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Apache Mxnet | Amazon Strategy Cloud Trends The evolution of culture and technology Adrian Cockcroft @adrianco VP Cloud Architecture Strategy Amazon Web Services © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 1 Get the culture right 2 Migrate to the cloud Culture And Evolution 3 The new de-normal, untangle data tier 4 Monoliths to microservices to functions 1 Get the culture right 2 Migrate to the cloud Cloud Trends 3 The new de-normal, untangle data tier 4 Monoliths to microservices to functions 5 Open source and artificial intelligence If you want to build a ship, don’t drum up the people to gather wood, divide the Culture work, and give orders. Instead, teach them to yearn for the vast and endless sea. Antoine de Saint-Exupéry, author of “Le Petit Prince” (“The Little Prince”) Culture Nordstrom Technology NorDNA Culture Deck 1. Values are what we value 2. High performance 3. Freedom & responsibility Culture 4. Context, not control Seven Aspects of Netflix Culture 5. Highly aligned, loosely coupled 6. Pay top of market 7. Promotions & development • Customer • Bias for action obsession • Frugality • Ownership • Learn and • Invent and be curious simplify • Earn trust Culture • Are right, a lot of others Amazon leadership • Hire and develop • Dive deep the best principles • Have backbone; • Insist on the disagree and highest standards commit • Think big • Deliver results Intentional Culture Appropriate Judgement Migrating to Cloud Lessons from the Netflix cloud journey, brought up to date IT’s assumption: make systems perfect 2008 so that developers don't have to think about failures Start with High-end IBM P-series hardware, Oracle... a shock Two-day outage caused by SAN hardware failure! 2008 Failure raised questions… Question Availability has to be application concern! Assumption Use low cost cloud infrastructure? 2009 Vast increase in datacenter capacity was needed Unpredictable in advance, how much, where… Add an Why? Online streaming replacing DVD shipping logistics existential threat Nowadays, systems of engagement are dominating IT Shipping plan Inventory DATACENTER SHIPPING SITE DVD Business Personalized Mail DVD Browsing Back A few interactions per week per customer to datacenter Add choices New DVD Encoded content DATACENTER CDN QoS Start Play DVDStreaming logging config Progress heartbeat Business Personalized Binge watching browsing episodes of TV Video data shows every day Add choices Encoded content Views per week DATACENTER10x CDN QoS Start Play Streaming logging config Progress Traffic to Business heartbeat Personalized100x datacenter per view Binge watching Browsing episodes of TV Video data shows every day Per customer that 1000x started streaming Add choices Streaming The Digital Transformation Point where 0.1% Capacity DATACENTER CAPACITY of customers are DVD streaming Crunch TIME If we say new workload causes 1000x traffic to datacenter, then when 0.1% of users switch, the capacity needed is equal. Recruit world class datacenter operations build team and guess how much capacity they would need, and build it before it was needed — lots of upfront $$$ spend Choices OR Use the Elastic Compute service of AWS, built by one of Netflix biggest competitors, and spend $$$ on video content and developers Competition Understand how AWS was separated from Amazon Prime Capacity Experiments 2009 to see what worked Mitigate Business Sign Up For Enterprise risks License Agreement Publicity NYT story about Netflix and AWS April 2010 Encoding movies 2009 Big backlog, not enough capacity Applications Moved to AWS EC2 Showed that capacity existed on demand Shut down capacity to save as backlog varied Quality of Service (QoS) logging 2009 Too much traffic to datacenter databases Storage for logs moved to S3 Applications Unlimited space Log analysis moved to EMR - Hadoop Worked with AWS to support Hadoop + Hive in Elastic Map-Reduce service Crunch Time Front end on AWS Start of 2010 AWS Decided not to Web pages and Backend capacity API clients migrate expands to fill Most backend to cloud remaining space build any more DATACENTER still in datacenter datacenter capacity Need to move to AWS before end of 2010 to survive January 2010 December Front end web page and API migration A picture like this was shown in every management meeting. Hard deadline to move capacity out to make space for what was left. Running out of runway January 2010 December Start with the simplest possible API service Migration Next the simplest web page Sequence Then pages and APIs one by one Logins and web page NETFLIX WEB PAGE requests How to Run Both? Gradual Migration Old web pages, Selective web backend, and page redirects login service Migrated web pages DATACENTER AWS CLOUD www.netflix.com movies.netflix.com WEB PAGE Reads of