Bluesoft @ AWS re:Invent 2017 + AWS 101

1. AWS re:INVENT 2017 @andrefaria

2. 6º Reinvent A Bluesoft esteve presente em todos eles!

3. 13.000 Sessions 43.000+ attendees

4. Expo

5. Recap

6. Amazon 101

7. Antes do Cloud

8. Cloud Computing is on-demand delivery of compute power, database storage, applications and other IT resources through a cloud services platform via the Internet with pay-as-you-go pricing.

9. no upfront investments no hardware management low cost scalable capex vs opex no capacity guessing increased speed and agility focus on core activities

10. IaaS - Infrastructure networking, computers, storage (EC2) PaaS - Platform management layer, patching (RDS) SaaS - Software end user apps (Amazon WorkDocs)

11. Global Infrastructure more than 1M customers in 190 countries low latency and higher throughput 42 AZs - 16 regions

12. AWS Management Console Simple and Intuitive User Interface

13. AWS Command Line Interface (CLI) AWS SDKs

14. EC2 - Amazon Elastic Compute Cloud On-Demand pay by the hour Reserved up to 75% for upfront payment Spot bid on spare capacity

15. ECS - Ec2 Container Service ECS Container Management Run Containers Clusters on EC2 instances ECR Container Registry Store, Manage, and Deploy Containers

16. Compute Services AWS Batch plan, schedule, and run batch computing jobs on AWS - it automatically provision resources (cpu, memory, spot, etc.) no need to manage servers clusters to run your jobs Amazon Lightsail laugh virtual private servers

17. Compute Services AWS Lambda run code without provisioning or maintaining servers, pay only for compute time you consume Elastic Beanstalk run Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Tomcat, Passenger, and Internet Information Services (IIS).

18. Compute and Storage Services Amazon S3 and Glacier S3 is an object storage designed to have 99.999999999% durability Glacier is a extremely low cost storage for archiving and long- term backup. AWS Autoscaling Ensure that your are running the desired number of EC2 Instances, and increases instances if demand increases

19. Storage Services Elastic File System Simple scalable ﬁle storage to use with EC2. Storage is elastic and can grow or shrink automatically as you add and remove ﬁles. AWS EBS Persistent block storage volumes to use with EC2, automatically replicated within the AZ. Best for low latency storage.

20. Storage and Database Services Aurora MySQL and Postgres compatible relational database that combines speed an availability of high-end comercial databases for 1/10 of the cost. AWS Storage Gateway Hybrid Storage between on premisses and cloud

21. Database Services Amazon Dynamo DB fast and ﬂexible NoSQL DB for consistent, single-digit millisecond latency at any scale, support both document and key- value storage. Amazon RDS Managed Aurora, PostgreSQL, MySQL, MariaDB, Oracle, Microsoft SQL Server.

22. Database and Networking Services Amazon VPC provision a logically isolated section for the cloud to launch resources (ip ranges, subnets, routes, route tables). Amazon ElastiCache Managed InMemory Database. Supports Redis and Memcached.

23. Networking Services Route 53 Highly available and scalable DNS Web Service - translates domains in IPS addresses AWS Cloud Front Global Content Delivery Network (CDN) that accelerates delivery for websites, APIs, video, or other assets, routing automatically to the nearest edge location.

24. Networking and Developer Services AWS Code Commit Fully Managed Source Control Service to host private Git Repos. Elastic Load Balancing ELB automatically distributes incoming application trafﬁc across multiple EC2 instances enabling fault-tolerance and scaling.

