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A real-life account
of moving 100%
to a public cloud
Antoine Guy, Principal Infrastructure Architect
Julien Simon, Chief Technology Officer
A word about us
Julien Simon
Last 10 years as VP Eng / CTO
in web startups (Digiplug, Pixmania,
Criteo, Viadeo)
Disclaimer : I joined AWS two weeks ago,
but don’t worry, this won’t be a sales pitch :D
Email: julsimon@amazon.com
Twitter: @julsimon
Antoine Guy
14 years of infrastructure & web ops
Tech lead for Infrastructure and
Operations at Viadeo since 2011
Email: aguy@viadeoteam.com
Twitter: @anto1ne
Viadeo.com
Leading professional social network
Founded in 2005, 10M members in France
What this case study will cover
§  The rationale that led to an all-in move to Amazon Web Services
§  The design options and trade-offs
§  Why we did or didn’t alter parts of our stack
§  The complete automation of our infrastructure
using AWS CloudFormation and continuous integration
Technology stack
§  Service-oriented platform: « Kasper » (Java)
-  CQRS: Command-Query Responsibility Segregation
-  ES: Event Sourcing
-  DDD: Domain Driven Design
§  Web application: « Limbo » (node.js)
§  Mobile applications: iOS and Android
§  Backends: MySQL, Elasticsearch, Hbase, Spark, Hadoop
§  Infrastructure: 15 racks hosted in San Francisco, 250 servers,
limited use of virtualization
Infrastructure challenges
1.  Aging, unsupported hardware
2.  Discrepancy between software agility and infrastructure rigidity
3.  Operating a physical network
4.  Operating a remote data center
5.  Limited disaster recovery capabilities (RTO > 1 day)
4 options
Server
upgrade
Full
virtualization
New
datacenter
Public
cloud
Refresh hardware Solved Solved Solved Solved
Improve agility No change Better No change Better
Manage network No change Worse No change Better
Manage remote DC No change No change No change Gone
Improve DR No change Little better Better Solved
Effort needed Low Medium High Damn!
Learning curve None Low Low Ouch!
Build spend Very high High Very high None
Run spend Little better Better Better Pay as you go
Gut feeling Meh… Too late Wasteful Party on!
Why a public cloud?
§  We want to focus on our real job : building a great service
-  No more issues with hardware vendors, no more licensing hell. Ever!
-  Experimenting, deploying & scaling are just a few clicks away
§  We’re ready and eager for it : Agile and DevOps are Viadeo values
§  We want to measure ROI and optimize cost
§  We’ve been using it for a while now and it just works
Why AWS
§  Already using « cold » services
§  Powerful PaaS technology
accessible in a few clicks
§  Multi region
§  Lots of new features,
constantly improving
“Cloud Infrastructure as a Service”
Gartner Group, May 2015
Play book
§  Key objectives: automation, scalability, safety
§  Continuous integration & delivery everywhere (infra, config, apps)
§  Replace parts of our stack only if the benefits are too good to pass
§  All-in, but no fork lift: move gradually (and be ready to rollback)
§  Plan & build with temporary hybrid run in mind
Pre-flight check
§  Build a thorough report of your infrastructure.
§  Estimate equivalent cost in cloud. Don’t be afraid by initial amount.
§  Evaluate each part for replacement: leave as is, PaaS, SaaS ?
§  Find pain points: technical debt, relevance of moving legacy apps.
§  Define a high-level migration plan (that you won’t follow)
§  Usually : staging, analytics, new projects, critical/legacy, close DC.
§  Expect (and allow) early adopters or emergencies to go first.
Infrastructure as code, for real
§  Versioned, auditable blueprints (developers can contribute)
§  Quick to deploy, repeatable, tested infrastructure
§  Enables CI/CD for infrastructure (just like everything else)
§  Deploy anywhere (for multi-region cloud)
§  Cloud can now be its own DR
AWS CloudFormation
§  Json-based descriptive “language” to create a set of
AWS resources called a stack.
§  Alternative solutions :
Terraform, Ansible, Troposphere
Step 1: automate your infra build
§  $ aws cloudformation validate-template
§  Write your test cases in the language of your choice
(many SDKs available)
§  Use git with a trigger to a CI tool (circle-ci or other)
§  If tests pass : deploy (in your staging environment first)
Step 2: build and CI your images
§  Automate your baking:
1 for each role from your config management
§  Bake automatically with packer or aminator
§  Baked or bootstrapped ?
