make Java Microservices small - using technologies like Serverless (Amazon Lambda), OSGi or Java EE Application Server.

Transcript

1. How Small Can Java Microservices Be? Eberhard Wolff Fellow, innoQ @ewolff
2. http://continuous-delivery-buch.de/
3. http://microservices-buch.de/ http://microservices-book.com/
4. http://microservices-book.com/primer.html FREE!!!!
5. Microservice Definition
6. Microservices: Definition > No consistent definition > Microservices are modules > Independent deployment units > E.g. processes, Docker container > Microservice owned by one team
7. Microservices: Definition Server / Container Server / Container Micro Service Micro Service
8. Components Collaborate Micro Service Micro Service Link Data Replication REST Messaging
9. Online Shop Order Catalog Search Billing Customer HTML / HTTP
10. Online Shop Elasticsearch Spring Batch Oracle Spring MVC MongoDB Order Catalog Search Billing
11. Microservices Stack
12. Docker > Linux (soon Windows) > Shared kernel > Filesystem just stores diffs > Extremely light weight > Can run in cluster (e.g. Kubernetes, Mesosphere etc)
13. Spring Boot > One build file > One Java class > = REST service + embedded Tomcat > Deploy: One Java Fat JARs > Alternatives: Dropwizard, Wildfly Swarm… > https://github.com/ewolff/spring-boot-demos
14. Microservice = Fat JAR + Java EE programming model possible!
15. Ideal size of a Microservice Team size Modularization Infrastructure Distributed Communication No absolute value! Replaceability Microservice Size
16. Nanoservices
17. Nanoservices?
18. Nanoservices? #SRSLY?
19. #SRSLY? YES!
20. Nanoservices!= Microservices
21. Nanoservices< Microservices
22. Ideal size of a Microservice Team size Modularization Infrastructure Distributed Communication No absolute value! Replaceability Microservice Size
23. Microservices= Independent Deployment Units
24. Nanoservices= Independent Deployment Units
25. Nanoservices use more light weight technologies
26. Serverless
27. Serverless > Deploy a function > Pay per call > Example: Amazon Lambda > Similar: Google Cloud Functions > Azure Functions > IBM OpenWhisk (Open Source)
28. Serverless vs. PaaS
29. Amazon Lambda > Service in the Amazon Cloud > Allows you to install individual functions > Java, JavaScript, Python
30. Amazon Lambda vs. PaaS > Commercial model: Pay-per-call / RAM / processing time > Fine grained (e.g. database trigger, HTTP GET) > First million requests / 400.000 DB seconds FREE! > Can edit Python / JavaScript functions in the browser
31. Lambda Function Command Line S3 Event Kinesis Stream DynamoDB SNS: Simple Notification Service SES: Simple EMail Service Cognito CloudWatch CloudFormation API Gateway (e.g. REST) Scheduled Events
32. Amazon Lambda adds e.g. trigger to DynamoDB.
33. Amazon Lambda + API Gateway = REST services.
34. public class Main { public String myHandler(int myCount, Context context) { LambdaLogger logger = context.getLogger(); logger.log("received : " + myCount); return "Hi"+myCount; } }
35. Deploy
36. Deploy
37. Deploy
38. Deploy
39. Deploy
40. Deploy
41. Deploy
42. Invoke
43. Invoke
44. Invoke
45. Invoke
46. Invoke
47. Invoke
50. Amazon Lambda > Can add any other Amazon Service to complete the system > i.e. Beanstalk PaaS, EC2 IaaS … > Or databased (DynamoDB, RDS...)
51. Send out slides via email!
52. Lambda Function Simple Email Service SMTP Simple Email Service Event calls Audience Cost: SES 0,10$ per 1000 EMails Lambda free
53. > Developed in Python > In the browser > ”Save & test” > Includes monitoring & alarm > Setting up SES was the hardest part…
55. OSGi
56. OSGi: Bundles > Partition system into – "bundles” > Bundles can be installed, started, stopped, uninstalled and updated > ...at runtime
57. OSGi: Code Sharing > Bundles can export and import packages > Updating code requires other bundles to start fresh
58. OSGi: Services > Bundles can publish services… dynamically! > Service = Java Object > Service Registry allows other bundles to consume services > Services come and go at runtime > Quite easy with OSGi Blueprints or OSGi Declarative Services
59. Calling Bundle Bundle (interface code) Bundle (implementation and service) Service Package (interface code) Package (interface code) Update to service in running application
60. (Almost) Independent Deployment Units
61. Java EE
62. Java EE > JARs e.g. for EJBs > WARs e.g. for web application > EARs for JARs and WARs > Completely separated code > …unlike OSGi
63. Java EE > Relevant: Deployment model > i.e. application server > Not programming model
64. Java EE Nanoservices? > Local calls not possible > No shared code e.g. for interfaces
65. Tomcat Java EE Server order.war customer.war catalog.war Customer
66. (Almost) Independent Deployment Units
67. Comparison
68. Independent Deployment > THE feature of Micro-/Nanoservices > Simplifies to put new features in production > Docker Fat JAR: ++ > Amazon Lambda: ++ > OSGi: + Restart the whole JVM? > Java EE: + Restart the whole JVM?
69. Benefits of Nanoservices
70. Effort per Service > How hard is it to create another service? > All: Create another project/JAR/WAR > Amazon Lambda: ++ > OSGi: ++ > Java EE: ++ > Docker Fat JAR : - (Docker container etc)
71. Cost per Service > Hardware, software cost > Amazon Lambda: ++ > OSGi: ++ > Java EE: ++ > Docker Fat JAR: -- (need Docker container etc, separat JVM Heap)
72. Local Communcation > Call without network stack > Docker Fat JAR : -- > Amazon Lambda: -- > OSGi: ++ > Java EE: --
73. Challenges of Nanoservices
74. Independent Scaling > Start more instances of a single service > Docker Fat JAR: ++ > Amazon Lambda: ++ > OSGi: ? > Java EE: --
75. Isolation > CPU / Memory consumption/crash influences other services > Docker Fat JAR: ++ > Amazon Lambda: ++ > OSGi: -- > Java EE: --
76. Resilience & Isolation > Resilience: System can handle crash of other services > Needs isolation > Problem for OSGi/Java EE
77. Technology Freedom > Using different technologies > Docker Fat JAR: ++ (whatever) > Amazon Lambda: + (Java, JavaScript, Python) > OSGi: -- (Java) > Java EE: -- (Java)
78. Conclusion
79. Nanoservices!= Microservices
80. Nanoservices< Microservices
81. Conclusion > Nanoservice technologies compromise > …to allow smaller services > …to allow local communication > OSGi and Java EE deployment model don’t fully support independent deployment > …might therefore not be “true” Nanoservices
82. Conclusion > OSGi and Java EE weak concerning > Independent scaling > Isolation > Technology freedom > Amazon Lambda a lot stronger
83. Might also consider… > Vert.x: polyglot, distributed, module concept > Erlang: support update to running system and processes in other languages
84. Thank You! @ewolff http://microservices-buch.de/ http://microservices-book.com/primer.html http://aws.amazon.com/lambda/getting-started/ http://www.heise.de/developer/artikel/ Nanoservices-kleiner-als-Microservices-3038541.html