25. Developer Services AWS Code Deploy Automates code deployments to any instance AWS Code Build Fully Managed Build Services that compile source code, run tests and produces software packages that ready to deploy

26. Developer Services AWS X-Ray analyse and debug apps with end-to-end view of requests and a map of components. AWS Code Pipeline Continuous Integration and Continuous Delivery

27. Management Tools AWS Systems Manager collect inventory, apply patches, create images, conﬁgure and run commands. Amazon CloudWatch Monitoring Resources and Apps

28. Management Tools AWS Cloud Trail records API calls for your account and delivers log ﬁles AWS Cloud Formation Create and manage a collection of AWS resources, providing and updating

29. Management Tools AWS OpsWorks Configuration Management Service that uses Chef or Puppet to automate how servers are configured, deposed and manger across EC2 instances. AWS Config Full Managed service that provides an AWS resource inventory, config history, config change notifications and rules evaluations

30. Management Tools AWS Services Catalog Create and manage catalogs of IT services that are approved for use on AWS AWS Config Full Managed service that provides an AWS resource inventory, config history, config change notifications and rules evaluations

31. Management Tools Amazon Inspector Amazon Inspector automatically assesses applications for vulnerabilities or deviations from best practices. AWS IAM control access to AWS services and resources for your users

32. Management and Analytics Tools Amazon Athena is an serverless interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. 94 Athena is serverless. You pay only for the queries that you run. AWS IAM control access to AWS services and resources for your users

33. Analytics Tools Amazon CloudSearch managed search solution for websites and applications Amazon Elasticsearch managed Elasticsearch Amazon EMR managed service to run Hadoop, Spark, HBase, Presto, and Flink workloads that in a easy, fast, and cost-effective fashion to process vast amounts of data across dynamically scalable Amazon EC2 instances.

34. Kinesis Kinesis Firehose capture, transforms and load streaming data into s3, redshift, kinesis analytics for real time analytics Kinesis Analytics process streaming data in real time with standard SQL without having to learn new languages or processing frameworks - run queries continuously Kinesis platform for collecting, storing and analysing streaming data - you can load terrabytes of data per hour from IoT devices, mobile apps, etc. Kinesis offers 3 services. Kinesis Streams continuously capture and store treats of data per hour from thousands for sources

35. Analytics Amazon QuickSight cloud business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights. Amazon Redshift fast, fully managed, petabyte - scale data warehouse that makes it simple and cost - effective to analyze all your data using your existing business intelligence tools.

36. ETL AWS Glue fully managed ELT service that makes it easy to move data between data stores. Disponibiliza um serviço ETL gerenciado, executado em um ambiente Apache Spark sem servidor. Para não Spark, Hive, Pig, etc. usar Data Pipeline Amazon Data Pipeline Move data between different AWS compute and storage services. Access, Transform and Process at Scale and Store Results. Serviço de orquestração com ﬂexibilidade de ambiente de execução, do acesso e do controle sobre os recursos que executam código, bem como sobre o próprio código responsável pelo processamento dos dados.

37. IA Amazon Polly turns text into Speech Amazon Rekognition image analysis Amazon LEX building conversational interfaces into any application using voice and text

38. IA and Mobile AWS Mobile Hub quickly create and conﬁgure mobile app backends features and integrate them to the mobile app Amazon Cognito serverless identity service Amazon Pinpoint target campaigns to drive user engagement (e-mails, SMS, push notiﬁcations) Machine Learning makes it easy for developers of all skill levels to use machine learning technology. Provides visualisation tools and wizards that guide you through the process of creating machine learn ing models Amazon Device Farm test apps on many devices at once (Android, iOS and web)

39. IA and Mobile AWS Mobile Hub quickly create and conﬁgure mobile app backends features and integrate them to the mobile app Amazon Cognito serverless identity service Amazon Pinpoint target campaigns to drive user engagement (e-mails, SMS, push notiﬁcations) Machine Learning makes it easy for developers of all skill levels to use machine learning technology. Provides visualisation tools and wizards that guide you through the process of creating machine learn ing models Amazon Device Farm test apps on many devices at once (Android, iOS and web)

40. Mobile and Application Services Simple Workﬂow Service developers build, run, and scale background jobs that have parallel or sequential steps (like Step functions but no visual and more control of your logic) Amazon API Gateway create, publish, maintain and monitor secure APIs at scale Mobile Analytics measure app usage and revenue AWS Step Functions coordinate componentes of distributed applications and micro services using visual workﬂows

