capacity between all Regions except China Over 150 Global CloudFront PoPs 89 Direct Connect Locations a e o q i h Paris Sweden AWS GovCloud East First 5 years: 4 regions 2016–2020: 13 regions Next 5 years: 7 regions A W S REGIONAL EXPANSION 1 9 R e g i o n s 5 7 A Z s d m c g b n s k v i i i i i i i i Milan i Cape Town
rights reserved. EC2 Instance Types Burstable T 3 Big Data Optimized H 1 Memory Optimized R 5 High I/O I 3 Compute Intensive C 5 Graphics Intensive G 3 General Purpose GPU P 3 Memory Intensive X 1 X 1 e General Purpose M 5 V i r t u a l P r i v a t e S e r v e r s Bare Metal High I/O I 3 m Dense Storage D 2 F 1 FPGA A m a z o n L i g h t s a i l High-Memory Intensive Z 1 Powered by M 5 a R 5 a • Choose between processors on AWS general purpose and memory optimized instances • 10% lower prices on AMD-based instances • Most applications can run on AMD-based variants with little to no modification M 5 d R 5 d C 5 d Z 1 d • NVMe-based SSD block level instance storage physically connected to the host server • High-speed, low latency local block storage • EBS PIOPS to 1GB/s (64,000)
rights reserved. Hibernate EC2 Instances • Signals OS to hibernate (suspend to disk) • RAM is saved to root FS, EBS remains attached • EBS root volume must be encrypted and large enough • Can be used to prewarm instance that take long to boot • Hibernated instances can be stopped https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-instance-lifecycle.html
Amazon EKS to better run containerized microservices at scale Microservice A Microservice B Microservice C Microservice A Microservice B Microservice C Microservice C Microservice C Before After
available in AWSMarketplace Choose from more than 160 curated and trusted container products in AWS Marketplace and run them on AWS Container product images are verified and scanned Deploy container products on Amazon ECS, AWS Fargate, or EKS Products are available with free, bring your own license, and usage-based pricing models AWS Marketplace for Containers
Y AVAI L AB L E A W S C l o u d 9 AWS Toolkit for PyCharm AWS Toolkit for IntelliJ AWS Toolkit for VS Code GENERALLY AVAILABLE IN DEVELOPER PREVIEW IN DEVELOPER PREVIEW Open source toolkits meeting you where and how you like to work AWS Toolkits for popular IDEs + IDEs
Bring any Linux compatible language runtime; Powered by new Runtime API - Codifies the runtime calling conventions and integration points Same technology powering Ruby support in AWS Lambda Bring any Linux compatible language runtime Custom Runtimes + AWS OPEN SOURCE o f f e r e d b y o f f e r e d b y o f f e r e d b y o f f e r e d b y PARTNER SUPPORTED https://aws.amazon.com/about-aws/whats-new/2018/11/aws-lambda-now-supports-custom-runtimes-and-layers/
any binaries, dependencies, or runtimes Lambda Layers BUSINESS LOGIC LIB A LIB B BUSINESS LOGIC LIB A LIB B BUSINESS LOGIC LIB A LIB B BUSINESS LOGIC LIB A LIB B Programming Model Before BUSINESS LOGIC BUSINESS LOGIC BUSINESS LOGIC BUSINESS LOGIC LIB A LIB B After
serverless applications Serverless Application Repository Compose application architectures from reusable building blocks Nested Applications using Serverless Application Repository Deploy new architectures as a set of serverless apps (nesting) Foster best organizational practices and reduce duplication of effort Share components, modules and full applications privately with teams or publicly with others to improve agility + + Integrate Lambda functions into existing web architectures ALB Support for Lambda AWS Lambda Applicatio n Load Balancer AWS Fargate Amazon EC2
Amazon API Gateway WebSockets API LAMBDA FUNCTIONS PUBLIC ENDPOINTS ON AMAZON EC2 AMAZON KINESIS ANY OTHER AWS SERVICE Stateful connection A L L P U B L I C L Y A C C E S S I B L E E N D P O I N T S Stateful connection Programming Model This new type of API will enable customers to build real-time two way communication applications backed by Lambda functions or other API Gateway integrations. Web Socket support for API Gateway
rights reserved. Firecracker Architecture and Benefits • Firecracker microVMs have the same security as KVM VMs • Designed for low overhead, high density, and fast start times • Built-in fair sharing
