Scaling on AWS for the First 10 Million Users

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Cloud computing gives you a number of advantages, such as being able to scale your application on demand. As a new business looking to use the cloud, you inevitably ask yourself, "Where do I start?" …

Cloud computing gives you a number of advantages, such as being able to scale your application on demand. As a new business looking to use the cloud, you inevitably ask yourself, "Where do I start?" Join us in this session to understand best practices for scaling your resources from zero to millions of users. We will show you how to best combine different AWS services, make smarter decisions for architecting your application, and best practices for scaling your infrastructure in the cloud.

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  • 1. © 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.© 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc. Scaling on AWS for the First 10 Million Users Mohan Vedula, Enterprise Solutions Architecture Brett Francis, Enterprise Solutions Architecture March 26, 2014
  • 2. Scaling on AWS for the First 10 Million Users • US: – Brett Francis – brettf@amazon.com – Mohan Vedula – mohanv@amazon.com • YOU: Here to learn more about scaling infrastructure on AWS • TODAY: about best practices and things to think about when building for large scale
  • 3. Scaling to 10M Users: A Story in Four Parts • Intro and Initial Steps • Building Blocks • Tools and Monitoring • 10M Users and Beyond
  • 4. So how do we scale?
  • 5. a lot of things to read
  • 6. not where we want to start a lot of things to read
  • 7. us today
  • 8. Auto Scaling is a tool and a destination. It’s not the single thing that fixes everything.
  • 9. What do we need first?
  • 10. Some basics…
  • 11. Regions US-WEST (Oregon) EU-WEST (Ireland) ASIA PAC (Tokyo) US-WEST (N. California) SOUTH AMERICA (Sao Paulo) US-EAST (Virginia) AWS GovCloud (US) ASIA PAC (Sydney) ASIA PAC (Singapore) CHINA (Beijing)
  • 12. Availability Zones US-WEST (Oregon) EU-WEST (Ireland) ASIA PAC (Tokyo) US-WEST (N. California) SOUTH AMERICA (Sao Paulo) US-EAST (Virginia) AWS GovCloud (US) ASIA PAC (Sydney) ASIA PAC (Singapore) CHINA (Beijing)
  • 13. Edge Locations
  • 14. • $7B+ retail business • 8,000+ employees • A whole lot of servers Every day, AWS adds enough server capacity to power that entire $7B enterprise 2004 2014
  • 15. Compute Storage & Content Delivery AWS Global Infrastructure Database App Services Deployment & Administration Networking
  • 16. Compute Storage & Content Delivery AWS Global Infrastructure Database App Services Deployment & Administration Networking Amazon CloudSearch Amazon SQS Amazon SNS Amazon Elastic Transcoder Amazon SWF Amazon SES Amazon DynamoDB Amazon RDS Amazon ElastiCache Amazon RedShift AWS Storage Gateway Amazon S3 Amazon Glacier Amazon CloudFrontAmazon EC2 Amazon EMR Amazon VPC Amazon Route 53 AWS Direct Connect Amazon Kinesis Amazon CloudWatch AWS IAM AWS CloudFormation Amazon Elastic Beanstalk AWS Data Pipeline AWS OpsWorks AWS CloudTrail
  • 17. So let’s start from day one, user one ( you )
  • 18. Day One, User One: • A single EC2 instance – With a full stack on this host • Web app • Database • Management • etc. • A single Elastic IP address • Amazon Route 53 for DNS EC2 instance Elastic IP address Amazon Route 53 User
  • 19. “We’re gonna need a bigger box” • Simplest approach • Can now leverage PIOPs • High I/O instances • High memory instances • High CPU instances • High storage instances • Easy to change instance sizes • Will hit an endpoint eventually m3.xlarge m1.small i2.4xlarge
  • 20. “We’re gonna need a bigger box” m3.xlarge m1.small i2.4xlarge • Simplest approach • Can now leverage PIOPs • High I/O instances • High memory instances • High CPU instances • High storage instances • Easy to change instance sizes • Will hit an endpoint eventually
  • 21. Day One, User One: • We could potentially get to a few hundred to a few thousand depending on application complexity and traffic • No failover • No redundancy • Too many eggs in one basket EC2 instance Elastic IP address Amazon Route 53 User
