This document discusses serverless architectures and provides examples of building serverless applications. It introduces serverless computing and explains why developers want to adopt serverless and DevOps approaches. Examples are given for static and dynamic websites built with serverless technologies like AWS Lambda, API Gateway, and S3 storage. The document also provides a case study of building a serverless application with services like Cognito, DynamoDB, and Lambda. Alternatives to AWS serverless options are mentioned along with takeaways about paying only for resources used.
10 Tips For Serverless Backends With NodeJS and AWS LambdaJim Lynch
The document provides 10 tips for building serverless backends with Node.js and AWS Lambda. It discusses how serverless architectures are cheaper and easier to manage than traditional servers. It then outlines each tip which includes how to create "Hello World" functions, pass data to Lambda functions, set up REST APIs, secure functions, send emails/texts, schedule functions, view logs, add additional Node.js libraries, and use Lambda with IoT devices.
AWS Summit Auckland - Getting Started with AWS Lambda and the Serverless CloudAmazon Web Services
This document provides an overview of AWS Lambda and serverless computing. It discusses five sample use cases for AWS Lambda including adding features to Amazon S3, extending platforms, building scalable mobile backends, real-time streaming analysis, and serverless microservices. The document then covers requirements, building a mobile backend without coding it, and additional capabilities. It dives deeper into programming models and resource sizing and provides examples of extending other AWS services like Amazon S3.
This document summarizes a presentation given by Dr. Tim Wagner, General Manager of AWS Lambda and Amazon API Gateway, at the AWS New York Summit on August 11, 2016 about getting started with serverless computing using AWS Lambda and Amazon API Gateway. The presentation introduced serverless computing and how it abstracts infrastructure management, discussed AWS Lambda and Amazon API Gateway services and how to choose between them. It also provided examples of serverless use cases including data processing, backend services, and app ecosystems. Tips for VPC configuration, function scheduling, and stage variables in API Gateway were also shared.
Do you want to run your code without the cost and effort of provisioning and managing servers? Find out how in this deep dive session on AWS Lambda, which allows you to run code for virtually any type of application or back end service – all with zero administration. During the session, we’ll look at a number of key AWS Lambda features and benefits, including automated application scaling with high availability; pay-as-you-consume billing; and the ability to automatically trigger your code from other AWS services or from any web or mobile app.
AWS October Webinar Series - AWS Lambda Best Practices: Python, Scheduled Job...Amazon Web Services
AWS Lambda lets you run code without provisioning or managing servers. We have introduced a few new features this year at re:Invent and would like to share with you some of the best practices.
This webinar will introduce you to scheduled AWS Lambda functions and how to use long running functions to handle large volume data ingestion and processing jobs. We will demonstrate how to use versioning to control which Lambda function version is being executed in your development, testing, and production environments. We will also show you how to run your Python code in AWS Lambda.
The document discusses serverless architectures using AWS Lambda and Amazon API Gateway. It provides background on moving from monolithic to microservices architectures. It then covers AWS Lambda functions, event sources, and networking environments. Amazon API Gateway is presented as a way to build multi-tier serverless applications. Common serverless architecture patterns and best practices for AWS Lambda, API Gateway, and general serverless development are outlined. The document concludes with a demonstration of a simple CRUD backend using Lambda and DynamoDB with API Gateway.
AWS Lambda allows any Node.js app to be run at scale in a massively parallel environment with no up-front costs or planning. This session shows how to use Lambda to build dynamic analytic data flows that can be tuned as they execute, based on initial results, to provide real-time output streamed to web clients. This process enables a cost-effective and responsive user experience for ad hoc big data jobs and lets developers focus on how data is consumed and presented, instead of how it is obtained.
This document provides an overview of AWS Lambda and how it enables serverless application development. It discusses how AWS Lambda allows developers to run code without provisioning or managing servers, and how it can automatically scale in response to triggers from various AWS services. It also summarizes some key capabilities like bringing custom code, parallel execution, integration with other AWS services, and event-driven or pull-based invocation models.
10 Tips For Serverless Backends With NodeJS and AWS LambdaJim Lynch
The document provides 10 tips for building serverless backends with Node.js and AWS Lambda. It discusses how serverless architectures are cheaper and easier to manage than traditional servers. It then outlines each tip which includes how to create "Hello World" functions, pass data to Lambda functions, set up REST APIs, secure functions, send emails/texts, schedule functions, view logs, add additional Node.js libraries, and use Lambda with IoT devices.