and 256 MB/s of throughput per gp2 volume genaral purpose SSD 2x performance increase for io1 and 60% performance increase for gp2volumes Use fewer volumes and operational staff to achieve maximum performance for your applications Achieve up to 64,000 IOPS and 1,000 MB/s of throughput per io1 volume provisioned IOPS
accesseddata Cost Optimized for Infrequent Access Lower price than standard tier Easy to Manage Users configure lifecycle policies between classes Single File System Store infrequently and frequently accessed files in the same data set
and accelerates movingdata Transfers up to 10 Gbps per agent Pay as you go Simple data movement to S3 or EFS Secure and reliable transfers Replicate data to AWSfor business continuity Transfer data for timely in-cloud analysis Migrate active application data toAWS Combines the speed and reliability of network acceleration software with the cost-effectiveness of open source tools AWS integrated AWS
it easy to integrate SFTP-based file transfers into AWS Move your existing SFTP workflows to AWS in 3steps Seamless migration of existing workflows Data available for archiving and processing in S3 Simple to use Cost effective Fully managed, highly available, and elastically scalable 1 2 3
rights reserved. Set up Storage 1 Move data 2 Cleanse and prep data 3 Configure and enforce security and compliance policies 4 Make data accessible for analytics 5 Steps for building and managing a data lake
Gain and manage new insights Move, store, catalog, and clean your data faster with machine learning A service that allows you to build a secure data lake in days Amazon Lake Formation
Windows native for fully compatible Windows File System experience No hardware or software to manage Secure and compliant including PCI-DSS, ISO, and HIPAA Up to 10s of GB/s throughput with sub- millisecond latencies (Compatibility with AD, Windows access control, and native Windows Explorer experience) Fully managed Windows file system built on native Windows file servers
of GBs/s and millions of IOPS Seamless integration with Amazon S3 Secure and compliant including PCI-DSS, ISO and HIPAA Fully managed file system for high compute intensive workloads Amazon FSx for Lustre
Highly available with rolling upgrades Fully compatible – Run your Kafka applications with zero code changes Fully managed and highly available Apache Kafka service Amazon Managed Streaming for Kafka
rights reserved. Provisioning capacity for DynamoDB ( S o m e t i m e s i t ’ s h a r d t o k n o w w h a t ’ s b e s t ) HIGH-SCALE APPLICATIONS Estimating how much throughput capacity to provision can be guesswork Not enough experience with app can cause unexpected extreme app usage Spikey traffic can be costly to maintain availability and performance Auto-scaling can cause lag time apps can’t afford
N o m o r e c a p a c i t y p l a n n i n g – p a y o n l y f o r w h a t y o u u s e No capacity planning No need to specify how much read/write throughput you expect to use Pay only for what you use Pay-per-request pricing Ideal for unpredictable workloads Ramp from zero to tens of thousands of requests per second on demand
needed for enterprise-grade availability and reliability Limited data lifecycle management capabilities Unnatural for time-series data Rigid schema inflexible for fast-moving time- series data Building with time-series data is challenging Lack time-series analytic functions like smoothing, approximation, and interpolation 1 2 3 Clickstream data IoT Sensor Readings DevOps data
the cost of relational databases Trillions of daily events Serverless Time-series analytics (interpolation, smoothing, approximation) built in Multiple orders of magnitude improvement in query performance Fast, scalable, fully managed time series database Amazon Timestream
history Manufacturers Track distribution of a recalled product HR & Payroll Track changes to an individual’s profile Healthcare Verify and track hospital equipment inventory Common customer use cases on Blockchain Relational databases Blockchain frameworks Using sub-optimal ways to solve the problem LEDGERS WITH CENTRALIZED TRUST 1
