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AWS re:Invent re:Cap 2019

Frank Munz
December 16, 2019
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AWS re:Invent re:Cap 2019

Frank Munz

December 16, 2019
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  1. AWS Co mmun i t y
    @frankmunz
    Frank Munz
    Amazon Web Services

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  2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  3. Tech Keynotes
    Getting Started
    Peter DeSantis, VP of AWS Global Infrastructure, Monday night
    https://www.youtube.com/watch?v=GPUWATKe15E
    Andy Jassy, CEO of AWS, Tuesday morning
    https://www.youtube.com/watch?v=7-31KgImGgU
    Dr. Werner Vogels, CTO of Amazon.com, Thursday morning
    https://www.youtube.com/watch?v=OdzaTbaQwTg

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  4. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Service Availability
    https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/
    Service Pricing
    https://aws.amazon.com/pricing/

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  5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  6. Amazon EC2 Inf1 Instances
    Introducing
    The fastest and lowest cost machine learning inference in the cloud
    Up to 16 AWS Inferentia with 128 TOPs each, first custom ML chip designed by AWS
    3X higher throughput and up to 40% lower cost per inference
    compared to GPU powered G4 instances
    Compute
    General Availability – December 3
    L E A R N M O R E CMP324-R: Deliver high performance ML inference with AWS Inferentia Wednesday, 7pm, Aria

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  7. AWS Graviton2 Processor
    Introducing
    Enabling the best price/performance for your cloud workloads
    A1 Instances.
    16 vCPUs,10 Gbps
    3.5 Gbps EBS
    bandwidth
    64 vCPUs, 20 Gbps
    14 Gbps EBS bandwidth
    Graviton1 Processor Graviton2 Processor
    DRAFT
    Compute
    Preview – December 3
    L E A R N M O R E CMP322-R: Deep dive on EC2 instances powered by AWS Graviton Wednesday 9:15am, MGM

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  8. AWS Graviton2 Based Instances
    Introducing
    Up to 40% better price-performance for general purpose, compute
    intensive, and memory intensive workloads.
    l
    M6g C6g R6g
    DRAFT
    Built for: General-purpose. Instance
    storage option: M6gd
    Built for: Compute intensive
    applications. Instance storage
    option C6gd
    Built for: Memory intensive
    workloads. Instance storage R6gd
    Compute
    Preview – December 3
    L E A R N M O R E CMP322-R: Deep dive on EC2 instances powered by AWS Graviton Wednesday 9:15am, MGM

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  9. AWS Compute Optimizer
    Introducing
    Identify optimal Amazon EC2 instances and EC2 Auto Scaling group
    for your workloads using a ML-powered recommendation engine
    DRAFT
    Management Tools
    General Availability – December 3

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  10. AWS Compute Optimizer

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  11. Quantum Computers
    https://en.wikipedia.org/wiki/Trapped_ion_quantum_computer
    A trapped ion quantum
    computer is one proposed
    approach to a large-scale quantum
    computer. Ions, or charged atomic
    particles, can be confined and
    suspended in free space
    using electromagnetic
    fields. Qubits are stored in stable
    electronic states of each ion,
    and quantum information can be
    transferred through the collective
    quantized motion of the ions in a
    shared trap (interacting through
    the Coulomb force).

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  12. Bra-ket Notation
    https://en.wikipedia.org/wiki/Quantum_mechanics
    Bra–ket notation is
    a notation for linear algebra and
    linear operators on complex
    vector spaces together with their
    dual space both in the finite-
    dimensional and infinite-
    dimensional case. It is
    specifically designed to ease the
    types of calculations that
    frequently come up in quantum
    mechanics

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  13. Amazon Braket
    Introducing
    Fully managed service to explore and experiment
    with quantum computing.
    design, test, and
    run quantum
    algorithms
    variety of quantum
    hardware
    technologies
    DRAFT
    Quantum Technology
    Preview – December 2
    LEARN MORE CMP213: Introducing Quantum Computing with AWS Wednesday 11:30am, Venetian