  • 22. Day One, User One: • We could potentially get to a few hundred to a few thousand depending on application complexity and traffic • No failover • No redundancy • Too many eggs in one basket EC2 instance Elastic IP address Amazon Route 53 User
  • 23. Day Two, User >1: First, let’s separate out our single host into more than one: • Web • Database – Make use of a database service? Web instance Database instance Elastic IP address Amazon Route 53 User
  • 24. Self-Managed Fully-Managed Database server on Amazon EC2 Your choice of database running on Amazon EC2 Bring Your Own License (BYOL) Amazon DynamoDB Managed NoSQL database service using SSD storage Seamless scalability Zero administration Amazon RDS Microsoft SQL, Oracle, MySQL or PostgreSQL as a managed service Flexible licensing BYOL or License Included Amazon Redshift Massively parallel, petabyte-scale, data warehouse service Fast, powerful and easy to scale Database Options
  • 25. Scaling to 10M Users: A Story in Four Parts • Intro and Initial Steps • Building Blocks • Tools and Monitoring • 10M Users and Beyond
  • 26. But how do I choose the DB technology I need? SQL? NoSQL?
  • 27. Some folks won’t like this. But…
  • 28. Start with SQL databases
  • 29. Unless you already have NoSQL skilled staff…
  • 30. Start with SQL databases
  • 31. Why start with SQL? • Established and well-worn technology • Lots of existing code, communities, books, background, tools, etc. • You aren’t going to break SQL DBs in your first 10 million users. No really, you won’t*. • Clear patterns to scalability * Unless you are manipulating data at MASSIVE scale; even then, SQL will have a place in your stack
  • 32. AH HA! You said “massive amounts”, I will have massive amounts!
  • 33. If your usage is such that you will be generating several TB ( >5 ) of data in the first year OR have an incredibly data-intensive workload… you might need NoSQL
  • 34. Regardless, why NoSQL? • Super low latency applications • Metadata driven datasets • Highly non-relational data • Need schema-less data constructs* • Massive amounts of data (again, in the TB range) • Rapid ingest of data ( thousands of records/sec ) • Already have skilled staff *Need != “it is easier to do dev without schemas”
  • 35. When NoSQL = Yes… investigate use of DynamoDB
  • 36. Amazon Dynamo DB • Managed, provisioned throughput NoSQL database • Fast, predictable performance • Fully distributed, fault tolerant architecture • Considerations for non-uniform data Feature Details Provisioned throughput Dial up or down provisioned read/write capacity Predictable performance Average single digit millisecond latencies from SSD-backed infrastructure Strong consistency Be sure you are reading the most up-to-date values Fault tolerant Data replicated across Availability Zones Monitoring Integrated to Amazon CloudWatch Secure Integrates with AWS Identity and Access Management (AWS IAM) Amazon EMR Integrates with Amazon EMR for complex analytics on large datasets
  • 37. But back to the main path… Let’s see how far SQL at the core can grow
  • 38. User >100: First, let’s separate out our single host into more than one: • Web • Database – Use Amazon RDS to make your life easier Web instance Elastic IP address RDS DB instance Amazon Route 53 User
  • 39. User > 1000: Next, let’s address the lack of failover and redundancy issues: • Elastic Load Balancing • Another web instance – In another Availability Zone • Enable Amazon RDS Multi-AZ Web instance Amazon RDS DB instance Active (Multi-AZ) Availability Zone Availability Zone Web instance Amazon RDS DB instance Standby (Multi-AZ) Elastic Load Balancing Amazon Route 53 User
  • 40. • Create highly-scalable applications Feature Details Available Load balance across instances in multiple Availability Zones Health checks Automatically checks health of instances and takes them in or out of service Session stickiness Route requests to the same instance Secure sockets layer Supports SSL offload from web and application servers with flexible cipher support Monitoring Publishes metrics to Amazon CloudWatch Elastic Load Balancing Elastic Load Balancing
