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re:Invent 2021 re:Cap – Part II

re:Invent 2021 re:Cap – Part II

AWS User Group Ireland, February 3rd, 2021

Analytics
Databases
AI/ML
IoT

Danilo Poccia

February 03, 2022
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  1. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Danilo Poccia
    AWS Chief Evangelist (EMEA)
    @danilop
    PART II

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  2. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Agenda
    Analytics
    Databases
    AI/ML
    IoT

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  3. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Analytics

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  4. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Data Exchange for APIs
    RESTful or GraphQL API calls directly to AWS Data
    Exchange
    Use the AWS SDK in the programming language of
    your choice.
    Manage API access centrally with AWS Identity and
    Access Management (IAM)

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  5. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Granular access control
    Define row- and cell-level access policies on
    both governed and traditional Amazon S3
    tables. Manage and consistently enforce
    policies in a single place.
    Governed tables
    A new type of Amazon S3 table that allows
    you to ingest and manage data at scale, easily
    and reliably.
    Storage optimization
    Automatically optimize how data is stored to
    improve query performance as data volume
    increases.
    A new storage API to simplify
    how data is ingested, stored,
    and managed, together with
    row-level security to protect
    your data
    AWS Lake Formation Governed Tables

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  6. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    New storage API that solves for those key challenges
    7
    Fine-grained
    access controls
    Simple to ingest
    and manage data
    Integration APIs
    Define column-, row-, and cell-
    level permissions in a single
    place and enforce them
    consistently across AWS native
    and third-party tools
    Ingest streaming and batch data
    with ACID transactions
    Automatic small file compaction
    and data management
    Unified data access APIs make it
    easy to securely integrate your
    applications and tools with data
    in the data lake

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  7. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon Athena ACID transactions
    Write, delete, update, and time travel operations
    Enables concurrent users to make row-level
    modifications to Amazon S3 data
    Use Athena's console, API, and ODBC and JDBC
    drivers
    Use ACID transactions either on Lake Formation
    Governed tables, or using the Apache Iceberg table
    format

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  8. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon Athena Engine Upgrade
    Queries up to 3x faster
    Up to 70% cost savings

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  9. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Faster time to market
    Don’t worry about data warehouse management
    Pay for what you use
    Compute provisioning
    Automated patching
    Routine maintenance
    Backup and recovery
    Automatic scaling
    Automatic failover
    Security and industry compliance
    Advanced monitoring
    YOU
    focus on insights
    takes care of the rest
    Automatically provisions and scales data warehouse capacity

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  10. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon Redshift Serverless – Easy Start Experience
    Activate Amazon
    Redshift Serverless for
    your AWS account
    Connect from your
    favorite BI tool or Amazon
    Redshift Query Editor
    BI tool
    Developer and
    business analyst Load data seamlessly and
    Amazon Redshift executes
    queries by automatically
    provisioning capacity
    Amazon Redshift
    Pay for compute and
    storage used during analysis
    Pay
    Easy to get started
    SQL features Performance at scale Security
    Scalability Analyze all your data
    No compromises

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  11. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Redshift Materialized views auto refresh & query rewrite
    S P E E D U P Q U E R Y P E R F O R M A N C E B Y O R D E R S O F M A G N I T U D E W I T H P R E C O M P U T E D R E S U L T S
    item store cust price
    i1 s1 c1 12.00
    i2 s2 c1 3.00
    i3 s2 c2 7.00
    store owner loc
    s1 Joe SF
    s2 Ann NY
    s3 Lisa SF
    loc total_sales
    SF 12.00
    NY 10.00
    sales store_info
    loc_sales
    Simplify and accelerate iterative and predictable
    workloads, such as ETL, BI/dashboarding queries
    MVs can be based on one or more Amazon Redshift
    tables or external tables (Spectrum, Federated)
    Efficient incremental maintenance
    Scheduled, automatic, or manually timed refresh
    Amazon Redshift auto query rewrite optimizes queries
    by replacing native tables with materialized views
    “The Amazon Redshift materialized view auto query rewrite feature reduced dashboard load times from 8 minutes to just
    500 ms. The best part is that this is completely transparent for Tableau and the business user.”
    —Arman Nasrollahi, Home24