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  14. AWS Nitro Enclaves
    Introducing
    Create additional isolation to further protect highly sensitive data
    Nitro Hypervisor
    Instance A Enclave A Instance B
    EC2 Host Additional isolation
    within an EC2 instance
    Isolation between EC2
    instances in the same host
    Local socket
    connection
    DRAFT
    Compute
    Preview – December 3

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  15. DRAFT
    Containers
    General Availability – December 3
    LEARN MORE CON-326R - Running Kubernetes Applications on AWS Fargate
    Wednesday, 4pm, Aria
    Thursday, 1:45pm, MGM
    Introducing
    Serverless Kubernetes
    Amazon EKS for AWS Fargate

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  16. Fargate Spot
    Spare capacity with savings
    up to 70% off of Fargate
    standard pricing
    ECS Capacity
    Providers
    Preview: Amazon
    ECS CLI 2.0
    ECS Cluster
    Autoscaling
    Improved scalability,
    reduced operational cost to
    run containers
    Containers
    New Features
    Accelerating momentum for AWS container services

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  17. Build and maintain secure OS images more quickly & easily
    Introducing
    DRAFT
    Compute
    General Availability – December 3
    EC2 Image Builder

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  18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  19. AWS Outposts
    Fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any
    connected customer site. Truly consistent hybrid experience for applications across on-premises and
    cloud environments. Ideal for low latency or local data processing application needs.
    Same AWS-designed infrastructure
    as in AWS regional data centers
    (built on AWS Nitro System)
    delivered to customer facilities
    Fully managed, monitored, and
    operated by AWS
    as in AWS Regions
    Single pane of management
    in the cloud providing the
    same APIs and tools as
    in AWS Regions
    Compute
    LEARN MORE
    CMP302-R: AWS Outposts: Extend the AWS experience to on-premises
    environments

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  20. AWS Outposts
    Amazon EC2
    Amazon EBS
    Amazon ECS
    Amazon EKS
    Amazon EMR
    Amazon VPC
    Amazon RDS
    Amazon S3

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  21. Local Zones
    Introducing
    Extend the AWS Cloud to more locations and closer to your end-users
    to support ultra low latency application use cases. Use familiar AWS
    services and tools and pay only for the resources you use.
    DRAFT
    Compute
    The first Local Zone to be released will be located in Los Angeles.

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  22. AWS Wavelength
    Introducing
    Embeds AWS compute and storage inside telco providers’ 5G
    networks. Enables mobile app developers to deliver applications with
    single-digit millisecond latencies. Pay only for the resources you use.
    DRAFT
    Compute
    Announcement

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  23. AWS Wavelength
    Introducing
    Embeds AWS compute and storage inside telco providers’ 5G
    networks. Enables mobile app developers to deliver applications with
    single-digit millisecond latencies. Pay only for the resources you use.
    DRAFT
    Compute
    Announcement

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  24. Container Support for AWS IoT Greengrass
    New Feature
    DRAFT
    Internet of Things
    Deploy containers seamlessly to edge devices
    Move containers from the cloud
    to edge devices using AWS IoT
    Greengrass, without rewriting
    any code.
    Enables both Docker & AWS
    Lambda components to
    operate seamlessly together at
    the edge
    Use AWS IoT Greengrass Secrets
    Manager to manage credentials
    for private container registries.

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  25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  26. Amazon S3 Access Points
    Introducing
    Simplify managing data access at scale for applications using shared data
    sets on Amazon S3. Easily create hundreds of access points per bucket,
    each with a unique name and permissions customized for each application.
    DRAFT
    Storage

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  27. 31

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  28. EBS Direct APIs for Snapshots
    Introducing
    A simple set of APIs that provide access to directly read EBS snapshot data, enabling backup providers
    to achieve faster backups for EBS volumes at lower costs.
    L E A R N M O R E CMP305-R: Amazon EBS snapshots: What’s new, best practices, and security
    Up to 70% faster
    backup times
    More granular recovery
    point objectives (RPOs)
    Lower cost backups
    Compute
    Easily track incremental
    block changes on EBS
    volumes to achieve:
    https://aws.amazon.com/blogs/aws/new-programmatic-access-to-ebs-snapshot-content/