  • 41. Scaling this horizontally and vertically will get us pretty far ( 10s-100s of thousands )
  • 42. User >10ks-100ks: RDS DB Instance Active (Multi-AZ) Availability Zone Availability Zone RDS DB Instance Standby (Multi-AZ) Elastic Load Balancing RDS DB Instance Read Replica RDS DB Instance Read Replica RDS DB Instance Read Replica RDS DB Instance Read Replica Web instance Web instance Web instance Web instance Web instance Web instance Web instance Web instance Amazon Route 53 User
  • 43. This will take us pretty far, honestly, but we care about performance and efficiency, so let’s clean up with some components and services
  • 44. Shift some load around: Think components and services: • Move static content from the web instance to Amazon S3 and Amazon CloudFront • Move session/state and DB caching to Amazon ElastiCache or Amazon DynamoDB • More on services later… Web instance RDS DB Instance Active (Multi-AZ) Availability Zone Elastic Load Balancing Amazon S3 Amazon CloudFront Amazon Route 53 User ElastiCache Amazon DynamoDB
  • 45. Working with Amazon S3 • Object-based storage for the web • Designed for 11 9s of durability • Good for things like: – Static assets (css, js, images, videos) – Backups – Logs – Ingest of files for processing • “Infinitely scalable” • Supports fine-grained permission control • Ties in well with CloudFront • Ties in with Amazon EMR • Acts as a logging endpoint for Amazon S3/CloudFront/Billing • Supports encryption at transit and at rest • Reduced redundancy 1/3 cheaper • Amazon Glacier for super long term storage
  • 46. CloudFront Amazon CloudFront is a web service for scalable content delivery: • Cache static content at the edge for faster delivery • Helps lower load on origin infrastructure • Dynamic and static content • Streaming video • Zone apex support • Custom SSL certificates • Low TTLs (as short as 0 seconds) • Lower costs for origin fetches (between Amazon S3 / Amazon EC2 and CloudFront) • Optimized to work with Amazon EC2, Amazon S3, Elastic Load Balancing, and Amazon Route 53 ResponseTime ServerLoad ResponseTime Server Load ResponseTime Server Load No CDN CDN for static content CDN for static & dynamic content 0 10 20 30 40 50 60 70 80 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 8:00 PM 9:00 PM VolumeofData Delivered(Gbps)
  • 47. Shift some load around: Let’s lighten the load on our web and database instances: • Move static content from the web instance to Amazon S3 and CloudFront • Move session/state and DB caching to ElastiCache or Amazon DynamoDB Web instance RDS DB Instance Active (Multi-AZ) Availability Zone Elastic Load Balancer Amazon S3 Amazon CloudFront Amazon Route 53 User ElastiCache Amazon DynamoDB
  • 48. Shift some load around: Let’s lighten the load on our web and database instances: • Move static content from the web instance to Amazon S3 and CloudFront • Move dynamic content from the load balancer to CloudFront • Move session/state and DB caching to ElastiCache or Amazon DynamoDB Web instance RDS DB Instance Active (Multi-AZ) Availability Zone Elastic Load Balancer Amazon S3 Amazon CloudFront Amazon Route 53 User ElastiCache Amazon DynamoDB
  • 49. Shift some load around: Let’s lighten the load on our web and database instances: • Move static content from the web instance to Amazon S3 and CloudFront • Move dynamic content from the load balancer to CloudFront • Move session/state and DB caching to ElastiCache or Amazon DynamoDB Web instance RDS DB Instance Active (Multi-AZ) Availability Zone Elastic Load Balancer Amazon S3 Amazon CloudFront Amazon Route 53 User ElastiCache Amazon DynamoDB
  • 50. Scaling to 10M Users: A Story in Four Parts • Intro and Initial Steps • Building Blocks • Tools and Monitoring • 10M Users and Beyond
  • 51. Now that our web tier is much more lightweight, we can revisit the beginning of our talk…
  • 52. Auto Scaling!
