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Development andQA
dilemmas in DevOps
Matteo Emili
twitter.com/MattVSTS || mattvsts.blogspot.com
Who am I?
 Visual Studio and DevelopmentTechnologies MVP (ALM)
 Professional Scrum Master I
 Systems EngineeringAdvisor @ Dell Software
 Taunton Developers Meetup
 London Microsoft DevOps Meetup
 Other communities overseas
CDCycle
Monitor
Operate
Workingsoftware
inproduction
Valuerealization
Are we all ready for it?
Sometimes
things are the
other way
round…
 The first thing to do should be creating a MinimumViable Product,
including the infrastructure
 The Pipeline must work from the very first moment
 Dev andTest environments should be disposable, infrastructure
must be idempotent
 Testing can happen in Production
It is a shocking
change for
some
 “I was frightened by not feeling a safety net”
 “Does it actually work?”
 “The feeling is not good at first”
 “We don’t want to be accountable for all of this”
 “It can’t work!”
 “How do we know what to build?”
 “It is hard to get the grip with these tools”
Prerequisite
The team must buy into DevOps!
Scenario #0
Use your
infrastructure!
 Leverage on Infrastructure As Code
(DSC,Azure RM, Amazon
CloudFormations) to remove
friction when factoring the
infrastructure in
 Spend time on defining what you
need to have, and the provider
(Azure, AWS, local deployment
service) will deploy that for you
 Idempotent and resilient – if there
is something wrong, redeploy
 Less friction here means no barrier
between Dev and Ops, a
fundamental (and time saving)
change!
Scenario #1
Database
schema
change
 You must bring a database schema change in production
 Cloud or mission critical web service
 Transparent for your users, regardless of public-facing or internal
change
 No downtime for migration – it must work!
WinOps Conf 2016 - Matteo Emili - Development and QA Dilemmas in DevOps
The typical
approach
 Develop everything in a separate environment
 Countless hours of tests
 Big-bang migration then new feature for all the users
 Big release date, people freak out
 …lots of fingers crossed!
Shhh! Don’t
make noise!
 There is no such approach in DevOps
 Each big change must be split in smaller changes
 They are often invisible to the user
 Silent deployments can happen across multiple sprints
 If something breaks, rollback
 Start using your MVP straight away!
Demo
Infrastructure as Code
Database schema change
Scenario #2
Feature Flags
 Championed by Martin Fowler, Feature Flags are around since at
least 2009
 Pretty much all services nowadays use them
 Flickr,Amazon, Microsoft, Facebook, Google, Netflix …
 They are used to enable or disable certain areas of your
application to your users
“…wait. Does
it mean
Microservices
and all the new
stuff around?”
 No, it doesn’t!
 You can use Feature Flags with all the architectures
 It is a practice, not a product
 It ties in with the previous scenario and makes testing easier
How?
 Practically speaking, it is about a Configuration Database coupled
with Identifiers
 The Configuration Database can be a csv file, XML file, key-value
model, a database (!)
 Identifiers are areas you will easily split your applications into
 They often go well together with Feature/Epics or even User Stories
 Countless OSS libraries
It doesn’t
come for free
 It is expensive (in terms of time, and sometimes refactoring) to
build it up from scratch in an existing application
 Not just enable/disable – logging, kill switch, selective adoption,
rollouts are all things to implement that takes time
 OSS libraries help, as there is a choice for each platform, but there
is still an implementation cost to keep in mind
Demo
Feature Flags with LaunchDarkly
Scenario #3
A/BTesting,
MVT
Testing…is it
about testing?
 Little changes for QA in DevOps, except for automation
 What is really new are practices ofTesting in Production -
extremely common especially withWeb Applications
 You deploy version B of your A application (or a permutation of
possibilities), direct a percentage of the traffic towards it and
compare the adoption results
 Implementing them is extremely easy, getting value out of them is
hard!
A bit of Lean…
 "There is no such thing as a free lunch“ – technology alone is not
going to deliver a successful product
 My take is to adopt the Build-Measure-Learn loop
 Start with a MinimumViable Product and measure its usage with
appropriate metrics
 Build on top of it, discard what doesn’t work
Getting
visibility on
what is
actually
happening
 Is my application performing as expected?
 What about availability?
 Are my users having a good experience?
 Above all, you need better, faster and more direct feedback
Learn from
your users and
improve your
product
 In the Build-Measure-Learn loop the Measure stage is the most
important one
 Metrics will tell if you are going in the right direction, so it is critical
to ‘get it right’
 Extend your product to include what really matters
 Get insights on your users before they react
 Proactively understand potential problems
 You can analyse your data and understand if your application is
behaving as expected
It is different
from logging
 We are not talking about plain application logs
 What user actions are meaningful to your business goals?
 Is the telemetry data answering this question?
 Is there any bottlenecks which is penalising the business?
 You need to have visibility on user events
 Actionable insights are mapped into behaviours (what content is
used, not how)
 E.g.: when a user enters in a certain page/area, log on/off,
Favourites, social stats, errors…
You won’t do
that from
scratch
 It is too expensive to build something from scratch
 You need to use an analytics provider
 The development experience must be cross-platform, unobtrusive
at first and then customisable with an SDK
 Easily add custom telemetry wherever needed
Demo
Learn from your users
So?