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  12. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Redshift Query Editor v2 – Notebook Support
    Data users engaging in advanced analytics work on
    multiple queries at a time to perform various tasks
    for their data analysis.
    organize related queries by saving them together
    in a folder, or combining them into a single saved
    query with multiple statements.
    The Notebooks support provides an alternative
    way to embed all queries required for a complete
    data analysis in a single document using SQL cells.
    You can share your Notebooks with team
    members, similar to how you share your saved
    queries in Query Editor V2. Documenting your
    work precisely enables further collaboration with
    other users.

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  13. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon
    EMR
    Serverless
    Easily run petabyte-scale data analytics in the cloud without
    managing, tuning, optimizing, securing, and operating clusters
    Quickly run large-scale applications that use open-source
    frameworks of your choice, including Spark, Hive, and Presto
    Automatically scale resources up and down as needed based on
    the changing requirements of your application
    Pay only for the resources you use for data analytics at scale

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  14. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Easily run Apache Kafka clusters without rightsizing
    cluster capacity
    Instantly scale I/O without worrying about scaling
    capacity up and down or reassigning partitions
    Pay for the data volume you stream and retain
    Amazon MSK Serverless

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  15. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Simple to use
    Simplify streaming data processing by eliminating capacity management
    Flexible scaling
    Automatically scale capacity in response to changing data volumes
    Automated high availability
    Provide built-in availability and fault tolerance by default
    Lower your costs
    Pay per gigabyte of data written, read, and stored
    Amazon Kinesis Data Streams on demand

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  16. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AWS Glue Autoscaling
    Cost =
    f(compute)
    t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11
    Without Autoscaling With Autoscaling
    Job execution timeline
    List operation
    Wide transform
    Uneven distribution of
    data partitions
    AWS Glue job Tear-down
    Setup
    Potential
    savings
    Preview

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  17. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Streaming Autoscaling (preview)
    Cost =
    f(compute)
    t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11
    Without Autoscaling With Autoscaling
    Job execution timeline
    Low stream
    activity Peak streaming
    record arrival rate
    Scale down as stream
    activity decreases
    Glue job Tear-down
    Setup
    Potential
    Savings
    Initial
    scale up
    Scale down to match
    stream activity

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  18. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AWS Glue Studio Notebook (Preview)
    Interactive AWS Glue
    jobs development
    Submit AWS Glue jobs from the
    AWS Glue Studio notebook
    Use notebook magic to define
    transforms in SQL and control cost
    Built-in monitoring support
    Preview

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  19. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AWS Glue Interactive Sessions
    Development
    tool of your
    choice
    Rapid
    development
    Built-in cost
    control
    Preview
    A dedicated cluster created in seconds for developers to
    interactively build data pipelines with choice of IDE…

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  20. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    … and advanced transforms like PII detection for
    advanced cleansing
    Scan Data Detect Entities Remeditate
    1 2 3
    Full Scan
    Sample Scan
    Built-in Entities
    (e.g. SSN, passport)
    Custom Entities
    Store results
    Redact/mask
    results

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  21. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    How does PII Detection work Preview
    Entities to detect
    Remediation
    Full Scan Sample Scan

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  22. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Databases

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  23. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon RDS Custom
    Amazon RDS Custom is a
    managed database service for
    legacy, custom, and packaged
    applications that require
    access to the underlying
    operating system and
    database environment
    Amazon RDS Custom is
    available for RDS for Oracle
    and for SQL Server

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  24. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    ML-powered database advisor for Amazon RDS
    First released for Amazon Aurora
    Delivers insights and recommendations to help resolve issues in minutes
    Uses ML models informed by years of operating thousands of databases for
    Amazon.com
    Automatically detects and diagnoses hard-to-find performance bottlenecks and
    operational issues
    Continuously monitors database workloads at scale
    No ML experience required
    Amazon DevOps Guru for RDS

