Devoxx 2016 Using Jenkins, Gerrit and Spark for Continuous Delivery Analytics

Jun 24, 2016Download as PPTX, PDF2 likes1,266 views

Our journey and experience in dealing with the collection/analysis of Continuous Delivery log events using Gerrit Code Review, Jenkins with Apache Flume, ElasticSearch, Kibana and Spark

@gitenterprise#DevoxxPL
Platinum Sponsors:
Speed-up your Continuous Delivery
with BigData
Luca Milanesio
GerritForge

@gitenterprise#DevoxxPL
• Founded in the UK
• HQ in London, Offices in
the UK and Italy
• Committed to
OpenSource
About GerritForge

@gitenterprise#DevoxxPL
• Co-founder and
Director of GerritForge
• over 20 years in Agile
Development and ALM
• Contributor to many
OpenSource projects
• Mind and hands of
@gitenterprise and
@gerritreview
About Luca Milanesio

@gitenterprise#DevoxxPL
NOT a lecture on Continuous Delivery
NOT a lecture on Code Review
NOT a lecture on BigData
What NOT to expect?

@gitenterprise#DevoxxPL
SHOW
a scenario of Continuous Delivery

@gitenterprise#DevoxxPL
LEARN
together about the problems

@gitenterprise#DevoxxPL
EXPERIMENT
my approach leveraging BigData

@gitenterprise#DevoxxPL
DISCUSS
and evolve the approach together

@gitenterprise#DevoxxPL
Continuous Delivery Pipeline
Push Build
Unit Tests
Push Build
Unit Tests
Automated
Tests
Push Build
Unit Tests
Automated
Tests
Beta Users
Tests
User's feedback Publish to all Users
Failed
Failed

@gitenterprise#DevoxxPL
Code Review & CD Validation
A1
refs/for/master
master
C2 C2*
A1 C2 (local)
master
C2*
push
Verified: -1
(build failed)
push
Verified: +1
(build OK)
Reviewed: +2
CI Build: OK
C2*
CI Build: OK
amend

@gitenterprise#DevoxxPL
Git/Gerrit
(Code Review)
Jenkins
(Continuous
Integration & Delivery)
Docker
(Release and Service
Packaging)
Mesos &
Marathon
(Delivery and Resource
Manangement)
Components

@gitenterprise#DevoxxPL
DEMO
See the pipeline in action

@gitenterprise#DevoxxPL
We use micro-services
• 100+ Components
• 200+ Repositories
• 300+ People and 100,000+ of review comments
• Cross-components [implicit] dependencies
• Lots of build chains
• 10,000+ of builds
Now feel the pain :-(

@gitenterprise#DevoxxPL
"It was working until 5
mins ago … then
someone changed
something"
 Rings any
bell?
Problem #1 : Ripple effect

@gitenterprise#DevoxxPL
In order to deliver Feature ABC
I NEED
Ver. N of Service-A with
Ver. M of Service-B and
Ver. K of Service C
Problem #2 : Dependencies

@gitenterprise#DevoxxPL
"Where can I find an environment
to
run ALL my Micro-Services
integration tests?"
Problem #3 : Resources

@gitenterprise#DevoxxPL
Release small changes is GOOD
Release often every change is GOOD
BUT
How long it takes the "Big Picture" and End-to-End?
Where is my bottleneck?
Problem #4 : Cycle time

@gitenterprise#DevoxxPL
Micro-Services are
distributed
Builds are distributed
Deployments are
distributed
 Tackling THIS
have you ever felt
like drowning in
your logs?
Problem #5 : Lots of logs

@gitenterprise#DevoxxPL
Problems #1 + #2 + #3 + #4 + #5 =
lead to your daily
Micro-Services mental meltdown
Problem #6 : all together

@gitenterprise#DevoxxPL
• Collect all review events
• Collect all logs
• Channel them to a
central store
• Crunch and Crunch
continuously
• Never delete
• Process, inspect and
learn
BigData to the rescue

@gitenterprise#DevoxxPL
DEMO
Continuous Delivery Analytics

@gitenterprise#DevoxxPL
•Problem #1 – Ripple effect?
•Problem #2 – Dependencies?
•Problem #3 – Resources?
•Problem #4 – Cycle Time?
•Problem #5 – Logs aggregation?
•Problem #6 – Avoid mental meltdown?
Did we solve the problems?