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  29. Increased EBS Bandwidth
    All new C5, M5, R5 (also with d,n capabilities) and P3dn
    support 36% higher EBS-optimized instance bandwidth, up
    to 19 Gbps.
    33
    https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-optimized.html
    Based on new Nitro Systems

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  30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  31. Amazon Managed Apache Cassandra Service
    Introducing
    A scalable, highly available, and serverless Apache Cassandra–compatible
    database service. Run your Cassandra workloads in the AWS cloud using the
    same Cassandra application code and developer tools that you use today.
    Apache Cassandra-
    compatible
    Performance
    at scale
    Highly available
    and secure
    No servers
    to manage
    DRAFT
    Databases
    Preview – December 3
    LEARN MORE DAT324: Overview of Amazon Managed Apache Cassandra Service

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  32. Amazon RDS Proxy
    Introducing
    Fully managed, highly available database proxy feature for Amazon
    RDS. Pools and shares connections to make applications more
    scalable, more resilient to database failures, and more secure.
    DRAFT
    Databases
    Public Beta – December 3
    LEARN MORE DAT368: Setting up database proxy servers with RDS Proxy

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  33. UltraWarm for Amazon Elasticsearch Service
    Introducing
    A performance-optimized warm storage tier for Amazon Elasticsearch Service.
    Store up to 10 PB of data in a single cluster at 1/10th the cost of existing
    storage tiers, while still providing an interactive experience for analyzing logs.
    Less expensive storage for older and less-frequently accessed data while still
    providing an interactive analytics experience.
    DRAFT
    Analytics
    Public Beta – December 3
    LEARN MORE ANT229: Scalable, secure, and cost-effective log analytics

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  34. DRAFT
    Analytics
    Amazon Redshift RA3 instances with Managed Storage
    Optimize your data warehouse costs by paying for compute and storage separately
    General Availability – December 3
    L E A R N M O R E
    ANT213-R1: State of the Art Cloud Data Warehousing
    ANT230: Amazon Redshift Reimagined: RA3 and AQUA
    Wednesday, 10am, Venetian
    2x perf of DS2, up to 8PB (compressed)
    COMPUTE NODE
    (RA3/i3en)
    SSD Cache
    S3 STORAGE
    COMPUTE NODE
    (RA3/i3en)
    SSD Cache
    COMPUTE NODE
    (RA3/i3en)
    SSD Cache
    COMPUTE NODE
    (RA3/i3en)
    SSD Cache
    Managed storage
    $/node/hour
    $/TB/month
    Introducing

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  35. AQUA (Advanced Query Accelerator) for Amazon Redshift
    Introducing
    Redshift runs 10x faster than any other cloud data warehouse without increasing cost
    DRAFT
    Analytics
    Private Beta – December 3
    LEARN MORE ANT230: Amazon Redshift Reimagined: RA3 and AQUA Wednesday, 10am, Venetian
    AQUA brings compute to storage so data doesn't have
    to move back and forth
    High-speed cache on top of S3 scales out to process
    data in parallel across many nodes
    AWS designed processors accelerate data compression,
    encryption, and data processing
    100% compatible with the current version of Redshift
    S3
    STORAGE
    AQUA
    ADVANCED QUERY ACCELERATOR
    RA3 COMPUTE CLUSTER

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  36. Amazon Redshift Federated Query
    Analyze data across data warehouse, data lakes, and operational
    database
    New Feature
    DRAFT
    Analytics
    Public Beta – December 3
    LEARN MORE ANT213-R1: State of the Art Cloud Data Warehousing Tuesday, 3pm, Bellagio