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  25. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon DynamoDB Standard-
    Infrequent Access (Standard-IA)
    table class
    The Standard-IA table class
    offers 60% lower storage
    costs than DynamoDB
    Standard tables.
    Standard-IA tables offer the
    same performance, durability,
    data availability, and massive
    scalability as existing
    DynamoDB Standard tables.
    Switch between table classes
    with a single click in the
    DynamoDB console, or using
    the AWS CLI or AWS SDK.
    Also, use the same DynamoDB
    APIs and service endpoints.
    Lower storage costs No performance trade-offs No developer overhead

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  26. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    What’s new in Amazon Timestream
    R E A L - T I M E A N A L Y T I C S A R E O R D E R S O F M A G N I T U D E F A S T E R A N D C H E A P E R
    Multi-measure records
    Scheduled queries
    Magnetic store writes
    • A new data modeling capability for cost-effective data storage, performant data access, and ease of
    use
    • Store multiple measurements and events in a single table row, instead of storing one measure per
    table row
    • Improve query performance and reduce costs by an order of magnitude
    • Fully managed, serverless, and scalable solution for calculating and storing aggregates, rollups, and
    other real-time analytics typically used to power dashboards, business reports, and other applications
    • Simply define the computation/query to precompute and its schedule. Amazon Timestream will
    automatically and periodically run the queries and reliably write the results into a separate table.
    • Flexible and cost-effective solution for late-arriving data
    • Ability to ingest data directly into the magnetic store
    • As you ingest data, Amazon Timestream will automatically determine whether the data gets written to
    the memory store or the magnetic store, based on the timestamp of the data and the configured data
    retention window for the memory and magnetic stores

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  27. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS DMS Fleet Advisor
    A C C E L E R A T E D A T A B A S E A N D A N A L Y T I C S M I G R A T I O N S W I T H A U T O M A T E D
    I N V E N T O R Y A N D M I G R A T I O N R E C O M M E N D A T I O N S
    Generates a list of
    possible migration
    targets
    Automatically
    gathers
    database fleet
    information
    Results in hours
    instead of weeks
    and months

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  28. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Database Migration Service – Time Travel
    Store and encrypt AWS DMS logs using Amazon S3,
    and view, download and obfuscate the logs within a
    certain time frame
    Log and debug replication tasks
    Time Travel can be used in all AWS Regions with
    DMS-supported PostgreSQL source endpoints and
    DMS-supported PostgreSQL and MySQL target
    endpoints

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  29. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AI/ML

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  30. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    The AWS ML Stack

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  31. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    The AWS ML Stack

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  32. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon EC2 Trn1 Instances for ML Training
    • Training larger models requires an increase in
    compute power, which also increases costs
    • Increasing costs become a barrier to
    innovation and growth
    INCREASING ML COMPLEXITY
    • Businesses need higher precision in their model
    predictions
    • Larger and more complex models result in
    more frequent retraining
    INCREASING TRAINING COSTS

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  33. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon EC2 Trn1 Instances for ML Training
    16 AWS Trainium chips,
    purpose-built for
    deep learning training
    Most cost efficient for large-
    scale distributed training
    AWS Neuron SDK integrated
    with TensorFlow
    and PyTorch
    Deployed in Amazon EC2 UltraClusters
    with tens of thousands of Trainium
    chips and petabit-scale networking
    800 Gbps networking and ultra-
    highspeed interconnect between
    accelerators
    Fastest ML training in the cloud

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  34. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    The AWS ML Stack

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  35. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker Notebooks
    P E R F O R M D A T A E N G I N E E R I N G , A N A L Y T I C S , A N D M L W O R K F L O W S I N O N E N O T E B O O K
    Discover, manage, create, terminate, and
    connect to Amazon EMR clusters
    Interactively access, transform, and analyze a
    wide range of data
    Build, train, and deploy models using
    your preferred framework
    Amazon SageMaker