AWS Summit Auckland - Getting Started with AWS Lambda and the Serverless CloudAmazon Web Services
This document provides an overview of AWS Lambda and serverless computing. It discusses five sample use cases for AWS Lambda including adding features to Amazon S3, extending platforms, building scalable mobile backends, real-time streaming analysis, and serverless microservices. The document then covers requirements, building a mobile backend without coding it, and additional capabilities. It dives deeper into programming models and resource sizing and provides examples of extending other AWS services like Amazon S3.
This document summarizes a presentation given by Dr. Tim Wagner, General Manager of AWS Lambda and Amazon API Gateway, at the AWS New York Summit on August 11, 2016 about getting started with serverless computing using AWS Lambda and Amazon API Gateway. The presentation introduced serverless computing and how it abstracts infrastructure management, discussed AWS Lambda and Amazon API Gateway services and how to choose between them. It also provided examples of serverless use cases including data processing, backend services, and app ecosystems. Tips for VPC configuration, function scheduling, and stage variables in API Gateway were also shared.
Do you want to run your code without the cost and effort of provisioning and managing servers? Find out how in this deep dive session on AWS Lambda, which allows you to run code for virtually any type of application or back end service – all with zero administration. During the session, we’ll look at a number of key AWS Lambda features and benefits, including automated application scaling with high availability; pay-as-you-consume billing; and the ability to automatically trigger your code from other AWS services or from any web or mobile app.
AWS October Webinar Series - AWS Lambda Best Practices: Python, Scheduled Job...Amazon Web Services
AWS Lambda lets you run code without provisioning or managing servers. We have introduced a few new features this year at re:Invent and would like to share with you some of the best practices.
This webinar will introduce you to scheduled AWS Lambda functions and how to use long running functions to handle large volume data ingestion and processing jobs. We will demonstrate how to use versioning to control which Lambda function version is being executed in your development, testing, and production environments. We will also show you how to run your Python code in AWS Lambda.
The document discusses serverless architectures using AWS Lambda and Amazon API Gateway. It provides background on moving from monolithic to microservices architectures. It then covers AWS Lambda functions, event sources, and networking environments. Amazon API Gateway is presented as a way to build multi-tier serverless applications. Common serverless architecture patterns and best practices for AWS Lambda, API Gateway, and general serverless development are outlined. The document concludes with a demonstration of a simple CRUD backend using Lambda and DynamoDB with API Gateway.
AWS Lambda allows any Node.js app to be run at scale in a massively parallel environment with no up-front costs or planning. This session shows how to use Lambda to build dynamic analytic data flows that can be tuned as they execute, based on initial results, to provide real-time output streamed to web clients. This process enables a cost-effective and responsive user experience for ad hoc big data jobs and lets developers focus on how data is consumed and presented, instead of how it is obtained.
This document provides an overview of AWS Lambda and how it enables serverless application development. It discusses how AWS Lambda allows developers to run code without provisioning or managing servers, and how it can automatically scale in response to triggers from various AWS services. It also summarizes some key capabilities like bringing custom code, parallel execution, integration with other AWS services, and event-driven or pull-based invocation models.
As serverless architectures become more popular, AWS customers need a framework of patterns to help them deploy their workloads without managing servers or operating systems.
This document discusses new features and capabilities for serverless applications on AWS Lambda. Key points include:
- AWS Serverless Application Model (SAM) allows defining serverless apps in a common language and integrates with CloudFormation.
- New features for serverless CI/CD pipelines include pulling source from GitHub/CodeCommit with CodePipeline and building with CodeBuild.
- Environment variables are now supported for Lambda functions.
- X-Ray provides visibility for tracing calls between Lambda and other AWS services.
- Other updates include Kinesis iterator, C# runtime, dead letter queues, and integrations with services like API Gateway, DynamoDB, and Step Functions for orchestrating functions.
This talk will be a 2-300 level discussion on Serverless Architectures on AWS. We’ll first explore the Serverless ecosystem on AWS, looking at some particular use cases for Serverless. Looking through the lens of AWS customers, we’ll look at the typical Serverless journey, as well some of the key emerging patterns and benefits of Serverless Architectures. We’ll also touch some of the key challenges in a distributed environment and some potential solutions and tools that customers might want to consider.