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  37. Amazon Redshift Data Lake Export
    New Feature
    No other data warehouse makes it as easy to gain new insights from
    all your data.
    format optimized for analytics
    Apache Parquet
    Amazon EMR, Amazon Athena,
    and Amazon SageMaker
    DRAFT
    Analytics
    General Availability – December 3
    LEARN MORE
    ANT335R: How to build your data analytics stack at scale with Amazon
    Redshift
    Monday, 7pm, Venetian
    Tuesday, 11:30am, Aria

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  38. Amazon Managed Streaming for
    Apache Kafka
    42
    Scale up to 100s of brokers
    per MSK cluster
    Open monitoring with Prometheus
    Fully managed Flink applications for Kafka
    New Feature
    Announced:
    MSK in-place version upgrades,
    T Instances, CloudWatch broker
    logs, SASL
    Analytics

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  39. AWS Data Exchange
    Quickly find diverse data
    in one place
    Efficiently access
    3rd-party data
    Easily analyze data
    Reach millions of
    AWS customers
    Easiest way to package and
    publish data products
    Built-in security and
    compliance controls
    For
    Subscribers
    For
    Providers
    DRAFT
    Analytics
    Announced – November 13
    L E A R N M O R E
    ANT238-R: AWS Data Exchange: Easily find & subscribe to third-party
    data in the cloud
    Thursday, 2:30pm, Venetian
    Easily find and subscribe to 3rd-party data in the cloud

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  40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  41. Amazon Detective
    Introducing
    Quickly analyze, investigate, and identify the root cause of security
    findings and suspicious activities.
    Automatically distills
    & organizes VPC,
    Cloud Trail, Guard
    Duty data into a graph
    model
    Easy to use visualizations
    for faster & effective
    investigation
    Continuously updated as
    new telemetry becomes
    available
    Preview – December 3
    DRAFT
    Security
    LEARN MORE SEC312: Introduction to Amazon Detective Thursday, 1:45pm, Venetian

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  42. AWS IAM Access Analyzer
    Introducing
    Continuously ensure that policies provide the intended public and cross-account access
    to resources, such as Amazon S3 buckets, AWS KMS keys, & AWS Identity and Access
    Management roles.
    Permissions are actually used over time?
    Remove unnecessary permissions.
    Organzitaions master account:
    Service last accessed data for root and OUs and accounts
    General Availability – December 2
    DRAFT
    Security
    LEARN MORE SEC309: Deep Dive into AWS IAM Access Analyzer Thursday, 3:15pm, Venetian

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  43. Existing Service
    DRAFT
    Networking
    Scale connectivity across thousands
    of Amazon VPCs, AWS accounts,
    and on-premises networks
    Amazon VPC
    Amazon VPC
    Amazon VPC
    Amazon VPC
    Customer
    gateway
    VPN
    connection
    AWS Direct
    Connect Gateway
    L E A R N M O R E NET203-L Leadership Session Networking Wednesday, 11:30am, MGM
    AWS Transit Gateway

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  44. New Feature
    AWS Transit Gateway Inter-Region Peering
    General Availability – December 3
    DRAFT
    Networking
    Encrypt no single point of
    failure or bandwidth bottleneck
    AWS TRANSIT
    GATEWAY
    Inter-Region Peering
    Build global networks by connecting transit gateways across multiple AWS Regions
    L E A R N M O R E NET203-L Leadership Session Networking Wednesday, 11:30am, MGM

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  45. High availability and improved performance of site-to-site VPN
    New Feature
    AWS Accelerated Site-to-Site VPN
    General Availability – December 3
    DRAFT
    Networking
    L E A R N M O R E NET203-L Leadership Session Networking Wednesday, 11:30am, MGM
    AWS Global Accelerator to route traffic from your on-premises network to an edge
    location that is closest to your CGW using two static IPv4 anycast addresses

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  46. AWS Transit Gateway Network Manager
    Introducing General Availability – December 3
    DRAFT
    Networking
    L E A R N M O R E NET212 - AWS Transit Gateway Network Manager