and distributers Retail Streamline customer rewards Financial Institutions Peer-to-peer payments Blockchain Frameworks Hard to scale Set up is hard Complicated to manage Expensive TRANSACTIONS WITH DECENTRALIZED TRUST 2 LEDGERS WITH CENTRALIZED TRUST 1 Common customer use cases on Blockchain
chained and verifiable Transparent Full visibility into entire data lineage Immutable Append-only, immutable journal tracks history of all changes Highly scalable Automatically scale up or down Easy to use Query with familiar SQL operators Fast Execute 2-3X more transactions Fully managed ledger database that provides a transparent, immutable, cryptographically verifiable transaction log owned by a central trusted authority Amazon Quantum Ledger Database
Amazon Managed Blockchain Choose Hyperledger Fabric or Ethereum Create blockchain networks with a few clicks; manage them with simple API calls Scales to support thousands of applications running millions of transactions Easy to move data into QLDB for further analysis
rights reserved. FRAMEWORKS INFRASTRUCTURE P3 P3dn INTERFACES Infrastructure and frameworks for Machine Learning C O M I N G S O O N Scale model training performance across multiple instances 100 Gbps networking 64 GB GPU memory 768 RAM (System Memory) P3dn.24xl 3X faster network throughput than any other provider 2X as much GPU memory than any other GPU instance from other major providers 100+ GB more system memory than the next largest instance available from other providers “In the cloud, 85% of TensorFlow workloads run on AWS" Nucleus Research, TensorFlow on AWS, 28 November 2018, Analyst: Rebecca Wettemann
rights reserved. Running inference in production drives the majority of cost for Machine Learning Inference Training Infrastructure costs But what about inference? It’s never been easier, faster, or more cost- effective to train Machine Learning models
rights reserved. Two main drivers of inference inefficiency: complexity and cost of Machine Learning inference today Elasticity is important One size does not fit all
GPU Add GPU acceleration to any Amazon EC2 instance for faster inference at much lower cost (up to 75% savings) Amazon Elastic Inference P 3 . 8 X L P 3 P 3 P 3 P 3 Amazon Elastic Inference 36 TOPS GPU M5.large Amazon Elastic Inference
rights reserved. Starting at 1 TFLOPS Any instance family Simple speech and language models Up to 32 TFLOPS Recommendation engines or fraud detection models Provision Elastic Inference capacity inside VPC 360,000 ResNet-50 Computer vision deep learning model images per hour, inference $0.22 per hour on medium EI accelerator 75% lower cost L O W E S T C O S T A V A I L A B L E Elastic Inference - Scale & Cost
annotations Training data Simple, pre-built workflows Mechanical Turk Your own employees Third party vendors Active Learning model >80% confidence <80% confidence Build highly accurate training datasets and reduce data labeling costs by up to 70% using Machine Learning Amazon SageMaker - Ground Truth
rights reserved. Amazon SageMaker: broad set of built-in algorithms Designed to be 10x faster K-Means Clustering Principal Component Analysis Neural Topic Modelling Factorization Machines Linear Learner (Regression) BlazingText Reinforcement Learning XGBoost Topic Modeling (LDA) Image Classification Seq2Seq Linear Learner (Classification) DeepAR Forecasting A L G O R I T H M S Built into Amazon SageMaker Improving and expanding continually 40% more algorithms added since SageMaker launch
Recognition Text Clustering Text Generation Text Classification Grammar and Parsing Named Entity Recognition Text to Speech Handwriting Recognition Object Detection in Images 3D Images Text OCR Video Classification Speaker Identification Ranking Regression Anomaly Detection Register with AWS Marketplace Automatic validation on SageMaker Package algorithm, models and configuration Self-service listing on AWS Marketplace Browse or search AWS Marketplace Subscribe in a single click Available through Amazon SageMaker Over a hundred algorithms and models that can be deployed directly to Amazon SageMaker AWS Marketplace for Machine Learning S e l l i n g a l g o r i t h m s & m o d e l s o n A W S M a r k e t p l a c e