The document describes building a real-time chat system using serverless architecture on AWS. It shows how to use AWS Lambda functions, API Gateway, DynamoDB, Cognito, IoT, S3 and CloudFront to create an interactive chat application without having to manage servers. The chat system allows users to publish and subscribe to messages in real-time using IoT topics and rules to route messages. Screenshots demonstrate the flow of data and functions within the serverless application.
AWS re:Invent 2016: Building Complex Serverless Applications (GPST404)Amazon Web Services
Provisioning, scaling, and managing physical or virtual servers—and the applications that run on them—has long been a core activity for developers and system administrators. The expanding array of managed AWS cloud services, including AWS Lambda, Amazon DynamoDB, Amazon API Gateway and more, increasingly allows organizations to focus on delivering business value without worrying about managing the underlying infrastructure or paying for idle servers and other fixed costs of cloud services. In this session, we discuss the design, development, and operation of these next-generation solutions on AWS. Whether you're developing end-user web applications or back-end data processing systems, join us in this session to learn more about building your applications without servers.
Building Serverless Backends with AWS Lambda and Amazon API GatewayAmazon Web Services
AWS Lambda is a compute service that runs your code without provisioning or managing servers. Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale.
This session will familiarize you with the basics of AWS Lambda and Amazon API Gateway and demonstrate how to build web, mobile, and IoT backends using these services. You will learn how to setup API endpoints that trigger AWS Lambda functions to handle mobile, web, IoT, and 3rd party API requests. You will also learn how to use Lambda to read and write to Amazon DynamoDB. We will run through a demo of setting up a simple serverless blogging web application that allows user authentication and the ability to create posts and comments.
With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we'll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.
(CMP407) Lambda as Cron: Scheduling Invocations in AWS LambdaAmazon Web Services
Do you need to run an AWS Lambda function on a schedule, without an event to trigger the invocation? This session shows how to use an Amazon CloudWatch metric and CloudWatch alarms, Amazon SNS, and Lambda so that Lambda triggers itself every minute—no external services required! From here, other Lambda jobs can be scheduled in crontab-like format, giving minute-level resolution to your Lambda scheduled tasks. During the session, we build this functionality up from scratch with a Lambda function, CloudWatch metric and alarms, sample triggers, and tasks.
AWS re:Invent 2016: Amazon CloudWatch Logs and AWS Lambda: A Match Made in He...Amazon Web Services
In this session, we cover three common scenarios that include Amazon CloudWatch Logs and AWS Lambda. First, you learn how to build an Elasticsearch cluster from historical data using Amazon S3, Lambda, and CloudWatch Logs. Next, you learn how to add details to CloudWatch alarm notifications using Amazon SNS and Lambda. Finally, we show you how to bring Elastic Load Balancing logs to CloudWatch Logs using S3 bucket triggers from Lambda.
Serverless Patterns: “No server is easier to manage than no server” - AWS Sec...Amazon Web Services
In this talk, we’ll take well known architectural patterns such as 3-tier web application, stream processing, scheduled jobs and show how they can be realized without needing to manage servers.
(GAM401) Build a Serverless Mobile Game w/ Cognito, Lambda & DynamoDBAmazon Web Services
Get a hands-on walkthrough of how to quickly build a mobile game with online services like user authentication, downloadable content, and social features. Using the AWS Mobile SDK for Unity, iOS, and Android, it's easier than ever to build a game with these services. This session provides a step-by-step approach to add features to your game such as user identity management, dynamic content updates, cross-platform data sync, and more. We demonstrate how to use the AWS Mobile SDK to securely interact with services such as Amazon Cognito, Amazon DynamoDB, Amazon S3, and AWS Lambda.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this session, you learn what you need to get started quickly, including a review of key features, a live demonstration, how to use AWS Lambda with Amazon S3 event notifications and Amazon DynamoDB streams, and tips on getting the most out of Lambda functions.
Amazon Lumberyard is a free, cross-platform, 3D game engine for you to create the highest-quality games, connect your games to the vast compute and storage of the AWS Cloud, and engage fans on Twitch. Amazon GameLift, a managed service for deploying, operating, and scaling session-based multiplayer games, reduces the time required to build a multiplayer backend from thousands of hours to just minutes. Available for developers using Amazon Lumberyard, Amazon GameLift is built on AWS’s highly available cloud infrastructure and allows you to quickly scale high-performance game servers up and down to meet player demand – without any additional engineering effort or upfront costs.
