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re:Invent recap
breakfast
Jimmy Dahlqvist & Maurits Johansson
2021-12-14
Agenda
 Sustainability
 Serverless
 Community & Builders
 Low Code / No Code
 Takeaways
Sustainability
Sustainability
 Adding a 6th pillar to the AWS Well Architected Framework
 Sustainability Shared Responsible Model
 AWS is responsible for the sustainability OF the cloud
 Customer is responsible for the sustainability IN the cloud
 AWS Customer Carbon Footprint tool
 Serverless can help your organization meet sustainability goals
 Share resources when not in use
The greenest energy is the
energy that you don’t use.
Peter Desantis
Graviton 3
 Latest CPU in the Graviton family
 AWS Custom designed ARM based CPU
 Use up to 60% less energy for the same performance than comparable EC2
instances
 Provide up to 25% better compute performance
 Best price performance
Don't forget to turn off the
lights.
Werner Vogels – re:Invent 2012
Serverless
Amazon S3 Event notifications with Amazon
EventBridge
 S3 Event = React to object changes in you bucket
 Since 2014 - Event delivery to SNS, SQS and Lambda
 2019 - EventBridge - built for Event driven applications
 EventBridge integration with 18 services
 Schema registry
 Archive + replay events
 API destinations
 What’s the impact?
 More reliable (At-least-once delivery)
 Faster
 Advanced filtering (object size, time-range)
 Less management
 When to use?
MSK(Managed Streaming for Kafka) Serverless
 MSK = Fully managed Apache Kafka Service
 Apache Kafka = Open-source Distributed event streaming platform
 No more:
 Provisioning of brokers
 Handling number of partitions
 Now
 0.75$/h cluster fee <—- note
 0.0015$/h per partition
 Storage
 Data in/out
 When to use?
Kinesis Data Streams On-Demand
 Kinesis Data Steams = Managed Real-time Data streaming service
 Provision Shards (1 shard = 1mb/s write and 2mb/s read throughout)
 On-Demand
 Pay per GB written/read from your data streams
 Accommodates workload
 Pay per stream per hour, Data ingestion, Fan out and storage
 When to use?
Amazon Redshift Serverless
 Redshift - Cloud Data Warehouse
 On-Demand
 Provision servers (vCPU, IO,Storage, Memory)
 Serverless
 Pay only for the compute capacity
 1 Redshift Processing Unit (RPU) = 0.49$/h
 Base and Max settings to control the scaling
 Make active/inactive (Only pay for persistent storage)
 Free 24h point-in-time restore (30 min granularity)
 When to use?
Amazon EMR Serverless
 Amazon EMR = Managed Service for open source analytics frameworks such as
Apache Spark, Hive, Presto
 EMR on EC2/EKS
 Provision Instances/Setup EKS
 EMR Serverless
 Choose framework version
 Submit jobs
 Min/Max concurrent workers
 Pay per vCPU, Memory and Storage
 When to use?
Lake formation Cell and row level security
 AWS Lake Formation = Service for Setting up and securing data lakes in AWS
 ”A data lake is a centralized, curated, and secured repository that stores all your
data, both in its original form and prepared for analysis”
 Whats new?
 More finely grained security
 No need to create subset of data for different consumers.
 When to use?
AWS Lambda Event filtering
 AWS Lambda = Serverless functions
 Event sources
 SQS
 DynamoDb
 Kinesis
 Before
 Now
 Simplifies following the single-responsibility model
 No more excessive lambda executions
 When to use?
DynamoDB Standard - IA Tables
 DynamoDb = Serverless NoSQL database
 Before
 After
 60% Lower cost for storage
 More expensive queries
 Convertible Tables
 When to use?
Amazon Simple Queue Service (SQS) DLQ Redrive
 SQS = Serverless message queues
 Before
 After
 Redrive back to source queue
 When to use?
Lambda partial batch response for SQS event source
 Before
 After
 Process at record-level instad of batch-level
 Removing repetitive data transfer = higher throughput
 More efficient processing (no visibility timeout on good messages)
 When to use?
Community & Builders
re:Post
 Community Driven Q&A
 Answers from community experts, AWS customers, Partners, and employees.
 Replaces AWS Forums
 Tied to your AWS account identity
 Lacking support for login with GitHub, LinkedIn, Amazon etc
 https://repost.aws
CDK V2
 Consolidates into a single package called aws-cdk-lib
 No need to download individual packages for each AWS service
 Comply with Semantic Versioning (semver)
 Improved productivity
 CDK API reference refresh with code snippets
 CDK Watch for faster inner-loop development iterations on the application code
Construct Hub
 Central place to discover CDK constructs
 Community & Developer Driven
 https://constructs.dev/
Low Code / No Code
Amplify Studio
 Low Code capability
 Build beautiful web apps with a backend easy and fast
 Import designs from Figma
 Generate React Components
Amazon SageMaker Canvas
 Amazon SageMaker = Fully managed service for preparing, building, training and
deploying machine learning models.
 SageMaker Canvas
 Point and click interface
 No coding
 Targets business users rather than data scientists
 When to use?
Takeaways
Takeaways
 Evolution – not a revolution
 Sustainability is a hot topic
 Continue to invest in serverless as a way.