§  Fully baked for autoscale services
§  Bootstrapped for non critical, fast-changing services
github
circle-ci
jenkins
github
AWS S3
AWS AMIs
packer.io
puppet repo codebase
cloudformation templates
CloudFormation best practices
§  Use AWS CloudFormer as a starting point
§  Reuse as much as possible
§  Nested stack, but not too much, max 1 level (hello UPDATE_ROLLBACK_FAILED).
§  Parameterized template : env, region, name, size, etc..
§  Use stacks to perform green/blue deployments
§  Tag everything!
AWS: lessons learned (1)
§  Plan your VPC network early. Watch ARC403
§  Hybrid run requires good connectivity
→ DirectConnect helps, but watch NET406
§  ELB is level 3 only, with limited options
§  CloudFront performance not great across continents
§  A 2nd CDN may be required, if only for peace of mind
AWS: lessons learned (2)
§  EMR != 24/7 Hadoop cluster
§  EMR in VPC with private DNS is very difficult
§  MySQL: RDS doesn’t allow myISAM
§  Limits: check them, raise them. Same everywhere
§  No more static naming/addressing: use service discovery
§  Make sure everything is multi-AZ and tagged
Tech is only half the work
§  Identify high-level stakeholders and understand THEIR goals
§  Involve your Legal/Finance departments early
-  Budgeting: cost overlap, AWS support, etc.
-  Early termination of legacy infrastructure contracts (there will be blood)
§  Build an A-team (dev, ops, security)
§  Work on awareness and knowledge transfer
Current status
§  Staging environment: done and running
§  Production web traffic served from AWS
§  Infrastructure live in 3 regions (us-east-1, us-west-2, eu-west-1)
§  Multiple inter-connected VPC
§  ≈ 100 AWS EC2 instances (half production, half development)
§  2 AWS Redshift clusters (5 instances each)
Next steps
§  Start moving backend servers to AWS
§  Live Hadoop cluster à EMR
§  Clean-up MySQL stack before we can use RDS
§  Elasticsearch will remain EC2-based for now
§  Optimize: reserved instances, spot instances, auto-scale
Conclusion
§  5 years ago : «Cloud computing? Why?»
§  Now : «NO cloud computing? Why?»
§  Some good reasons, but many outdated ones
§  Cloud computing a fashion? We don’t think so
§  Infrastructure is now digital, like photos, music, movies, money, etc.
§  We’re making the most of it, it’s a great engineering challenge!
aguy@viadeoteam.com
julsimon@amazon.com

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A real-life account of moving 100% to a public cloud

  • 1. A real-life account of moving 100% to a public cloud Antoine Guy, Principal Infrastructure Architect Julien Simon, Chief Technology Officer
  • 2. A word about us Julien Simon Last 10 years as VP Eng / CTO in web startups (Digiplug, Pixmania, Criteo, Viadeo) Disclaimer : I joined AWS two weeks ago, but don’t worry, this won’t be a sales pitch :D Email: julsimon@amazon.com Twitter: @julsimon Antoine Guy 14 years of infrastructure & web ops Tech lead for Infrastructure and Operations at Viadeo since 2011 Email: aguy@viadeoteam.com Twitter: @anto1ne Viadeo.com Leading professional social network Founded in 2005, 10M members in France
  • 3. What this case study will cover §  The rationale that led to an all-in move to Amazon Web Services §  The design options and trade-offs §  Why we did or didn’t alter parts of our stack §  The complete automation of our infrastructure using AWS CloudFormation and continuous integration
  • 4. Technology stack §  Service-oriented platform: « Kasper » (Java) -  CQRS: Command-Query Responsibility Segregation -  ES: Event Sourcing -  DDD: Domain Driven Design §  Web application: « Limbo » (node.js) §  Mobile applications: iOS and Android §  Backends: MySQL, Elasticsearch, Hbase, Spark, Hadoop §  Infrastructure: 15 racks hosted in San Francisco, 250 servers, limited use of virtualization
  • 5. Infrastructure challenges 1.  Aging, unsupported hardware 2.  Discrepancy between software agility and infrastructure rigidity 3.  Operating a physical network 4.  Operating a remote data center 5.  Limited disaster recovery capabilities (RTO > 1 day)
  • 6. 4 options Server upgrade Full virtualization New datacenter Public cloud Refresh hardware Solved Solved Solved Solved Improve agility No change Better No change Better Manage network No change Worse No change Better Manage remote DC No change No change No change Gone Improve DR No change Little better Better Solved Effort needed Low Medium High Damn! Learning curve None Low Low Ouch! Build spend Very high High Very high None Run spend Little better Better Better Pay as you go Gut feeling Meh… Too late Wasteful Party on!