AWS re:Invent 2016: All Your Chats are Belong to Bots: Building a Serverless ...Amazon Web Services
Bots are eating the world! Wild Rydes (www.wildrydes.com), a new startup that is building the world’s leading mobile/VR/AR unicorn transportation system, has decided to use serverless chatbots to staff its customer service department. As it scales to millions of users, Wild Rydes needed a scalable way to meet the customer service needs of its customers instead of relying on human customer service agents. Wild Rydes needs your help to implement its vision.
In this workshop, you will help Wild Rydes launch the future of customer service. You will build a customer service bot for Facebook that runs on AWS Lambda and Amazon API Gateway. You’ll enable the bot to respond intelligently to customers by building in Natural Language Processing (NLP). The bot will use an event-driven architecture in which Lambda functions trigger workflows that pull customer responses from a Knowledge Base of Q&A. You’ll also write a function to trigger a manual approval request to a Slack channel, so that Wild Rydes’ technical staff can approve or reject messages from the bot to the customer. Finally, you’ll also learn to use Amazon S3, Amazon DynamoDB, and Amazon Elasticsearch Service to log all incoming requests and create live analytical dashboards, such as for sentiment analysis, to track customer satisfaction.
Serverless architectures allow you to build and run applications and services without having to manage infrastructure. With serverless architectures, your application still runs on servers, but all the server management is done by AWS. In this session, you will learn how to build applications and services using a serverless architecture. We will discuss how you can use AWS Lambda to run code for any type of application or backend service; Amazon DynamoDB to store application data with high scalability and redundancy; and Amazon API Gateway to create and manage secure API endpoints. We will run through a demo setting up a web application using this architecture, and we will discuss best practices and patterns used by our customers to run serverless applications.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this session, you learn what you need to get started quickly, including a review of key features, a live demonstration, guidelines on how to use AWS Lambda with Amazon S3 event notifications and Amazon DynamoDB streams, and tips on getting the most out of Lambda functions.
AWS re:Invent 2016: Monitoring, Hold the Infrastructure: Getting the Most fro...Amazon Web Services
This document discusses monitoring AWS Lambda functions. It provides an overview of AWS Lambda, important concepts like triggers and statelessness. It also covers best practices, examples of AWS Lambda usage, and how to add monitoring. Specifically, it recommends adding a line to CloudWatch logs to report metrics to monitoring systems like Datadog. The speaker then demonstrates creating and monitoring a sample AWS Lambda function.
The document discusses various ways to use the ZFS file system on Amazon EC2 instances. It describes ZFS as a file system and logical volume manager with features like data protection, high storage capacities, and snapshots. It provides instructions for installing and using ZFS on Linux, OmniOS, and FreeBSD AMIs, including attaching EBS volumes to an instance and creating ZFS pools and filesystems on them similar to using physical disks.
The AWS Lambda is now available in Singapore and we are excited to invite you to participate in a webinar to learn more about the service and ask questions live throughout the webinar and receive responses during the Q&A session. In this one hour session, you will get to understand key AWS Lambda features, learn the AWS Lambda programming model and get tips on getting the most out of AWS Lambda.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this webinar you’ll learn what you need to quickly begin building mobile, tablet, or IoT applications that use AWS Lambda as a serverless back-end. You’ll also hear about Amazon Web Service’s Event-Driven Compute strategy and see demonstrations that use Lambda to respond to events from Amazon S3 notifications and Amazon DynamoDB streams.
This document discusses AWS Lambda, a platform as a service for event-driven microservices. It provides an introduction and overview of AWS Lambda and how it can be used to process events from services like S3, Kinesis, and DynamoDB using Node.js functions. Examples are given of how AWS Lambda could be used to build a serverless home security system that processes images uploaded to S3.
The document provides an introduction to TensorFlow and neural networks. It discusses perceptron classifiers for MNIST data, convolutional neural networks for image recognition, recurrent neural networks for language modeling, and generating poems with RNNs. It also introduces Keras as an easier way to build neural networks and provides contact information for the author and upcoming machine learning conferences.
As serverless architectures become more popular, AWS customers need a framework of patterns to help them deploy their workloads without managing servers or operating systems.
This document discusses new features and capabilities for serverless applications on AWS Lambda. Key points include:
- AWS Serverless Application Model (SAM) allows defining serverless apps in a common language and integrates with CloudFormation.
- New features for serverless CI/CD pipelines include pulling source from GitHub/CodeCommit with CodePipeline and building with CodeBuild.