  • 53. Automatic resizing of compute clusters based on demand Trigger auto-scaling policy Feature Details Control Define minimum and maximum instance pool sizes and when scaling and cool down occurs Integrated to Amazon CloudWatch Use metrics gathered by CloudWatch to drive scaling Instance types Run Auto Scaling for On-Demand and Spot Instances; compatible with VPC aws autoscaling create-auto-scaling- group --auto-scaling-group-name MyGroup --launch-configuration-name MyConfig --min-size 4 --max-size 200 --availability-zones us-west-2c Auto Scaling Amazon CloudWatch
  • 54. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Typical weekly traffic to Amazon.com
  • 55. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Typical weekly traffic to Amazon.com Provisioned capacity
  • 56. November traffic to Amazon.com November
  • 57. November traffic to Amazon.com Provisioned capacity November
  • 58. November traffic to Amazon.com 76% 24% Provisioned capacity November
  • 59. November traffic to Amazon.com November
  • 60. Auto Scaling lets you do this!
  • 61. Auto Scaling can help from one instance to thousands and back down
  • 62. User >500k+: Availability Zone Amazon Route 53 User Amazon S3 Amazon CloudFront Availability Zone Elastic Load Balancing Amazon DynamoDBRDS DB Instance Read Replica Web instance Web instance Web instance ElastiCache RDS DB Instance Read Replica Web instance Web instance Web instance ElastiCacheRDS DB Instance Standby (Multi-AZ) RDS DB Instance Active (Multi-AZ)
  • 63. Use Tools: Managing your infrastructure will become an ever increasing important part of your time. Use tools to automate repetitive tasks. • Tools to manage AWS resources • Tools to manage software and configuration on your instances • Automated data analysis of logs and user actions
  • 64. AWS Application Management Solutions AWS Elastic Beanstalk AWS OpsWorks AWS CloudFormation Amazon EC2 Convenience Control Higher-level services Do it yourself
  • 65. Host-Based Configuration Management Two big players: – Opscode Chef – PuppetLabs Puppet • Both do more or less the same thing • Both have syntax that isn’t too dissimilar • Use HBCM with one of the tools from the previous slide • Spend the time required to learn them • Can’t scale easily without HBCM • Growing in popularity: Salt, Ansible
  • 66. User >500k+: You’ll potentially start to run into issues with speed and performance of your applications: • Have monitoring/metrics/logging in place – If you can’t build it internally, outsource it! (3rd party SaaS) • Pay attention to what customers are saying works well • Squeeze as much performance as you can out of each service/component
  • 67. HOST LEVEL METRICS AGGREGATE LEVEL METRICS LOG ANALYSIS EXTERNAL SITE PERFORMANCE
  • 68. Not having proper monitoring/metrics is like flying a plane with an eye mask on in a thunderstorm. Oh, and your wing is on fire.
  • 69. AWS Marketplace & Partners Can Help • Customer can find, research, and buy software • Simple pricing, aligns with Amazon EC2 usage model • Launch in minutes • AWS Marketplace billing integrated into your AWS account • 1300+ products across 20+ categories Learn more at: aws.amazon.com/marketplace
  • 70. Scaling to 10M Users: A Story in Four Parts • Intro and Initial Steps • Building Blocks • Tools and Monitoring • 10M Users and Beyond
  • 71. There are further improvements to be made in breaking apart our web/app layer
  • 72. SOA = Service Oriented Architecture
  • 73. SOA’ing Move services into their own tiers/modules. Treat each of these as 100% separate pieces of your infrastructure and scale them independently. Amazon.com and AWS do this extensively! It offers flexibility and greater understanding of each component.