Updates SoR data HowAWS Database to Migration Service RunMove Both? Data? Move from Oracle to scalable low cost Continuous cloud database replication services Amazon Updates DMS Amazon Aurora DynamoDB Postgres DATACENTER— SYSTEM OF RECORD AWS CLOUD How to MoveBack upData? Data? For cloud to be used as the system of record an archive backup mechanism is needed To replace offsite tape backup, create a separate account in a different region Amazon S3 is extremely secure and durable. Data can’t be deleted. Automatic time based purge after 90 days Long term very low cost archive using Amazon Glacier ARCHIVE Separate AWS account, How to different region Back up Data? Versioned Amazon purged after 90 days Glacier Compress, encrypt, archive Expensive offsite Amazon Amazon tape backups DynamoDB S3 NETFLIX WEB PAGE Final Stage “All-In” Netflix migration of billing and corporate IT Corporate IT, billing, last Login functions to Close down datacenter be migrated Systems of record data APIs Pages, etc. DATACENTER AWS CLOUD The New De-Normal Monolithic Kitchen Sink De-normalized Databases Analogy Monolith Expensive, Hard to Create and Run ic DatabaseMonolith Expensive, Hard to Create and Run Database Schema Entity Relationship Database Schema Entity Relationship Database Schema Entity Relationship Kitchen Sink Analogy GLASSES Kitchen Sink CleanupAnalogy GLASSES Kitchen Sink Cleanup GLASSES Kitchen Sink Cleanup GLASSES Kitchen Sink Cleanup GLASSES Kitchen Sink Cleanup GLASSES Kitchen Sink Cleanup GLASSES Kitchen Sink Cleanup Consistency Problem How Many Complete Sets Are There? Consistency Problem How Many Complete Sets Are There? GLASSES Consistency Problem How Many Complete Sets Are There? GLASSES Adding a New Use Case SAKE SET GLASSES Adding a New BOWLS Use Case Cloud Makes it Easy to Add New Databases Amazon Redshift Untangle and Migrate Existing “Kitchen Sink” Schemas Untangle and Migrate Existing “Kitchen Sink” Schemas The New De-Normal Monolithic Kitchen Sink De-normalized Databases Analogy Evolution of Business Logic Monolith Microservices Functions Splitting Monoliths Ten Years Ago XML & SOAP Splitting Monoliths Ten Years Ago Splitting Monoliths FiveTen Years Ago REST JSON Fast binary Splitting encodings Monoliths Five Years Ago Splitting Monoliths FiveTen Years Ago Microservices Five Years Ago Amazon SQS Amazon API Amazon Microservices Gateway DynamoDB Fiveto Functions Years Ago Standard building brick services provide standardized platform capabilities Amazon Kinesis Amazon S3 Amazon SNS Amazon SQS Business Logic Glue between the bricks Amazon API Amazon Microservices Gateway DynamoDB to Functions Standard building brick services provide standardized platform capabilities Amazon Kinesis Amazon S3 Amazon SNS Amazon SQS Amazon API Amazon Microservices Gateway DynamoDB to Functions Amazon Kinesis Amazon S3 Amazon SNS Amazon SQS Amazon API Amazon Microservices Gateway DynamoDB to Functions Amazon Kinesis Amazon S3 Amazon SNS Amazon SQS Amazon API Amazon Microservices Gateway DynamoDB to FunctionsEphemeral Amazon Kinesis Amazon S3 Amazon SNS Microservices to Ephemeral Functions Amazon SQS Amazon API Microservices Gateway to Ephemeral Functions Amazon API Amazon Microservices Gateway DynamoDB to Ephemeral Functions Amazon Kinesis Amazon API Microservices Gateway to Ephemeral Functions Amazon S3 Amazon SNS Amazon SQS Amazon API Amazon Microservices Gateway When the system is DynamoDB idle, it shuts down and to Ephemeral costs nothing to run Functions Amazon Kinesis Amazon S3 Amazon SNS Evolution of Business Logic Monolith Microservices Functions Open Source AI at AWS, and Apache MXNet What I’m currently working on… © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. • Open Source at AWS • Applications of Deep Learning • Apache MXNet Overview • Apache MXNet API • Code and DIYrobocars • Tools and Resources Amazon Open Source Contributions Linux & Drivers Apache Hadoop Apache Lucene Xen Apache Hive Apache Solr Apache Tomcat Apache Bigtop Kuromoji PostgreSQL Apache Oozie ElasticSearch Docker Apache Drill CBMC Boto Apache Zeppelin Apache MXNet Apache Pig Moses Cloudera HUE Apache Joshua Repositories Owned by AWS & Amazon https://github.com/aws https://github.com/awslabs https://github.com/amznlabs https://blox.github.io/ Blox – Container orchestration for ECS s2n – Secure replacement for openssl, used by S3 Chalice – Python serverless microframework for AWS Sockeye – Neural Machine Translation using MXNet AWS-CLI – Command line interface to AWS AWS-shell – Autocomplete based user interface for AWS-CLI AWS SDKs for Java, Python, PHP, Go, Ruby etc. AWS Mobile SDKs for iOS, Android etc. Cloud9 Ace – Cloud based interactive development editor Cfncluster – Build and manage HPC clusters ION – Amazon data serialization libraries
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