- Environment variables are now supported for Lambda functions.
- X-Ray provides visibility for tracing calls between Lambda and other AWS services.
- Other updates include Kinesis iterator, C# runtime, dead letter queues, and integrations with services like API Gateway, DynamoDB, and Step Functions for orchestrating functions.
This talk will be a 2-300 level discussion on Serverless Architectures on AWS. We’ll first explore the Serverless ecosystem on AWS, looking at some particular use cases for Serverless. Looking through the lens of AWS customers, we’ll look at the typical Serverless journey, as well some of the key emerging patterns and benefits of Serverless Architectures. We’ll also touch some of the key challenges in a distributed environment and some potential solutions and tools that customers might want to consider.
The document describes building a real-time chat system using serverless architecture on AWS. It shows how to use AWS Lambda functions, API Gateway, DynamoDB, Cognito, IoT, S3 and CloudFront to create an interactive chat application without having to manage servers. The chat system allows users to publish and subscribe to messages in real-time using IoT topics and rules to route messages. Screenshots demonstrate the flow of data and functions within the serverless application.
AWS re:Invent 2016: Building Complex Serverless Applications (GPST404)Amazon Web Services
Provisioning, scaling, and managing physical or virtual servers—and the applications that run on them—has long been a core activity for developers and system administrators. The expanding array of managed AWS cloud services, including AWS Lambda, Amazon DynamoDB, Amazon API Gateway and more, increasingly allows organizations to focus on delivering business value without worrying about managing the underlying infrastructure or paying for idle servers and other fixed costs of cloud services. In this session, we discuss the design, development, and operation of these next-generation solutions on AWS. Whether you're developing end-user web applications or back-end data processing systems, join us in this session to learn more about building your applications without servers.
Building Serverless Backends with AWS Lambda and Amazon API GatewayAmazon Web Services
AWS Lambda is a compute service that runs your code without provisioning or managing servers. Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale.
This session will familiarize you with the basics of AWS Lambda and Amazon API Gateway and demonstrate how to build web, mobile, and IoT backends using these services. You will learn how to setup API endpoints that trigger AWS Lambda functions to handle mobile, web, IoT, and 3rd party API requests. You will also learn how to use Lambda to read and write to Amazon DynamoDB. We will run through a demo of setting up a simple serverless blogging web application that allows user authentication and the ability to create posts and comments.
With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we'll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.
(CMP407) Lambda as Cron: Scheduling Invocations in AWS LambdaAmazon Web Services
Do you need to run an AWS Lambda function on a schedule, without an event to trigger the invocation? This session shows how to use an Amazon CloudWatch metric and CloudWatch alarms, Amazon SNS, and Lambda so that Lambda triggers itself every minute—no external services required! From here, other Lambda jobs can be scheduled in crontab-like format, giving minute-level resolution to your Lambda scheduled tasks. During the session, we build this functionality up from scratch with a Lambda function, CloudWatch metric and alarms, sample triggers, and tasks.
AWS re:Invent 2016: Amazon CloudWatch Logs and AWS Lambda: A Match Made in He...Amazon Web Services
In this session, we cover three common scenarios that include Amazon CloudWatch Logs and AWS Lambda. First, you learn how to build an Elasticsearch cluster from historical data using Amazon S3, Lambda, and CloudWatch Logs. Next, you learn how to add details to CloudWatch alarm notifications using Amazon SNS and Lambda. Finally, we show you how to bring Elastic Load Balancing logs to CloudWatch Logs using S3 bucket triggers from Lambda.
Serverless Patterns: “No server is easier to manage than no server” - AWS Sec...Amazon Web Services
In this talk, we’ll take well known architectural patterns such as 3-tier web application, stream processing, scheduled jobs and show how they can be realized without needing to manage servers.
(GAM401) Build a Serverless Mobile Game w/ Cognito, Lambda & DynamoDBAmazon Web Services
Get a hands-on walkthrough of how to quickly build a mobile game with online services like user authentication, downloadable content, and social features. Using the AWS Mobile SDK for Unity, iOS, and Android, it's easier than ever to build a game with these services. This session provides a step-by-step approach to add features to your game such as user identity management, dynamic content updates, cross-platform data sync, and more. We demonstrate how to use the AWS Mobile SDK to securely interact with services such as Amazon Cognito, Amazon DynamoDB, Amazon S3, and AWS Lambda.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this session, you learn what you need to get started quickly, including a review of key features, a live demonstration, how to use AWS Lambda with Amazon S3 event notifications and Amazon DynamoDB streams, and tips on getting the most out of Lambda functions.