MXNet, Intel Coach, and Ray RL 2D and 3D simulation environments via OpenGym Simulate environments with Amazon Sumerian and AWS RoboMaker Example notebooks and tutorials New machine learning capabilities in Amazon SageMaker to build, train, and deploy with Reinforcement Learning Amazon SageMaker RL
rights reserved. HD Video Camera Gyroscope for direction and orientation Accelerometer for measuring change in speed Two batteries: one to power on-board compute, one to drive motors Dual-core Intel Atom® Processor Introducing AWS DeepRacer All wheel drive, monster truck chassis Suspension mounted high for a view of the road Both accelerometer and gyroscope useful in the future for building more sophisticated models such as finding the perfect racing line or path finding
rights reserved. Build reinforcement learning model DeepRacer League Races at AWS Summits Winners of each DRL Race and top points getters compete in Championship Cup at re:Invent 2019 Virtual tournaments through the year AWS DeepRacer League World’s first global autonomous racing league, open to anyone
conversion, etc. Inventory Articles, products, videos, etc. Demographics (optional) LOAD DATA (EMR Cluster) INSPECT DATA IDENTIFY FEATURES SELECT ALGORITHMS SELECT HYPERPARAMETERS TRAIN MODELS OPTIMIZE MODELS HOST MODELS BUILD FEATURE STORE CREATE REAL-TIME CACHES Customized personalization & recommendation API F u l l y m a n a g e d b y A m a z o n P e r s o n a l i z e Amazon Personalize Age, location, etc. Real-time personalization and recommendation service, based on the same technology used at Amazon.com Amazon Personalize
with SAP and Oracle Supply Chain Custom forecasts with 3 clicks 50% more accurate 1/10th the cost Integrates with Amazon Timestream Retail demand Travel demand AWS usage Revenue forecasts Web traffic Advertising demand Generate forecasts for: Accurate time-series forecasting service, based on the same technology used at Amazon.com
security alerts & automate compliance checks • Enabled in minutes to aggregate security findings from AWS and Partner services across your accounts • Quickly assess security and compliance in one location and take action on findings • Built-in and customizable insights help you track security issues that are unique to your environment • Improve compliance with automated, continuous account-level configuration and compliance checks
multi-account environment in a single location to govern AWS workloads Automate the creation of a landing zone with best practice blueprints AWS Control Tower automates the set-up of a well-architected multi-account environment with best practices, and guides you through a step-by-step process to customize it to your organization Guardrails for policy enforcement Control Tower offers curated guardrails. Guardrails are high-level rules that provide on-going governance for your overall AWS environment Dashboard for continuous visibility The Control Tower dashboard gives you continuous visibility into your AWS environment. You can view the number of organizational units and accounts provisioned, guardrails enabled, and the compliance status of your enabled guardrails
improve your architecture using AWS Well-Architected best practices Implement workplans to improve your architecture Stay up to date as your architecture evolves Review workloads against best practices
rights reserved. Space Business? • Build ground stations, sign long-term leases, and purchase excess bandwidth • Expensive to build and difficult to maintain and require high CAPEX investment to scale, and experience network latency and scheduling conflicts • Have opaque investing and pricing for startups
with fully managed Ground Station as a Service AWS Ground Station Low Earth Orbit (LEO) Medium Earth Orbit (MEO) Simultaneous narrowband S-band, X-band and UHF downlink Receive satellite data into Amazon VPC and Process data in AWS Cloud
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