 These scenarios are very common when approaching DevOps
 Remember: DevOps is not the silver bullet, teams must buy-in into
the process
 Collaboration is key to success
 Use data to take decisions
 Don’t be afraid!
Ad

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WinOps Conf 2016 - Matteo Emili - Development and QA Dilemmas in DevOps

  • 1. Development andQA dilemmas in DevOps Matteo Emili twitter.com/MattVSTS || mattvsts.blogspot.com
  • 2. Who am I?  Visual Studio and DevelopmentTechnologies MVP (ALM)  Professional Scrum Master I  Systems EngineeringAdvisor @ Dell Software  Taunton Developers Meetup  London Microsoft DevOps Meetup  Other communities overseas
  • 4. Are we all ready for it?
  • 5. Sometimes things are the other way round…  The first thing to do should be creating a MinimumViable Product, including the infrastructure  The Pipeline must work from the very first moment  Dev andTest environments should be disposable, infrastructure must be idempotent  Testing can happen in Production
  • 6. It is a shocking change for some  “I was frightened by not feeling a safety net”  “Does it actually work?”  “The feeling is not good at first”  “We don’t want to be accountable for all of this”  “It can’t work!”  “How do we know what to build?”  “It is hard to get the grip with these tools”
  • 7. Prerequisite The team must buy into DevOps!
  • 8. Scenario #0 Use your infrastructure!  Leverage on Infrastructure As Code (DSC,Azure RM, Amazon CloudFormations) to remove friction when factoring the infrastructure in  Spend time on defining what you need to have, and the provider (Azure, AWS, local deployment service) will deploy that for you  Idempotent and resilient – if there is something wrong, redeploy  Less friction here means no barrier between Dev and Ops, a fundamental (and time saving) change!
  • 9. Scenario #1 Database schema change  You must bring a database schema change in production  Cloud or mission critical web service  Transparent for your users, regardless of public-facing or internal change  No downtime for migration – it must work!
  • 11. The typical approach  Develop everything in a separate environment  Countless hours of tests  Big-bang migration then new feature for all the users  Big release date, people freak out  …lots of fingers crossed!
  • 12. Shhh! Don’t make noise!  There is no such approach in DevOps  Each big change must be split in smaller changes  They are often invisible to the user  Silent deployments can happen across multiple sprints  If something breaks, rollback  Start using your MVP straight away!
  • 14. Scenario #2 Feature Flags  Championed by Martin Fowler, Feature Flags are around since at least 2009  Pretty much all services nowadays use them  Flickr,Amazon, Microsoft, Facebook, Google, Netflix …  They are used to enable or disable certain areas of your application to your users
  • 15. “…wait. Does it mean Microservices and all the new stuff around?”  No, it doesn’t!  You can use Feature Flags with all the architectures  It is a practice, not a product  It ties in with the previous scenario and makes testing easier
  • 16. How?  Practically speaking, it is about a Configuration Database coupled with Identifiers  The Configuration Database can be a csv file, XML file, key-value model, a database (!)  Identifiers are areas you will easily split your applications into  They often go well together with Feature/Epics or even User Stories  Countless OSS libraries
  • 17. It doesn’t come for free  It is expensive (in terms of time, and sometimes refactoring) to build it up from scratch in an existing application  Not just enable/disable – logging, kill switch, selective adoption, rollouts are all things to implement that takes time  OSS libraries help, as there is a choice for each platform, but there is still an implementation cost to keep in mind
  • 18. Demo Feature Flags with LaunchDarkly
  • 19. Scenario #3 A/BTesting, MVT Testing…is it about testing?  Little changes for QA in DevOps, except for automation  What is really new are practices ofTesting in Production - extremely common especially withWeb Applications  You deploy version B of your A application (or a permutation of possibilities), direct a percentage of the traffic towards it and compare the adoption results  Implementing them is extremely easy, getting value out of them is hard!
  • 20. A bit of Lean…  "There is no such thing as a free lunch“ – technology alone is not going to deliver a successful product  My take is to adopt the Build-Measure-Learn loop  Start with a MinimumViable Product and measure its usage with appropriate metrics  Build on top of it, discard what doesn’t work
  • 21. Getting visibility on what is actually happening  Is my application performing as expected?  What about availability?  Are my users having a good experience?  Above all, you need better, faster and more direct feedback
  • 22. Learn from your users and improve your product  In the Build-Measure-Learn loop the Measure stage is the most important one  Metrics will tell if you are going in the right direction, so it is critical to ‘get it right’  Extend your product to include what really matters  Get insights on your users before they react  Proactively understand potential problems  You can analyse your data and understand if your application is behaving as expected
  • 23. It is different from logging  We are not talking about plain application logs  What user actions are meaningful to your business goals?  Is the telemetry data answering this question?  Is there any bottlenecks which is penalising the business?  You need to have visibility on user events  Actionable insights are mapped into behaviours (what content is used, not how)  E.g.: when a user enters in a certain page/area, log on/off, Favourites, social stats, errors…
  • 24. You won’t do that from scratch  It is too expensive to build something from scratch  You need to use an analytics provider  The development experience must be cross-platform, unobtrusive at first and then customisable with an SDK  Easily add custom telemetry wherever needed
  • 26. So?  These scenarios are very common when approaching DevOps  Remember: DevOps is not the silver bullet, teams must buy-in into the process  Collaboration is key to success  Use data to take decisions  Don’t be afraid!
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