Amazon Lumberyard is a free, cross-platform, 3D game engine for you to create the highest-quality games, connect your games to the vast compute and storage of the AWS Cloud, and engage fans on Twitch. Amazon GameLift, a managed service for deploying, operating, and scaling session-based multiplayer games, reduces the time required to build a multiplayer backend from thousands of hours to just minutes. Available for developers using Amazon Lumberyard, Amazon GameLift is built on AWS’s highly available cloud infrastructure and allows you to quickly scale high-performance game servers up and down to meet player demand – without any additional engineering effort or upfront costs.
AWS re:Invent 2016: All Your Chats are Belong to Bots: Building a Serverless ...Amazon Web Services
Bots are eating the world! Wild Rydes (www.wildrydes.com), a new startup that is building the world’s leading mobile/VR/AR unicorn transportation system, has decided to use serverless chatbots to staff its customer service department. As it scales to millions of users, Wild Rydes needed a scalable way to meet the customer service needs of its customers instead of relying on human customer service agents. Wild Rydes needs your help to implement its vision.
In this workshop, you will help Wild Rydes launch the future of customer service. You will build a customer service bot for Facebook that runs on AWS Lambda and Amazon API Gateway. You’ll enable the bot to respond intelligently to customers by building in Natural Language Processing (NLP). The bot will use an event-driven architecture in which Lambda functions trigger workflows that pull customer responses from a Knowledge Base of Q&A. You’ll also write a function to trigger a manual approval request to a Slack channel, so that Wild Rydes’ technical staff can approve or reject messages from the bot to the customer. Finally, you’ll also learn to use Amazon S3, Amazon DynamoDB, and Amazon Elasticsearch Service to log all incoming requests and create live analytical dashboards, such as for sentiment analysis, to track customer satisfaction.
Serverless architectures allow you to build and run applications and services without having to manage infrastructure. With serverless architectures, your application still runs on servers, but all the server management is done by AWS. In this session, you will learn how to build applications and services using a serverless architecture. We will discuss how you can use AWS Lambda to run code for any type of application or backend service; Amazon DynamoDB to store application data with high scalability and redundancy; and Amazon API Gateway to create and manage secure API endpoints. We will run through a demo setting up a web application using this architecture, and we will discuss best practices and patterns used by our customers to run serverless applications.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this session, you learn what you need to get started quickly, including a review of key features, a live demonstration, guidelines on how to use AWS Lambda with Amazon S3 event notifications and Amazon DynamoDB streams, and tips on getting the most out of Lambda functions.
AWS re:Invent 2016: Monitoring, Hold the Infrastructure: Getting the Most fro...Amazon Web Services
This document discusses monitoring AWS Lambda functions. It provides an overview of AWS Lambda, important concepts like triggers and statelessness. It also covers best practices, examples of AWS Lambda usage, and how to add monitoring. Specifically, it recommends adding a line to CloudWatch logs to report metrics to monitoring systems like Datadog. The speaker then demonstrates creating and monitoring a sample AWS Lambda function.
The document discusses various ways to use the ZFS file system on Amazon EC2 instances. It describes ZFS as a file system and logical volume manager with features like data protection, high storage capacities, and snapshots. It provides instructions for installing and using ZFS on Linux, OmniOS, and FreeBSD AMIs, including attaching EBS volumes to an instance and creating ZFS pools and filesystems on them similar to using physical disks.
The AWS Lambda is now available in Singapore and we are excited to invite you to participate in a webinar to learn more about the service and ask questions live throughout the webinar and receive responses during the Q&A session. In this one hour session, you will get to understand key AWS Lambda features, learn the AWS Lambda programming model and get tips on getting the most out of AWS Lambda.
AWS Lambda is a new compute service that runs your code in response to events and automatically manages compute resources for you. In this webinar you’ll learn what you need to quickly begin building mobile, tablet, or IoT applications that use AWS Lambda as a serverless back-end. You’ll also hear about Amazon Web Service’s Event-Driven Compute strategy and see demonstrations that use Lambda to respond to events from Amazon S3 notifications and Amazon DynamoDB streams.