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  47. New Feature
    Transit Gateway Multicast General Availability – December 3
    DRAFT
    Networking
    multicast applications
    grain control
    Build and deploy multicast applications in the cloud
    L E A R N M O R E NET203-L Leadership Session Networking Wednesday, 11:30am, MGM

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  48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  49. L E A R N M O R E SVS401 - Optimizing your serverless applications
    Wednesday, 1:45pm, Mirage
    Thursday, 3:15pm, Venetian
    Provisioned Concurrency on AWS Lambda
    New Feature
    • Keeps functions initialized and hyper-ready, ensuring
    start times stay in the milliseconds
    • Builders have full control over when provisioned
    concurrency is set
    • No code changes are required to provision concurrency
    on functions in production
    • Can be combined with AWS Auto Scaling at launch
    DRAFT
    Serverless
    General Availability – December 3

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  50. Your feedback for REST APIs: Faster, cheaper, more features!
    HTTP APIs: low-latency, cost-effective AWS Lambda proxy and HTTP proxy APIs.
    67% cost reduction, 50% latency reduction compared to REST APIs.
    HTTP APIs for Amazon API Gateway
    Introducing
    DRAFT
    Mobile Services
    Preview – December 4
    L E A R N M O R E
    CON213-L - Leadership session: Using containers and serverless to
    accelerate modern application development (incl schema registry demo)
    Wednesday 9:15am, Venetian
    https://docs.aws.amazon.com/apigateway/latest/developerguide/http-api-vs-rest.html
    $1.00/million request vs $3.50 for REST API

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  51. AWS Step Functions Express Workflows
    Introducing
    Orchestrate AWS compute, database, and messaging services at rates
    greater than 100,000 events/second, suitable for high-volume event
    processing workloads such as IoT data ingestion, streaming data
    processing and transformation.
    DRAFT
    App Integration
    General Availability – December 3
    L E A R N M O R E API321: Event-Processing Workflows at Scale with AWS Step Functions Wednesday, 3:15pm, MGM

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  52. Amazon EventBridge Schema Registry
    Introducing
    Store event structure - or schema - in a shared central location, so it’s
    faster and easier to find the events you need. Generate code bindings
    right in your IDE to represent an event as an object in code.
    DRAFT
    App Integration
    Preview – December 3
    LEARN MORE
    CON213-L - Leadership session: Using containers and serverless to
    accelerate modern application development (incl schema registry demo)
    Wednesday 9:15am,
    Venetian

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  53. Amplify for iOS & Android
    Introducing
    DRAFT
    Mobile Services
    General Availability – December 3
    Open source libraries and toolchain that enable mobile developers to
    build scalable and secure cloud powered serverless applications.
    L E A R N M O R E MOB317 - Speed up native mobile development with AWS Amplify Wednesday, 11:30am, Venetian

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  54. Amplify DataStore
    New Feature
    DRAFT
    Mobile Services
    General Availability – December 3
    Multi-platform (iOS/Android/React Native/Web) on-device persistent
    storage engine that automatically synchronizes data between
    mobile/web apps and the cloud using GraphQL.
    L E A R N M O R E MOB402: Build data-driven mobile and web apps with AWS AppSync Wednesday, 2:30pm, Mirage

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  55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  56. Deep Graph Library
    https://www.dgl.ai
    • Python open source library that helps
    researchers and scientists quickly build,
    train, and evaluate Graph Neural Networks
    on their data sets
    • Use cases: recommendation, social
    networks, life sciences, cybersecurity, etc.
    • Available in Deep Learning Containers
    • PyTorch and Apache MXNet, TensorFlow coming soon
    • Available for training on Amazon
    SageMaker

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  57. Deep Java Library
    https://www.djl.ai
    • Java open source library,
    to train and deploy models
    • Framework agnostic
    • Apache MXNet for now, more will come
    • Train your own model, or use a
    pretrained one from the model
    zoo

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  58. Builders‘ Library https://aws.amazon.com/builders-library