41. Messaging and App Streaming Amazon Workspaces fully managed desktop computing service Amazon AppStream 2.0 store your app from AWS to any device running in a web browser Amazon SQS managed queuing service Amazon SNS push notiﬁcation service Amazon SES send e-mails

42. IoT AWS IoT connect devices to AWS AWS Greengrass run local compute, lambda, messaging, caching, syncing for connected devices AWS ioT Button programable button (Dash alike)

43. back to re:INVENT

44. first keynote

45. $18B+ revenue run rate 42% growth rate AWS 44% of the public cloud marketshare (more than all other competitors combined) Millions of Active Customers airbnb, slack, intercom, pinterest, sony, go pro, johson, pﬁzer, GE, philps, siemens, netﬂix, disney, hbo, discovery, fox, kellogs, coca cola, samsung, LG 3000 government agencies 8000 academic institutions

46. Pace of Innovation 2016 1000+ Features 2017 1300+ Features

47. What builders really want? 6 songs

48. second keynote

49. Voice is next big disruption it’s a natural interface how you interact with people?

50. Security is everyone’s job Encryption is not only faster and more efﬁcient now. There’s really no excuse not to encrypt your data.

51. Dance like no one is watching Encrypt like everyone is

52. Trusted Advisor

53. Inspector (app level)

54. GuardDuty (network level plus IA)

55. Serverless

56. Product Launch Amazon Elastic Container Service for Kubernetes (EKS)

57. Go and .NET Support

58. Product Launch AWS Serverless Application Repository Publish and Find Lambdas to use

59. AI

60. AI © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Vision Speech LanguageServices Platforms Frameworks Infrastructure Amazon ML Spark & EMR Kinesis Mechanical Turk Amazon ECS Amazon Batch AWS Deep Learning AMI Apache MXNet TensorFlow Caffe2 & Caffe Theano Keras Cognitive Toolkit PyTorch GPU CPU IoT (Greengrass) Mobile Gluon

61. AWS DeepLens A camera fully loaded with onboard compute power optimized for deep learning

62. Amazon Sagemaker - prebuilt notebooks that solve common problems in machine learning - 10 algorithms to address problems - Import your own if you need a custom solution - “one-click training” specify the location of your dataset in S3, choose an instance type to run the computation, and Sagemakers does all the heavy lifting, setting up the algorithms to run your training. - “one-click-deploy“ set the instance type and minimum/maximum numbers for your cluster and Sagemaker then gives you secure endpoints to connect to your app.

63. Amazon Rekognition © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Rekognition Extract rich metadata from visual content Object and Scene Detection Facial Analysis Face Comparison Facial Recognition Celebrity recognition Image moderation Text in Image

64. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Maple Villa Bushes Grass Tree House Window Sky Mountain Range Forest Clouds Object and scene detection makes it easy for you to add features that search, filter, and curate large image libraries. Identify objects and scenes and provide confidence scores DetectLabelsObject & Scene Detection

65. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Demographic Data Facial Landmarks Sentiment Expressed Image Quality Brightness: 23.6 Sharpness: 99.9 General Attributes Facial Analysis DetectFaces Analyze facial characteristics in multiple dimensions Smiling 99.1% Female 100% Mouth Closed 99.5% Age Range 26 – 43 years old Crowd Mode

66. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Facial Analysis Image Quality Facial Landmarks Demographic Data Emotion Expressed General Attributes Facial Pose Brightness 23.6% Sharpness 99.9% EyeLeft,EyeRight,Nose RightPupil,LeftPupil MouthRight,LeftEyeBrowUp Bounding Box... Age Range 29-45 Gender:Male 96.5% Happy 83.8% Surprised 0.65% Smile:True 23.6% EyesOpen:True 99.8% Beard:True 99.5% Mustache:True 99.9%... Pitch 1.446 Roll 5.725 Yaw 4.383 DetectFaces

67. AWS Rekognition Video process real-time and batch video to detect objects, people, activities, and more - detect inappropriate content - check surveillance footage for missing people - continually trained, gets “smarter” as more people use it

68. Amazon Kinesis Video Streams its real time streaming capabilities for video - integrates with Rekognition video (as an input source) - SDK that manufacturers can use to integrate it directly into their devices

70. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. End-to-End Architecture SELECT STREAM COUNT(*) AS MUSTACH_COUNT, STEP(ROWTIME BY INTERVAL '1' SECOND) FROM SOURCE_STREAM WHERE HAS_MUSTACH = TRUE; Amazon Kinesis Stream Amazon Kinesis Analytics Amazon Cognito Amazon Kinesis Stream Amazon DynamoDB Amazon Lambda Amazon S3 JavaScript SDK Amazon Rekognition Amazon Kinesis Firehose Amazon S3

71. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Rekognition Case Study W a s h i n g t o n C o u n t y S h e r i f f ’ s O f f i c e Chris Adzima Washington County Sheriff’s Office Chris_adzima@co.washington.or.us

72. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Real-world example © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. The solution © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Real-world example

73. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Unlimited replays Returns an MP3 or audio stream Lightning-fast response Fully managed and low cost Amazon Polly Turn text into lifelike speech using deep learning technologies to synthesize speech that sounds like a human voice Potential use cases Content creation Education and E-learning Mobile and desktop applications Customer contact center Internet of Things (IoT) Accessibility

74. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Lex Conversational interfaces for your applications, powered by the same natural language understanding (NLU) and automatic speech recognition (ASR) models as Alexa Integrated development in AWS console Trigger AWS Lambda functions Multi-step conversations Continually improving ASR and NLU models Enterprise connectors Fully managed Potential use cases Appointment booking Customer support (Contact Center bots) Informational services Access enterprise data Internet of Things (IoT)

75. Amazon Transcribe converts speech to text

76. Amazon Translate it translates text from one language to another use batches of text from S3 it boasts real-time translation

77. Amazon Comprehend fully managed natural language processing service Provide data from your lake (S3) via an API then Comprehend will provide four elements for analysis: 1 Entities – Things like people, dates, and speciﬁc places 2 Key phrases – Comprehend picks out the “most important” sets of words 3 Language – Automatic detection of the language used 4 Sentiment – Is the text saying something positive or negative?

78. Amazon Comprehend

79. Customer Voice

80. Content Recommendation

82. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. “Book a hotel” Book hotel NYC “Book a hotel in NYC” Automatic speech recognition Hotel booking New York City Natural language understanding Intent/slot model UtterancesHotel booking City New York City Check In April 19 Check Out April 21 “Your hotel is booked for April 19” Amazon Polly Confirmation: “Your hotel is booked for April 19” “Can I go ahead with the booking?” a in

83. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Lex Utterances Spoken or typed phrases that invoke your intent BookHotel Intents An intent performs an action in response to natural language user input Slots Slots are input data required to fulfill the intent Fulfillment Fulfillment mechanism for your intent

86. Alexa for Business Alexa for Business is a fully managed service for Alexa voice-controlled devices at work. just say, “Alexa, start the meeting.”

87. Tools

88. Mobile

89. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. MOBILE INDUSTRY TRENDS Time spent in apps and growing 1.6T hours Source: AppAnnie New enterprise apps built with web technologies 50%+ Source: AWS JavaScript – most commonly used programming language 66.7%▲ Source: Stack Overflow

90. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. THREE SIMPLE STEPS 1. Pick a Platform Mobile Hub 2. Set Up Cloud Services Native SDKs 3. Connect Your App Mobile CLI AWS Amplify

91. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. MOBILE CLI: SETTING UP CLOUD SERVICES > awsmobile init > awsmobile user-signin enable Initialize your app Enable User Sign-in Supported services: • user-signin (Amazon Cognito) • analytics (Amazon Pinpoint) • database (Amazon DynamoDB) • user-files (Amazon S3) • cloud-api (API GW & AWS Lambda) Web app deployment support: • hosting (Amazon S3 and Amazon CloudFront)

92. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. APP DATA: HARD PROBLEMS REMAIN Data requirements vary across devices and become harder when multiple users share data Users want instant access to data Building scalable data-driven apps without learning distributed systems concepts is hard Users want to continue using their apps even with low or no connectivity

95. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. EASY ACCESS TO RICH DATA { "id": "1", "name": "Get Milk", "priority": "1" }, "id": "2", "name": "Go to gym", "priority": "5" },… type Query { getTodos: [Todo] } type Todo { id: ID! name: String description: String priority: Int duedate: String } query { getTodos { id name priority } } Model data with application schema Client requests what it needs Only that data is returned

97. AWS Amplify AWS Amplify is a JavaScript library for frontend and mobile developers building cloud-enabled applications. The library is a declarative interface across different categories of operations in order to make common tasks easier to add into your application. "I was able to use AWS Cognito to integrate a full-featured authentication system, including email signup veriﬁcation and MFA, into a React application with less than 10 lines of code, in about 20 minutes. That time would have been drastically less if I had already created a user pool beforehand."

98. Networking

99. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Load balancer used to route incoming requests to multiple Amazon EC2 instances, containers, or IP addresses in your VPC. ELB EC2 Instance EC2 Instance EC2 Instance

100. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Application Load Balancer Network Load Balancer Classic Load Balancer Protocol HTTP, HTTPS, HTTP/2 TCP TCP, SSL, HTTP, HTTPS SSL offloading ✔ ✔ IP as Target ✔ ✔ Path-based routing, Host-based routing ✔ Static IP ✔ WebSockets ✔ ✔ Container Support ✔ ✔

101. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. For TCP in VPC, use Network Load Balancer. For all other use cases in VPC , use Application Load Balancer For Classic networking, use Classic Load Balancer

102. Data

103. Aurora Multi-Master

104. Aurora Serverless Database starts up on demand, shuts down when it’s not in use… when it is in use, you’re billed by the second.

105. DynamoDB Global Tables The ﬁrst fully managed, multi-master, multi-region database system in the world

106. DynamoDB On-Demand Backup create backups (and restore them) with one click or API call

107. Amazon Neptune Neptune is a fully managed graph database service store billions of records will millisecond latency

108. S3 Select and Glacier Select Good for Data Lakes pull out only the data you need using an API to pull only speciﬁc parts of an object

109. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon S3 By The Numbers 44 Availability Zones (16 more coming in 2018) 16 Regions (5 more coming in 2018) Trillions of objects Millions of requests per second One of first three AWS Services (2006) 99.999999999% Durability

110. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon S3 Availability Zones S3 stores data in at least 3 Availability Zones (AZ’s) Each AZ can be up to 8 physical data centers Unavailability of a data center or an AZ does not impact overall S3 availability Low latency private network connect data centers and AZ’s Physically separate – even extremely uncommon disasters would only affect a single AZ Data is automatically distributed across a minimum of 3 AZ’s GEO separated within an AWS Region

111. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon S3 Storage Classes & T ra n sitio n s S3 Standard S3 Standard – Infrequent Access Amazon Glacier Active data Synchronous access Milliseconds retrieval 2.1¢-GB/mo Archive data Asynchronous access Minutes-to-hours retrieval 0.4¢-GB/mo Infrequently accessed data Synchronous access Milliseconds retrieval 1.25¢-GB/mo

112. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon S3 Security, Encryption & Compliance T he b roade st se t of tools in the indu stry Security • IAM and Bucket Policies • Access Control Lists • Audit logging with CloudTrail & Alerts with CloudWatch • Secure CloudFormation templates • Amazon Macie • S3 Console Permission Checks Encryption • Encryption in transit with TLS • SSE-S3 – Amazon S3 manages data & keys • SSE-C – Customer managed keys • SSE-KMS – Master keys in KMS • CSE – 100% Customer managed • Default Bucket Encryption • Encryption Status in Inventory Compliance • PCI-DSS • HIPAA/HITECH • FedRAMP • FISMA • EU Data Protection Directive

113. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Do More With Your In-place Data • Athena • Redshift Spectrum • QuickSight • EMR Data Lake Storage IoT Storage Machine Learning & AI Storage • AWS IoT • Greengrass • Other IoT sensors • Rekognition • LEX • Polly • MXNet & TensorFlow

114. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Enter Data Lake Architectures Data lake is a new and increasingly popular architecture to store and analyze massive volumes and heterogeneous types of data

115. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Benefits of a Data Lake—All Data is in One Place Analyze all of your data, from all of your sources, in one stored location “Why is the data distributed in many locations? Where is the single source of truth?”

116. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Designed for 11 9s of durability Designed for 99.99% availability Durable Available High performance Multiple upload Range GET Scalable throughput Store as much as you need Scale storage and compute independently No minimum usage commitments Scalable Amazon EMR Amazon Redshift Spectrum Amazon DynamoDB Amazon Athena AWS Glue Amazon Rekognition Amazon Macie Integrated Simple REST API AWS SDKs Simple management tools Event notification Lifecycle policies Easy to use Why Amazon S3 for a Data Lake?

117. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AWS Direct Connect AWS Snowball ISV Connectors Amazon Kinesis Firehose Amazon S3 Transfer Acceleration AWS Storage Gateway Data Ingestion into Amazon S3

119. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Processing and Analytics Real-time Batch AI and Predictive BI and Data Visualization Transactional and RDBMS AWS Lambda Apache Storm on EMR Apache Flink on EMR Spark Streaming on EMR Elasticsearch Service Kinesis Analytics, Kinesis Streams DynamoDB NoSQL DB Relational Database Aurora EMR Hadoop, Spark, Presto Amazon Redshift Data Warehouse Amazon Athena Query Service Amazon Lex Speech recognition Amazon Rekognition Amazon Polly Text to speech Machine Learning Predictive analytics Kinesis Streams and Firehose

120. IoT

121. IoT is about… “closing the gap between the physical and digital world in self-reinforcing and self-improving systems.”

122. AWS IoT 1-Click

123. AWS IoT Device Management IoT Device Management is similar to 1-Click, but at a larger scale. Onboard, deploy, and manage your ﬂeet of devices all from a single location. Organize inventory, query the ﬂeet for troubleshooting, and remotely deploy updates take action on subsets of your devices, not just all of them at once

124. AWS IoT Device Defender Many of the attacks we’ve seen in recent years have utilized unsecured IoT devices. Device Defender allows you to set device policies, audit them, and monitor behaviours on an individual level to identify anomalies and out-of-compliance behaviours Send you automatic alerts when it detects a problem

125. AWS IoT Analytics Traditionally, IoT devices pick up a lot of “noisy” data, like temperature and humidity, resulting in raw, unstructured information that’s very difﬁcult to process.

126. AWS FreeRTOS While larger devices often come with a full onboard CPU, smaller ones tend to use an MCU (micro controller unit) and they do still need an operating system. Amazon has created their own version of FreeRTOS (a commonly used OS in these devices), and it’s got some awesome features. Amazon FreeRTOS comes with prepackaged libraries to connect to AWS services, update, and secure the device. It also allows you to easily send data to the cloud for further analysis.

127. AWS GreenGrass Execute funções lambda nos dispositivos com segurança usando recursos locais de computação, sistema de mensagens, armazenamento de dados em cache e sincronização para dispositivos conectados.

128. AWS GreenGrass Exemplo You have a collection of IoT sensors deployed in the ﬁeld, along with a GreenGrass device. Rather than sending data straight to the cloud, the sensors can connect to the GreenGrass device directly and have it perform some operation for them. This is done locally – the sensors don’t need to be connected to the public internet to communicate with GreenGrass. This saves time by lowering the latency of connections, and money by ﬁltering data from the sensors before sending it all to the cloud for processing.

129. AWS GreenGrass Machine Learning Inference GreenGrass device still operates the same way – at the edge of your network. But it can now apply machine learning models in the ﬁeld. ex: an IoT sensor that takes an action in response to a voice command. Before, you’d have to send that data to the cloud for processing, then back to the sensor, which would then trigger the action (back to the cloud again, most likely). With Machine Learning Inference on a GreenGrass device, you can do all of that locally, resulting in much faster response times.

130. Obrigado!@andrefaria - andrefaria.com

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