This document discusses AWS Lambda, a platform as a service for event-driven microservices. It provides an introduction and overview of AWS Lambda and how it can be used to process events from services like S3, Kinesis, and DynamoDB using Node.js functions. Examples are given of how AWS Lambda could be used to build a serverless home security system that processes images uploaded to S3.
The document provides an introduction to TensorFlow and neural networks. It discusses perceptron classifiers for MNIST data, convolutional neural networks for image recognition, recurrent neural networks for language modeling, and generating poems with RNNs. It also introduces Keras as an easier way to build neural networks and provides contact information for the author and upcoming machine learning conferences.
TensorFlow can be installed and run in a distributed environment using Docker. The document discusses setting up TensorFlow workers and parameter servers in Docker containers using a Docker compose file. It demonstrates building Docker images for each role, and configuring the containers to communicate over gRPC. A Jupyter server container is also built to host notebooks. The distributed TensorFlow environment is deployed locally for demonstration purposes. Future directions discussed include running the distributed setup on a native cluster using tools like Docker Swarm or RancherOS, and testing TensorFlow with GPU support in Docker.
TensorFlow is an open source software library for machine learning developed by Google. It provides primitives for defining functions on tensors and automatically computing their derivatives. TensorFlow represents computations as data flow graphs with nodes representing operations and edges representing tensors. It is widely used for neural networks and deep learning tasks like image classification, language processing, and speech recognition. TensorFlow is portable, scalable, and has a large community and support for deployment compared to other frameworks. It works by constructing a computational graph during modeling, and then executing operations by pushing data through the graph.
AWS Lambda and Serverless framework: lessons learned while building a serverl...Luciano Mammino
The document discusses lessons learned from building a serverless company. It introduces Planet 9 Energy and their use of AWS Lambda and the Serverless framework. Key topics covered include security, quality assurance, developer experience, costs, and lessons learned. Some challenges discussed are debugging, API Gateway custom domains, and Lambda limitations. The document emphasizes that serverless architectures provide infinite scalability at low cost but also have some limitations that require management.
2016 아이펀팩토리 Dev Day 발표 자료
강연 제목 : Docker 로 Linux 없이 Linux 환경에서 개발하기
발표자 : 김진욱 CTO
<2016>
- 일시 : 2016년 9월 28 수요일 12:00~14:20
- 장소 : 넥슨 판교 사옥 지하 1층 교육실
Building a Machine Learning App with AWS LambdaSri Ambati
Ludi Rehaks' meetup on 03.17.16
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Microservice Architecture on AWS using AWS Lambda and Docker ContainersDanilo Poccia
This document summarizes microservice architecture on AWS using AWS Lambda and Docker containers. It discusses why organizations adopt microservices and how to design smaller loosely coupled services. It then covers how to use AWS services like EC2 Container Service, Lambda, ECS, and others to build and deploy microservices. Specific topics covered include distributed systems, security, testing, monitoring, discovery, deployment pipelines and more. Examples of Netflix and Hailo architectures on AWS are also mentioned.
Getting Started with AWS Lambda and the Serverless Cloud by Jim Tran, Princip...Amazon Web Services
1) The document provides an overview of AWS Lambda and serverless computing on AWS, including how AWS Lambda works, common use cases, and best practices.
2) It explains that AWS Lambda allows users to run code in response to events without provisioning or managing servers, and only pays for the compute time used.
3) The document demonstrates sample serverless architectures using AWS Lambda along with other AWS services, and provides guidance on best practices like using versions and aliases, function networking, authorization, and monitoring.
TensorFlow에 대한 분석 내용
- TensorFlow?
- 배경
- DistBelief
- Tutorial - Logistic regression
- TensorFlow - 내부적으로는
- Tutorial - CNN, RNN
- Benchmarks
- 다른 오픈 소스들
- TensorFlow를 고려한다면
- 설치
- 참고 자료
This document provides an introduction to deep neural networks using TensorFlow. It begins with an example classification problem to motivate deep learning. It then discusses three types of deep learning models: unsupervised learning, convolutional neural networks, and recurrent neural networks. The remainder of the document demonstrates how to build deep learning models with TensorFlow, including logistic regression, multi-layer perceptrons, and convolutional neural networks. Code examples are provided in Jupyter notebooks on GitHub.
