AWS Summit - SFO - Day-2 Notes from Keynote and Fireside chat

Written on April 18, 2017

AWS organized the AWS Summit at San Francisco on 18th and 19th of April. It was an eye-opener for me on the devOps progress and the adoption of cloud based work-flows. I had take some notes and thought of sharing it. This is the notes from Day 2 of the event. Hope it is of use to you!

Amazon Summit SFO logo

This part 2 of the blog post. For notes on the 1st day’s events, see the AWS Summit - SFO - Day - 1 Notes post.

Keynote featuring Dr. Werner Vogels, CTO, Amazon.com

  • 7,500 people in attendence
  • $ 14 billion run-rate growing at 14/40% YOY?
  • focus on startups
  • Twilio literally used every service of AWS.
  • new “in the cloud” integrators instead of System Integrators like Cognizant, IBM, Accenture, etc.
  • Software vendors - almost everyone is on AWS. 1,200 ISVs
  • SaaS integrations - Splunk is a strategic partner
  • Yelp - uses Yelp for end to end delivery on timing of the delivery of content.
  • Developers are like James Bond and AWS is like the ‘Q’
    • Supersonic speed: over 90 services. Mostly on feedback.
      • AWS Codestar: In one environment, IDE,
      • Create a project, add the roles, build the piepline and connect with IDE.
    • F1 instances: Field programmable gate array. Real time video processing, financial analytics, big data search and analytics.
    • End goal - make the infrastructure invisible.
    • Managing containers is hard - almost like pre-cloud world.
    • NextDoor - private social network.
      • Entire platform is on AWS.
      • build and deployment time down by 10%
        • used to have weekly releases
        • Red+Black deployments: Every deployment, create a whole set of new EC2 instances. Route a small traffic and based on feedback, switch the traffic and bring down old instances.
        • dropped deployments from 25 mins to 7 mins.
        • 10x improvement in deployment. dozens of deployments a day!
    • Serverless - Lambda
      • Sholastic, Robot, Netflix, Experian - some examples
      • AWS X-Ray: UI based debugging and troubleshooting on flow, components.
      • Amazon DynamoDB: auto scales: Expedia, Lyft
      • Amazon DynamoDB Accelerator (DAX): fully managed, in-memory cache
    • Flight
      • Old world database: Expensive, proprietary, lock-in
      • OpenSource Dbs to help.
      • 23,0000 DB migrated from on-prem to cloud
      • Amazon aurora: MySQL compatible. 5x performance. Amazon Aurora PostGreSQL: semantically closer to Oracle.
      • Aurora - used by Expedia. 100 million writes a day, 17,000 writes a second. 17ms read.
    • X-Ray Vision
      • Amazon Athena - interactive query service. Amazon EMR - hadoop, spark, presto. Date warehousing - RedShift.
      • Yelp, Hudl, Sholastic, sling.
      • Redshift Spectrum: Directly run data warehouse queries on S3 data. Yelp is using it.
    • Precognition
      • Amazon ML (machine learning),
      • Deep learning AMI
      • Amazon Rekognition used for C-SPAN politician recognition and tagging. 3 weeks saving 9,000 hours!
      • Image Rekogniition - scoring for inappropriate content.
      • Amazon Polly - 47 voices, 24 languages, customize on what is said., whispering voice and speech marks.
      • Amazon Speech recognition - Amazon lex. Lex connected to Lambda. So based on the intent of the voice, this will be used to trigger the Lambda function.
      • Slack uses Cloudfront, Athena,
      • Amazon lex has been integrated with slack. Conversational bots.
      • Amazon AI - hubspot, duolingo
    • Immortality
      • { lot of focus on startups }
        • moving fast, agile, use all of the services
      • Digital Transformation: ticketmaster, PBS, GE

Fireside Chat featuring Andy Jassy, CEO, Amazon Web Services – RED

  • growth of 47%
  • Workday - preferred cloud provider.
  • private cloud - not common in lot of customers. Hybrid operation is more common.
  • VmWare + AWS collaboration
  • Multi cloud strategy: Most customers don’t do it.
    • Standardize to lowest common stuff - that’s constraining their developers
    • Learning different platforms ==> Isn’t this is the same as vendor lock in?
    • Diminish buying power - essentially lose the volume discounts.
  • Machine learning / deep learning - 3 levels
    • Level 0: actual mathematicians / expert practitioner (eg: Netflix)
    • Level 1: Providing tools for regular developers.
    • Level 2: Quick tools for everyone.
  • Big challenge is getting data from data center into the S3.
  • Connected devices: Over time servers at offices or homes will be replaced with connected devices. That will be the new hybrid model.
    • Tata motors manages trucks ?
  • Amazon GreenGrass - software module that can run lambda functions that will partly run in cloud and in the device.
  • Focus
    • expansion of geographical foot print: in every tier 1 country
    • DB expansion - Aurora fastest growing service
    • Container and orchestration management
    • Event driven and serverless computing
    • Self service and improving it.
  • How do you innovate so quickly?
    • disproportionately hire builders
      • understand that launch is a starting line and not the finish
    • organization
      • small autonomous team
      • technology and product management in the same team
      • teams own the road-map
    • eat your dog food
      • amazon.com itself is using AWS and that gives a large amt of feedback
      • Trying to get away from the institutional ways to say “no”.
      • About ability to make fast decisions.
  • Organizational culture
    • unusually customer oriented
      • most tech companies are competitor focused.
    • we are pioneers
      • most competitors are losing their drive to innovate
    • unusually long term oriented
    • trusted advisor capabilities in the customer relationship team
      • we’ll reach out to tell customers to tell you’re not using everything. So save the money. Saved $350 mil last 2 yrs to customers.
  • Quirky parts of culture
    • ban powerpoints at meetings
      • have conversation. 6 page narrative.
      • read this at a meeting and then start the discussion.
    • a press release, FAQ and documentation is first created before a product is even written.
      • forces to think on use and reason for its adoption.
    • unusually truth seeking
      • disagree and commit
  • Learning
    • don’t fight gravity. If you know that the inevitable will happen, then you should cannibalize before your competitor does it.
      • explained within the context of whether Amazon should support 3rd party suppliers and Amazon’s jump to support them before eBay and others could kill them.

Deep Dive on AWS IoT

  • MQTT is the protocol used, WebSockets is what the phones use.
  • Use a shadow device for sending the control commands. This will ensure that the device gets the commands in right order.
  • Amazon Cognito for authentication of devices.