  • 7. Why a public cloud? §  We want to focus on our real job : building a great service -  No more issues with hardware vendors, no more licensing hell. Ever! -  Experimenting, deploying & scaling are just a few clicks away §  We’re ready and eager for it : Agile and DevOps are Viadeo values §  We want to measure ROI and optimize cost §  We’ve been using it for a while now and it just works
  • 8. Why AWS §  Already using « cold » services §  Powerful PaaS technology accessible in a few clicks §  Multi region §  Lots of new features, constantly improving “Cloud Infrastructure as a Service” Gartner Group, May 2015
  • 9. Play book §  Key objectives: automation, scalability, safety §  Continuous integration & delivery everywhere (infra, config, apps) §  Replace parts of our stack only if the benefits are too good to pass §  All-in, but no fork lift: move gradually (and be ready to rollback) §  Plan & build with temporary hybrid run in mind
  • 10. Pre-flight check §  Build a thorough report of your infrastructure. §  Estimate equivalent cost in cloud. Don’t be afraid by initial amount. §  Evaluate each part for replacement: leave as is, PaaS, SaaS ? §  Find pain points: technical debt, relevance of moving legacy apps. §  Define a high-level migration plan (that you won’t follow) §  Usually : staging, analytics, new projects, critical/legacy, close DC. §  Expect (and allow) early adopters or emergencies to go first.
  • 11. Infrastructure as code, for real §  Versioned, auditable blueprints (developers can contribute) §  Quick to deploy, repeatable, tested infrastructure §  Enables CI/CD for infrastructure (just like everything else) §  Deploy anywhere (for multi-region cloud) §  Cloud can now be its own DR
  • 12. AWS CloudFormation §  Json-based descriptive “language” to create a set of AWS resources called a stack. §  Alternative solutions : Terraform, Ansible, Troposphere
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  • 15. Step 1: automate your infra build §  $ aws cloudformation validate-template §  Write your test cases in the language of your choice (many SDKs available) §  Use git with a trigger to a CI tool (circle-ci or other) §  If tests pass : deploy (in your staging environment first)
  • 16. Step 2: build and CI your images §  Automate your baking: 1 for each role from your config management §  Bake automatically with packer or aminator §  Baked or bootstrapped ? §  Fully baked for autoscale services §  Bootstrapped for non critical, fast-changing services
  • 18. CloudFormation best practices §  Use AWS CloudFormer as a starting point §  Reuse as much as possible §  Nested stack, but not too much, max 1 level (hello UPDATE_ROLLBACK_FAILED). §  Parameterized template : env, region, name, size, etc.. §  Use stacks to perform green/blue deployments §  Tag everything!
  • 19. AWS: lessons learned (1) §  Plan your VPC network early. Watch ARC403 §  Hybrid run requires good connectivity → DirectConnect helps, but watch NET406 §  ELB is level 3 only, with limited options §  CloudFront performance not great across continents §  A 2nd CDN may be required, if only for peace of mind
  • 20. AWS: lessons learned (2) §  EMR != 24/7 Hadoop cluster §  EMR in VPC with private DNS is very difficult §  MySQL: RDS doesn’t allow myISAM §  Limits: check them, raise them. Same everywhere §  No more static naming/addressing: use service discovery §  Make sure everything is multi-AZ and tagged
  • 21. Tech is only half the work §  Identify high-level stakeholders and understand THEIR goals §  Involve your Legal/Finance departments early -  Budgeting: cost overlap, AWS support, etc. -  Early termination of legacy infrastructure contracts (there will be blood) §  Build an A-team (dev, ops, security) §  Work on awareness and knowledge transfer
  • 22. Current status §  Staging environment: done and running §  Production web traffic served from AWS §  Infrastructure live in 3 regions (us-east-1, us-west-2, eu-west-1) §  Multiple inter-connected VPC §  ≈ 100 AWS EC2 instances (half production, half development) §  2 AWS Redshift clusters (5 instances each)
  • 23. Next steps §  Start moving backend servers to AWS §  Live Hadoop cluster à EMR §  Clean-up MySQL stack before we can use RDS §  Elasticsearch will remain EC2-based for now §  Optimize: reserved instances, spot instances, auto-scale
  • 24. Conclusion §  5 years ago : «Cloud computing? Why?» §  Now : «NO cloud computing? Why?» §  Some good reasons, but many outdated ones §  Cloud computing a fashion? We don’t think so §  Infrastructure is now digital, like photos, music, movies, money, etc. §  We’re making the most of it, it’s a great engineering challenge!