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  36. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker Training Compiler
    A C C E L E R A T E T H E T R A I N I N G O F D E E P L E A R N I N G M O D E L S
    Training compiler
    Accelerate training times by up to 50% through more
    efficient use of GPUs
    Reduce training costs
    Save time and money associated with training
    Integrated with existing frameworks
    Use familiar framework APIs with minimal code
    changes
    Amazon SageMaker

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  37. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker Inference Recommender
    A C C E L E R A T E T H E D E P L O Y M E N T O F M O D E L E N D P O I N T S
    Automatic deployment recommendations
    Optimal instance type/count and container
    parameters
    Reduce inference costs
    Receive endpoint configuration recommends for best
    price performance
    Fully managed load testing
    Run and review fully managed load tests on a set of
    instance types to evaluate performance and trade-offs
    Amazon SageMaker

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  38. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon SageMaker Serverless Inference
    D E P L O Y M L M O D E L S F O R I N F E R E N C E W I T H O U T C O N F I G U R I N G O R M A N A G I N G U N D E R L Y I N G I N F R A S T R U C T U R E
    Optimize for intermittent or unpredictable workloads
    Automatic and fast scaling when usage is required
    Pay per use
    Pay only for the resources consumed, not idle time
    Fully managed
    Underlying infrastructure, security, patching,
    monitoring and logging is all managed
    Amazon SageMaker

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  39. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker MLOps
    T R A C K , A S S E S S , A N D M O N I T O R Y O U R M L M O D E L S
    Improved lineage management
    Retrieve all ML lineage across accounts and in a single
    query, from data to endpoint
    Model quality and bias detection in workflows
    SageMaker Model Monitor and SageMaker Clarify
    integrated into SageMaker Pipeline workflows
    Monitor endpoints from SageMaker Model Registry
    Track endpoints, custom metadata, and model metrics
    Amazon SageMaker

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  40. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker Ground Truth Plus
    D E L I V E R H I G H - Q U A L I T Y T R A I N I N G D A T A S E T S F A S T A N D R E D U C E D A T A L A B E L L I N G C O S T S
    Increase data quality through
    ML-powered data labeling
    Access expert data labelers
    Reduce data labeling costs
    with assistive labeling features
    Improve operational efficiency by
    reviewing project metrics
    Make data labeling accessible to data
    operations and program managers

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  41. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon SageMaker Canvas
    G E N E R A T E M L P R E D I C T I O N S – N O C O D E R E Q U I R E D
    Quickly access and prepare data sources for
    ML
    AutoML built in to generate accurate
    predictions
    Share ML models with data science teams
    Amazon SageMaker

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  42. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon SageMaker Studio Lab
    L E A R N A N D E X P E R I M E N T W I T H M A C H I N E L E A R N I N G
    Amazon SageMaker
    Studio Lab
    Free, no-configuration
    development environment
    All you need is an email address to get started
    As many CPU and GPU sessions as needed
    Automatically saves session data
    Models ready for production

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  43. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    The AWS ML Stack

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  44. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon Textract
    S P E C I A L I Z E D S U P P O R T F O R I D E N T I T Y D O C U M E N T S
    Amazon Textract
    OUTPUT
    First Name: JORGE
    Last Name: SOUZA
    Middle Name:
    Address Line1: 100 MAIN STREET
    Address Line 2:
    City: ANYTOWN
    State: MA
    Document Number: 820BAC729CBAC
    Expiration Date: 01/20/2020
    Date of Birth: 03/18/1978
    ID Type: Driver License
    Date of Issue: 03/18/1978
    Issued By: MASSACHUSETTS
    Class: D
    Restrictions: NONE
    Endorsements: NONE
    DOCUMENT

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  45. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon Personalize
    I N T E L L I G E N T U S E R S E G M E N T A T I O N
    Amazon Personalize
    • Identify users interested in a genre,
    category, or any other item attribute
    • Identify users interested in a given item
    such as a movie, product, and so on
    • More effective campaigns through
    marketing channels
    • Acquire users for new product categories,
    genres, channels, and more
    • Improve return on investment for your
    marketing spend
    Action movie
    fans