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  59. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  60. VISION SPEECH TEXT SEARCH NEW CHATBOTS PERSONALIZATION FORECASTING FRAUD NEW DEVELOPMENT NEW CONTACT CENTERS NEW
    Amazon SageMaker Ground
    Truth
    Augmented
    AI
    SageMaker
    Neo
    Built-in
    algorithms
    SageMaker
    Notebooks NEW
    SageMaker
    Experiments NEW
    Model
    tuning
    SageMaker
    Debugger NEW
    SageMaker
    Autopilot NEW
    Model
    hosting
    SageMaker
    Model Monitor NEW
    Deep Learning
    AMIs & Containers
    GPUs &
    CPUs
    Elastic
    Inference
    Inferentia
    (Inf2)
    FPGA
    Amazon
    Rekognition
    Amazon
    Polly
    Amazon
    Transcribe
    +Medical
    Amazon
    Comprehend
    +Medical
    Amazon
    Translate
    Amazon
    Lex
    Amazon
    Personalize
    Amazon
    Forecast
    Amazon
    Fraud Detector
    Amazon
    CodeGuru
    AI SERVICES
    ML SERVICES
    ML FRAMEWORKS & INFRASTRUCTURE
    Amazon
    Textract
    Amazon
    Kendra
    Contact Lens
    For Amazon Connect
    SageMaker Studio IDE NEW
    NEW
    AWS Machine Learning stack
    NEW

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  61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  62. Pre:Invent highlights
    https://aws.amazon.com/about-aws/whats-new/machine-learning
    • Amazon Comprehend: 6 new languages
    • Amazon Translate: 22 new languages
    • Amazon Transcribe: 15 new languages, alternative transcriptions
    • Amazon Lex: SOC compliance, sentiment analysis,
    web & mobile integration with Amazon Connect
    • Amazon Personalize: batch recommendations
    • Amazon Forecast: use any quantile for your predictions
    With region expansion across the board!

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  63. Introducing Amazon Transcribe Medical
    Easy-to-Use
    Accurate Affordable

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  64. AWS Rekognition

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  65. Introducing Amazon Rekognition Custom Labels
    • Import images labeled by Amazon
    SageMaker Ground Truth…
    • Or label images automatically based on folder structure
    • Train a model on fully managed
    infrastructure
    • Split the data set for training and validation
    • See precision, recall, and F1 score at the end of training
    • Select your model
    • Use it with the usual Rekognition APIs

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  66. Introducing Amazon Fraud Detector
    A fraud detection service that makes
    it easy for businesses to use machine
    learning to detect online fraud in
    real-time, at scale

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  67. Amazon Fraud Detector – Key Features
    Pre-built fraud
    detection model
    templates
    Automatic
    creation of
    custom fraud
    detection
    models
    Models learn
    from past
    attempts to
    defraud Amazon
    Amazon
    SageMaker
    integration
    One interface to
    review past
    evaluations and
    detection logic

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  68. Introducing Contact Lens For Amazon Connect
    Theme
    detection
    Built-in automatic
    call transcription
    Automated
    contact
    categorization
    Enhanced
    Contact Search
    Real-time sentiment
    dashboard
    and alerting
    Presents
    recurring
    issues based
    on
    Customer
    feedback
    Identify call types
    such as script
    compliance,
    competitive
    mentions,
    and cancellations.
    Filter calls of
    interest based
    on words
    spoken and
    customer
    sentiment
    View entire call
    transcript directly in
    Amazon Connect
    Quickly identify
    when customers
    are having a
    poor experience
    on live calls
    Easily use the power of machine learning to improve the quality of your customer experience
    without requiring any technical expertise

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  70. Introducing AWS CodeGuru
    Built-in code reviews
    with intelligent
    recommendations
    Detect and
    optimize expensive
    lines of code
    Identify latency and
    performance
    improvements
    CodeGuru Reviewer CodeGuru Profiler
    Write + Review Build + Test Deploy Measure Improve