  • 74. Loose coupling sets you free! • The looser they're coupled, the bigger they scale – Independent components – Design everything as a black box – Decouple interactions – Favor services with built-in redundancy and scalability rather than building your own Controller A Controller B Controller A Controller B Q Q Tight coupling Use Amazon SQS for buffers Loose coupling
  • 75. Loose coupling + SOA = winning Examples: • Email • Queuing • Transcoding • Search • Databases • Monitoring • Metrics • Logging Amazon CloudSearch Amazon SQSAmazon SNS Amazon Elastic Transcoder Amazon SWF Amazon SES In the early days, if someone has a service for it already, opt to use that instead of building it yourself. DON’T RE-INVENT THE WHEEL
  • 76. On re-inventing the wheel… If you find yourself writing your own: queue, DNS server, database, storage system, monitoring tool
  • 77. Take a deep breath and stop it. Now.
  • 78. Back to SOA
  • 79. User >1mil+: Reaching a million and above is going to require some bit of all the previous things: • Multi-AZ • Elastic Load Balancing between tiers • Auto Scaling • Service-oriented architecture • Serving content smartly (Amazon S3/CloudFront) • Caching off DB • Moving state off tiers that auto-scale
  • 80. User >1mil+: RDS DB Instance Active (Multi-AZ) Availability Zone Elastic Load Balancing RDS DB Instance Read Replica RDS DB Instance Read Replica Web instance Web instance Web instance Web instance Amazon Route 53 User Amazon S3 Amazon CloudFront Amazon DynamoDB Amazon SQS ElastiCache Worker instance Worker instance Amazon CloudWatch Internal app instance Internal app instance Amazon SES
  • 81. The next big steps
  • 82. User >5mil – 10mil: You’ll potentially start to run into issues with your database around contention on the write master. How can you solve it? • Federation ~ splitting into multiple DBs based on function • Sharding ~ splitting one data set up across multiple hosts • Moving some functionality to other types of DBs (NoSQL)
  • 83. Shifting functionality to NoSQL • Similar in a sense to federation • Again, review the earlier points to determine need of NoSQL vs SQL • Leverage hosted services like Amazon DynamoDB • Some use cases: – Leaderboards/scoring – Rapid ingest of clickstream/log data – Temporary data needs ( cart data ) – “Hot” tables – Metadata/lookup tables Amazon DynamoDB
  • 84. …and there you have it. 10 Million
  • 85. A Quick Review
  • 86. Review • Multi-AZ your infrastructure • Make use of self-scaling services – Elastic Load Balancing, Amazon S3, Amazon SNS, Amazon SQS, Amazon SWF, Amazon SES, etc. • Build in redundancy at every level • Most likely start with SQL • Cache data both inside and outside your infrastructure • Use automation tools in your infrastructure
  • 87. Review (cont) • Make sure you have good metrics/monitoring/logging tools in place • Split tiers into individual services (SOA) • Use Auto Scaling when you’re ready for it • Don’t reinvent the wheel • Move to NoSQL when it really makes sense but do your best not to administer it
  • 88. Putting all this together means we should now easily be able to handle 10+ million users!
  • 89. To infinity…..
  • 90. User >10mil: • More fine tuning of your application • More SOA of features/functionality • Going from Multi-AZ to multi-region • Potentially needing to start building custom solutions • Deep analysis of your whole stack
  • 91. Next Steps? READ! • aws.amazon.com/documentation • aws.amazon.com/architecture • aws.amazon.com/start-ups
  • 92. Next Steps? START USING AWS aws.amazon.com/free
  • 93. Next Steps? ASK FOR HELP! • forums.aws.amazon.com • aws.amazon.com/support • Your Account Manager • A Solutions Architect
  • 94. THANKS FOR LISTENING! Mohan Vedula – mohanv@amazon.com Brett Francis – brettf@amazon.com
  • 95. © 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.© 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc. Scaling on AWS for the First 10 Million Users Mohan Vedula, Enterprise Solutions Architecture Brett Francis, Enterprise Solutions Architecture March 26, 2014 Thank you!