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  46. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    Amazon Personalize
    U S E - C A S E O P T I M I Z E D R E C O M M E N D E R S F O R R E T A I L , A N D M E D I A A N D E N T E R T A I N M E N T
    Retail
    • Recommended for you
    • Customers who viewed this
    also viewed
    • Frequently bought
    together
    • Most viewed
    • Best sellers
    Media and
    entertainment
    • Top picks for you
    • Because you watched X
    • More like Y
    • Most popular
    Amazon Personalize

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  47. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Amazon Lex
    A U T O M A T E D C H A T B O T D E S I G N E R
    Amazon Lex
    Analyze thousands
    of lines of transcripts
    in minutes
    Discover the most common
    intents and the information
    needed to fulfill them
    Accelerate chatbot
    deployment
    Allows you to design
    chatbots in hours rather
    than weeks
    Improve customer
    experience
    Helps ensure that intents
    are well defined and
    separated

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  48. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    AI & ML Scholarship Program
    Learn ML faster with AWS DeepRacer Student
    An all-new free service for students over the age of 16
    Fast-track your career with scholarships
    2,000 students per year to be awarded scholarships as
    part of the AWS AI & ML Scholarship program
    Receive mentorship from AWS and Intel ML experts
    Students in the AWS AI & ML Scholarship program
    receive mentoring and career guidance from industry
    experts

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  49. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    IoT

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  50. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    New services:
    • AWS IoT ExpressLink
    • AWS IoT TwinMaker
    • AWS IoT FleetWise
    • AWS IoT RoboRunner
    • FreeRTOS out-of-the-box
    AWS IoT Announcements
    Other:
    • AWS IoT Greengrass & Systems Manager
    • AWS IoT Greengrass Software Catalog
    • AWS IoT SiteWise Hot/Cold Storage Tiers
    • AWS IoT Fleet Indexing enhancements
    • FreeRTOS extended maintenance

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  51. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT ExpressLink
    AWS IoT ExpressLink packages all the
    complex and security-critical code into
    a single hardware component.
    A 3-wire serial interface is all you need
    to connect any embedded device to
    the cloud.
    TX
    RX
    GND WAKE
    INT
    RST

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  52. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT ExpressLink
    IoT
    library
    Hardware
    security
    Radio
    library
    Your application
    Host processor
    Hardware
    security
    Radio
    library
    Your
    application
    Wireless module
    IoT
    library
    AWS IoT ExpressLink
    Host processor
    Hardware
    security library
    Without AWS IoT ExpressLink With AWS IoT ExpressLink

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  53. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT ExpressLink
    int main()
    {
    print("AT+CONNECT\n");
    while(1){
    print("AT+SEND data {\"A\"=%d}", getSensorA());
    delays(1);
    }
    }
    In less than 10 lines of code

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  54. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT ExpressLink – Four evaluation kits
    Vendor Evaluation Kit Technology Buy
    Espressif ESP32-C3-DevKitM1 Wi-Fi
    Infineon CCM Eval Kit Wi-Fi
    u-blox Nora-W2 Mini Evaluation kit Wi-Fi
    u-blox Sara – R5 AWS Evaluation kit Cellular

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  55. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT TwinMaker
    E A S I L Y C R E A T E D I G I T A L T W I N S O F R E A L - W O R L D S Y S T E M S T O O P T I M I Z E O P E R A T I O N S
    Easily access data no matter where it lives
    Accurately model your built environment
    Create immersive 3D views

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  56. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT TwinMaker – How it works
    AWS IoT TwinMaker
    Digital twin
    Operations Planning
    Operational and
    maintenance history
    Real-time
    process data
    Real-time IoT
    sensor data
    CAD/BIM
    models
    Point cloud
    scans
    Video feeds Geo-spatial
    metadata
    Statistical and
    physics-based
    models
    Integrated asset model
    3D visualization
    Insights
    AWS Cloud
    End-user web application