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  71. CodeGuru Reviewer: How It Works
    Input:
    Source Code
    Feature Extraction Machine Learning
    Output:
    Recommendations
    Customer provides source
    code as input
    Java
    AWS CodeCommit
    Github
    Extract semantic features /
    patterns
    ML algorithms identify similar
    code for comparison
    Customers see
    recommendations as Pull
    Request feedback

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  72. CodeGuru Example – Looping vs Waiting
    do {
    DescribeTableResult describe = ddbClient.describeTable(new DescribeTableRequest().withTableName(tableName));
    String status = describe.getTable().getTableStatus();
    if (TableStatus.ACTIVE.toString().equals(status)) {
    return describe.getTable();
    }
    if (TableStatus.DELETING.toString().equals(status)) {
    throw new ResourceInUseException("Table is " + status + ", and waiting for it to become ACTIVE is not useful.");
    }
    Thread.sleep(10 * 1000);
    elapsedMs = System.currentTimeMillis() - startTimeMs;
    } while (elapsedMs / 1000.0 < waitTimeSeconds);
    throw new ResourceInUseException("Table did not become ACTIVE after ");
    This code appears to be waiting for a resource before it runs. You could use the waiters feature to help improve
    efficiency. Consider using TableExists, TableNotExists. For more information,
    see https://aws.amazon.com/blogs/developer/waiters-in-the-aws-sdk-for-java/
    Recommendation
    Code
    We should use waiters instead - will help remove a lot of this code.
    Developer Feedback

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  73. CodeGuru Profiler: How It Works
    Input:
    Live application stack
    trace
    Application profile
    sampling
    Pattern matching
    Output:
    Method names,
    Recommendations
    and searchable
    visualizations
    Customer application
    runs in production
    CodeGuru Profiler
    continuously captures
    application stack trace
    information
    CodeGuru Profiler detects
    performance inefficiencies in
    the live application
    Customers see
    recommendations in their
    automated efficiency reports
    and visualizations
    Amazon Confidential

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  74. CodeGuru Profiler – Example

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  75. LOWER COST
    INCREASE IN CPU UTILIZATION
    AMAZON PRIME DAY 2017 VS 2018

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  76. Employees spend 20% of their
    time looking for information.
    —McKinsey
    20%
    44%
    44% of the time, they cannot
    find the information they need to
    do their job.
    —IDC

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  77. Introducing Kendra
    Easy to find what you are
    looking for
    Fast search, and
    quick to set up
    Native connectors
    (S3, Sharepoint,
    file servers,
    HTTP, etc.)
    Natural language
    Queries
    NLU and
    ML core
    Simple API
    and console
    experiences
    Code samples
    Incremental
    learning through
    feedback
    Domain
    Expertise

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  78. Kendra connectors
    …and more coming in 2020

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  79. View Slide

  80. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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  81. Fully managed
    infrastructure in SageMaker
    Amazon SageMaker Operators for Kubernetes
    Kubernetes customers can now train, tune, & deploy models in
    Amazon SageMaker
    $ kubectl apply -f training.yaml
    trainingjob.sagemaker.aws.amazon.com/tf-mnist created

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  82. Amazon SageMaker Studio
    The first fully integrated development environment (IDE) for machine learning
    Organize, track, and
    compare thousands of
    experiments
    Easy experiment
    management
    Share scalable notebooks
    without tracking code
    dependencies
    Collaboration at
    scale
    Get accurate models for
    with full visibility & control
    without writing code
    Automatic model
    generation
    Automatically debug errors,
    monitor models, & maintain
    high quality
    Higher quality ML
    models
    Code, build, train, deploy, &
    monitor in a unified visual
    interface
    Increased
    productivity

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  83. View Slide

  84. Amazon SageMaker Notebooks
    Access your notebooks in
    seconds with your corporate
    credentials
    Fast-start shareable notebooks
    Administrators manage
    access and permissions
    Share your notebooks
    as a URL with a single click
    Dial up or down
    compute resources
    Start your notebooks
    without spinning up
    compute resources
    https://aws.amazon.com/about-aws/whats-new/2019/12/introducing-the-new-amazon-sagemaker-notebook-experience-now-in-preview/

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  85. Amazon SageMaker Processing
    Analytics jobs for data processing and model evaluation
    Use SageMaker’s built-in
    containers or bring your own
    Bring your own script for
    feature engineering
    Custom processing
    Achieve distributed
    processing for clusters
    https://aws.amazon.com/blogs/aws/amazon-sagemaker-processing-fully-managed-data-processing-and-model-evaluation/
    New Python SDK that lets data scientists and ML engineers easily run preprocessing,
    postprocessing and model evaluation workloads on Amazon SageMaker.