 Low code trend continues
Thank You!

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re:Invent Recap Breakfast

  • 1. re:Invent recap breakfast Jimmy Dahlqvist & Maurits Johansson 2021-12-14
  • 2. Agenda  Sustainability  Serverless  Community & Builders  Low Code / No Code  Takeaways
  • 4. Sustainability  Adding a 6th pillar to the AWS Well Architected Framework  Sustainability Shared Responsible Model  AWS is responsible for the sustainability OF the cloud  Customer is responsible for the sustainability IN the cloud  AWS Customer Carbon Footprint tool  Serverless can help your organization meet sustainability goals  Share resources when not in use
  • 5. The greenest energy is the energy that you don’t use. Peter Desantis
  • 6. Graviton 3  Latest CPU in the Graviton family  AWS Custom designed ARM based CPU  Use up to 60% less energy for the same performance than comparable EC2 instances  Provide up to 25% better compute performance  Best price performance
  • 7. Don't forget to turn off the lights. Werner Vogels – re:Invent 2012
  • 9. Amazon S3 Event notifications with Amazon EventBridge  S3 Event = React to object changes in you bucket  Since 2014 - Event delivery to SNS, SQS and Lambda  2019 - EventBridge - built for Event driven applications  EventBridge integration with 18 services  Schema registry  Archive + replay events  API destinations  What’s the impact?  More reliable (At-least-once delivery)  Faster  Advanced filtering (object size, time-range)  Less management  When to use?
  • 10. MSK(Managed Streaming for Kafka) Serverless  MSK = Fully managed Apache Kafka Service  Apache Kafka = Open-source Distributed event streaming platform  No more:  Provisioning of brokers  Handling number of partitions  Now  0.75$/h cluster fee <—- note  0.0015$/h per partition  Storage  Data in/out  When to use?
  • 11. Kinesis Data Streams On-Demand  Kinesis Data Steams = Managed Real-time Data streaming service  Provision Shards (1 shard = 1mb/s write and 2mb/s read throughout)  On-Demand  Pay per GB written/read from your data streams  Accommodates workload  Pay per stream per hour, Data ingestion, Fan out and storage  When to use?
  • 12. Amazon Redshift Serverless  Redshift - Cloud Data Warehouse  On-Demand  Provision servers (vCPU, IO,Storage, Memory)  Serverless  Pay only for the compute capacity  1 Redshift Processing Unit (RPU) = 0.49$/h  Base and Max settings to control the scaling  Make active/inactive (Only pay for persistent storage)  Free 24h point-in-time restore (30 min granularity)  When to use?
  • 13. Amazon EMR Serverless  Amazon EMR = Managed Service for open source analytics frameworks such as Apache Spark, Hive, Presto  EMR on EC2/EKS  Provision Instances/Setup EKS  EMR Serverless  Choose framework version  Submit jobs  Min/Max concurrent workers  Pay per vCPU, Memory and Storage  When to use?
  • 14. Lake formation Cell and row level security  AWS Lake Formation = Service for Setting up and securing data lakes in AWS  ”A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis”  Whats new?  More finely grained security  No need to create subset of data for different consumers.  When to use?
  • 15. AWS Lambda Event filtering  AWS Lambda = Serverless functions  Event sources  SQS  DynamoDb  Kinesis  Before  Now  Simplifies following the single-responsibility model  No more excessive lambda executions  When to use?
  • 16. DynamoDB Standard - IA Tables  DynamoDb = Serverless NoSQL database  Before  After  60% Lower cost for storage  More expensive queries  Convertible Tables  When to use?
  • 17. Amazon Simple Queue Service (SQS) DLQ Redrive  SQS = Serverless message queues  Before  After  Redrive back to source queue  When to use?
  • 18. Lambda partial batch response for SQS event source  Before  After  Process at record-level instad of batch-level  Removing repetitive data transfer = higher throughput  More efficient processing (no visibility timeout on good messages)  When to use?
  • 20. re:Post  Community Driven Q&A  Answers from community experts, AWS customers, Partners, and employees.  Replaces AWS Forums  Tied to your AWS account identity  Lacking support for login with GitHub, LinkedIn, Amazon etc  https://repost.aws
  • 21. CDK V2  Consolidates into a single package called aws-cdk-lib  No need to download individual packages for each AWS service  Comply with Semantic Versioning (semver)  Improved productivity  CDK API reference refresh with code snippets  CDK Watch for faster inner-loop development iterations on the application code
  • 22. Construct Hub  Central place to discover CDK constructs  Community & Developer Driven  https://constructs.dev/
  • 23. Low Code / No Code
  • 24. Amplify Studio  Low Code capability  Build beautiful web apps with a backend easy and fast  Import designs from Figma  Generate React Components
  • 25. Amazon SageMaker Canvas  Amazon SageMaker = Fully managed service for preparing, building, training and deploying machine learning models.  SageMaker Canvas  Point and click interface  No coding  Targets business users rather than data scientists  When to use?
  • 27. Takeaways  Evolution – not a revolution  Sustainability is a hot topic  Continue to invest in serverless as a way.  Low code trend continues