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  57. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT TwinMaker – Features
    Data connectors
    Access data from diverse
    sources using built-in
    connectors, or easily
    create your own
    connectors to AWS and
    third-party data sources.
    Model builder
    Create entities to virtually
    represent physical systems,
    specify relationships
    between them, and connect
    them to different data
    sources to form a digital
    twin graph
    Scene composer
    Combine existing 3D
    visual models with real-
    world data from the
    digital twin graph to
    compose an interactive
    3D view of your physical
    environment
    App toolkit
    Integrate digital twins
    into 3D-enabled
    applications using
    Amazon Managed
    Grafana or AWS Partners
    for end users to monitor
    and improve operations

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  58. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview

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  59. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    Build virtual representations of
    vehicles and apply a common data
    format to structure and label vehicle
    attributes, sensors, and signals
    Easily access
    standardized, fleet-wide
    vehicle data
    AWS IoT FleetWise
    Easily collect, transform, and transfer vehicle data to the cloud at scale
    Reduce costs with
    intelligent data
    filtering
    Detect and mitigate problems
    more quickly by surfacing
    vehicle data in near real time
    Select which data to transfer, define
    rules and events for when to transfer it,
    and automatically reduce redundant
    data through dynamic data selection
    Take quick, corrective action by notifying
    operations or manufacturing groups in
    near real time when problems occur

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  60. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Preview
    AWS IoT RoboRunner
    B U I L D A P P L I C A T I O N S T H A T H E L P R O B O T S W O R K T O G E T H E R S E A M L E S S L Y
    Connect robots and
    work management
    systems to a common
    infrastructure
    Enable robots
    from different
    vendors to work
    together
    Simplify building
    applications for
    optimizing robot
    fleets

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  61. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    IoT devices Hub/gateway
    AWS IoT Greengrass
    AWS Systems Manager integrates AWS IoT Greengrass
    Systems Manager
    OS upgrades, schedule maintenance tasks, and remotely access their edge device fleet

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  62. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Greengrass Software Catalog
    A W S I O T G R E E N G R A S S S O F T W A R E C O M P O N E N T S D E V E L O P E D B Y T H E G R E E N G R A S S C O M M U N I T Y

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  63. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    AWS IoT SiteWise cold tier storage support
    1 0 1 0 1 1 0
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    0 1 0 1 0 1 0
    1 0 1 0 1 0 1
    101011010
    01010 10101
    0101001010
    01010 10101
    1010101010
    1010101010
    1010101010
    1 0 1 0 1 1 0
    0 1 0 1 0 1 0
    0 1 0 1 0 0 1
    0 1 0 1 0 1 0
    1 0 1 0 1 0 1
    1 0 1 0 1 0 1 0 1 0 1 0 1 0
    1 0 1 0 1 0 1 0 1 0 1 0 1 0
    1 0 1 0 1 0 1 0 1 0 1 0 1 0
    1 0 1 0 1 0 1 0 1 0 1 0 1 0
    1 0 1 0 1 0 1 0
    01010101
    ASSET MODEL
    Property: Attribute
    tool_id :
    Property: Time-series
    pressforce-ch1 :
    Property: Formula
    Avg Pressforce : f
    (pressforce-ch1)
    Ingest equipment data
    into AWS in minutes
    Structure data and specify
    performance metrics for your
    equipment and processes
    Store data in a time-series-
    optimized data store
    Create and share dashboards to
    visualize live and historical
    equipment data

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  64. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    FreeRTOS out-of-the-box connectivity

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  65. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    GA
    FreeRTOS Extended Maintenance Plan

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  66. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Agenda
    Analytics
    Databases
    AI/ML
    IoT

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  67. © 2022, Amazon Web Services, Inc. or its affiliates. All rights reserved.
    Thank you!
    Danilo Poccia
    AWS Chief Evangelist (EMEA)
    @danilop

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