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  86. Amazon SageMaker Experiments
    Experiment
    tracking at scale
    Visualization for
    best results
    Flexibility with
    Python SDK & APIs
    Iterate quickly
    Track parameters & metrics
    across experiments & users
    Organize
    experiments
    Organize by teams, goals, &
    hypotheses
    Visualize & compare
    between experiments
    Log custom metrics &
    track models using APIs
    Iterate & develop high-
    quality models
    A system to organize, track, and evaluate training experiments
    Python SDK for logging and analytics: Create experiments, populate them with
    trials, and run analytics across trials and experiments for HPO and AutoML

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  87. View Slide

  88. Introducing Amazon SageMaker Autopilot
    Quick to start
    Provide your data in a
    tabular form & specify target
    prediction
    Automatic
    model creation
    Get ML models with feature
    engineering & automatic model
    tuning automatically done
    Visibility & control
    Get notebooks for your
    modelswith source code
    Automatic model creation with full visibility & control
    Recommendations &
    Optimization
    Get a leaderboard & continue
    to improve your model
    Autopilot Workshop from re:Invent: https://gitlab.com/juliensimon/aim361

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  89. Models Drift

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  90. Introducing Amazon SageMaker Model Monitor
    Automatic data
    collection
    Continuous
    Monitoring
    CloudWatch
    Integration
    Data is automatically
    collected from your
    endpoints
    Automate corrective
    actions based on Amazon
    CloudWatch alerts
    Continuous monitoring of models in production
    Visual
    Data analysis
    Define a monitoring
    schedule and detect
    changes in quality against
    a pre-defined baseline
    See monitoring results,
    data statistics, and
    violation reports in
    SageMaker Studio
    Flexibility
    with rules
    Use built-in rules to
    detect data drift or write
    your own rules for
    custom analysis

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  91. Ground
    Truth
    Algorithms
    & Frameworks
    Collaborative
    notebooks
    Experiments
    Distributed
    Training &
    Debugger
    Deployment,
    Monitoring, & Hosting
    SageMaker AutoPilot
    Build, Train, Deploy Machine Learning Models Quickly at Scale
    Reinforcement
    Learning
    Tuning
    & Optimization
    SageMaker Studio
    Marketplace
    for ML
    Amazon SageMaker

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  92. Automatic data
    analysis
    Relevant data
    capture
    Automatic error
    detection
    Improved productivity
    with alerts
    Visual analysis
    and debug
    Introducing Amazon SageMaker Debugger
    Analyze and debug data
    with no code changes
    Data is automatically
    captured for analysis
    Errors are automatically
    detected based on rules
    Take corrective action based
    on alerts
    Visually analyze & debug
    from SageMaker Studio
    Analysis & debugging, explainability, and alert generation

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  93. AWS DeepRacer improvements
    • AWS DeepRacer Evo
    • Stereo camera
    • LIDAR sensor
    • New racing opportunities
    • Create your own races
    • Object Detection & Avoidance
    • Head-to-head racing

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  94. AWS DeepComposer
    • The world’s first machine
    learning-enabled musical
    keyboard
    • Compose music using Generative
    Adversarial Networks (GAN)
    • Use a pretrained model, or train
    your own

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  95. https://medium.com/@frank.munz

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  96. frankmunz
    @frankmunz https://medium.com/@frank.munz
    (Blog)
    https://speakerdeck.com/fmunz
    (Slides)
    Thank You!

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