@gitenterprise#DevoxxPL
• Collect more data (System, JVM, Review
scores)
• Real-time statistics
• Events correlation
• Feedback loop to Code-Review
• Production data harvest
• More?
Future directions

@gitenterprise#DevoxxPL
• My blog
www.gitenterprise.me
• Gerrit Code Review
www.gerritcodereview.co
m
• Jenkins
www.jenkins.io
• RabbitMQ
rabbitmq.com
• Apache Flume
flume.apache.org
• Hadoop HDFS
hadoop.apache.org
• Apache Spark
spark.apache.org
• Kibana
github.com/elastic/kibana
Resources

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1. @gitenterprise#DevoxxPL Platinum Sponsors: Speed-up your Continuous Delivery with BigData Luca Milanesio GerritForge

2. @gitenterprise#DevoxxPL • Founded in the UK • HQ in London, Offices in the UK and Italy • Committed to OpenSource About GerritForge

3. @gitenterprise#DevoxxPL • Co-founder and Director of GerritForge • over 20 years in Agile Development and ALM • Contributor to many OpenSource projects • Mind and hands of @gitenterprise and @gerritreview About Luca Milanesio

4. @gitenterprise#DevoxxPL NOT a lecture on Continuous Delivery NOT a lecture on Code Review NOT a lecture on BigData What NOT to expect?

5. @gitenterprise#DevoxxPL SO WHAT? #!@$!

6. @gitenterprise#DevoxxPL SHOW a scenario of Continuous Delivery

7. @gitenterprise#DevoxxPL LEARN together about the problems

8. @gitenterprise#DevoxxPL EXPERIMENT my approach leveraging BigData

9. @gitenterprise#DevoxxPL DISCUSS and evolve the approach together

10. @gitenterprise#DevoxxPL Continuous Delivery Pipeline Push Build Unit Tests Push Build Unit Tests Automated Tests Push Build Unit Tests Automated Tests Beta Users Tests User's feedback Publish to all Users Failed Failed

11. @gitenterprise#DevoxxPL Code Review & CD Validation A1 refs/for/master master C2 C2* A1 C2 (local) master C2* push Verified: -1 (build failed) push Verified: +1 (build OK) Reviewed: +2 CI Build: OK C2* CI Build: OK amend

12. @gitenterprise#DevoxxPL Git/Gerrit (Code Review) Jenkins (Continuous Integration & Delivery) Docker (Release and Service Packaging) Mesos & Marathon (Delivery and Resource Manangement) Components

13. @gitenterprise#DevoxxPL DEMO See the pipeline in action

14. @gitenterprise#DevoxxPL We use micro-services • 100+ Components • 200+ Repositories • 300+ People and 100,000+ of review comments • Cross-components [implicit] dependencies • Lots of build chains • 10,000+ of builds Now feel the pain :-(

15. @gitenterprise#DevoxxPL "It was working until 5 mins ago … then someone changed something"  Rings any bell? Problem #1 : Ripple effect

16. @gitenterprise#DevoxxPL In order to deliver Feature ABC I NEED Ver. N of Service-A with Ver. M of Service-B and Ver. K of Service C Problem #2 : Dependencies

17. @gitenterprise#DevoxxPL "Where can I find an environment to run ALL my Micro-Services integration tests?" Problem #3 : Resources

18. @gitenterprise#DevoxxPL Release small changes is GOOD Release often every change is GOOD BUT How long it takes the "Big Picture" and End-to-End? Where is my bottleneck? Problem #4 : Cycle time

19. @gitenterprise#DevoxxPL Micro-Services are distributed Builds are distributed Deployments are distributed  Tackling THIS have you ever felt like drowning in your logs? Problem #5 : Lots of logs

20. @gitenterprise#DevoxxPL Problems #1 + #2 + #3 + #4 + #5 = lead to your daily Micro-Services mental meltdown Problem #6 : all together

21. @gitenterprise#DevoxxPL • Collect all review events • Collect all logs • Channel them to a central store • Crunch and Crunch continuously • Never delete • Process, inspect and learn BigData to the rescue

22. @gitenterprise#DevoxxPL DEMO Continuous Delivery Analytics

23. @gitenterprise#DevoxxPL •Problem #1 – Ripple effect? •Problem #2 – Dependencies? •Problem #3 – Resources? •Problem #4 – Cycle Time? •Problem #5 – Logs aggregation? •Problem #6 – Avoid mental meltdown? Did we solve the problems?

24. @gitenterprise#DevoxxPL • Collect more data (System, JVM, Review scores) • Real-time statistics • Events correlation • Feedback loop to Code-Review • Production data harvest • More? Future directions

25. @gitenterprise#DevoxxPL • My blog www.gitenterprise.me • Gerrit Code Review www.gerritcodereview.co m • Jenkins www.jenkins.io • RabbitMQ rabbitmq.com • Apache Flume flume.apache.org • Hadoop HDFS hadoop.apache.org • Apache Spark spark.apache.org • Kibana github.com/elastic/kibana Resources

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