Using Docker for GPU Accelerated ApplicationsNVIDIA
Build and run Docker containers leveraging NVIDIA GPUs. Containerizing GPU applications provides several benefits, among them:
* Reproducible builds
* Ease of deployment
* Isolation of individual devices
* Run across heterogeneous driver/toolkit environments
* Requires only the NVIDIA driver to be installed
* Enables "fire and forget" GPU applications
* Facilitate collaboration
Docker and Windows: The State of the UnionElton Stoneman
Session from Docker London, covering Docker on Windows:
- the Docker platform on Windows
- limitations and differences
- Dockerizing Windows applications
- running a hybrid swarm
Large Scale Deep Learning with TensorFlow Jen Aman
Large-scale deep learning with TensorFlow allows storing and performing computation on large datasets to develop computer systems that can understand data. Deep learning models like neural networks are loosely based on what is known about the brain and become more powerful with more data, larger models, and more computation. At Google, deep learning is being applied across many products and areas, from speech recognition to image understanding to machine translation. TensorFlow provides an open-source software library for machine learning that has been widely adopted both internally at Google and externally.
Deploying deep learning models with Docker and KubernetesPetteriTeikariPhD
Short introduction for platform agnostic production deployment with some medical examples.
Alternative download: https://www.dropbox.com/s/qlml5k5h113trat/deep_cloudArchitecture.pdf?dl=0
Managed services such as AWS Lambda and API Gateway allow developers to focus on value adding development instead of IT heavy lifting. This workshop introduces how to build a simple REST blog backend using AWS technologies and the serverless framework.
DevOps Fest 2019. Alex Casalboni. Configuration management and service discov...DevOps_Fest
Your system is composed of highly decoupled, independent, fast, and modular microservices. But how can they share common configurations, dynamic endpoints, database references, and properly rotate secrets? Based on the size and complexity of your serverless system, you may simply use environment variables or eventually opt for some sort of centralized store. And then how do integrate all of this with monitoring and automation tooling? During this session, I will present the ideal solutions and some of the alternatives available on AWS (such as AWS Systems Manager Parameter Store and AWS Secrets Manager). I will also discuss the best use cases for each solution and the corresponding best practices to achieve the highest standards for security and performance.
My presentation about Serverless Architectures in JavaDay Lviv, June 2016. It covers AWS Lambda and related AWS Services. LiveDemo have got terraform and apex.
Alex Casalboni - Configuration management and service discovery - Codemotion ...Codemotion
Your system is composed of highly decoupled, independent, fast, and modular microservices. But how can they share common configurations, dynamic endpoints, database references, and properly rotate secrets? Based on the size and complexity of your serverless system, you may simply use environment variables or eventually opt for some sort of centralized store. During this session, I will present the ideal solutions and some of the alternatives available on AWS (such as Parameter Store and AWS Secrets Manager). I will also discuss the best use cases for each solution
AWS Lambda with Serverless Framework and JavaManish Pandit
Serverless is a node.js based framework that makes creating, deploying, and managing serverless functions a breeze. We will use AWS Lambda as our FaaS (Function-as-a-Service) provider, although Serverless supports IBM OpenWhisk and Microsoft Azure as well.
In this session, we will talk about Serverless Applications, and Create and deploy a java-maven based AWS Lambda API. We will also explore the command line interface to manage lambda, which is provided out of the box by serverless framework.
This document provides instructions for developing an API plug-in for CloudStack version 4.5 using SolidFire as an example. It outlines the steps to create a new Maven project called "abc123" by copying the existing "solidfire" project template. It describes updating files and dependencies to reference the new "abc123" project instead of "solidfire". The document then explains how to create the key classes needed to implement the plug-in, map it to API commands, and deploy the final JAR file. The goal is to extend CloudStack's API with new commands that can invoke functionality from a third-party product via the plug-in.
An overview of the SDKs and tools available when working with AWS. Review of sample application code and a live demo of a deployment using AWS Elastic Beanstalk.
The document discusses different approaches for describing and deploying applications in the cloud, including declarative and procedural options. It provides examples of AWS CloudFormation templates, OpenStack Heat templates, Apache Whirr specifications, and Brooklyn application blueprints. It also outlines ongoing work to standardize application modeling through the OASIS TOSCA specification.
AWS Presents: Infrastructure as Code on AWS - ChefConf 2015Chef
Find out how to create automated infrastructure deployments using versioned Infrastructure as Code - CloudFormation templates on AWS. This talk will walk through two example CloudFormation templates. The first template will show how to use CloudFormation via AWS cli commands to create a Chef Server 12 instance and have it upload it’s client validation pem into private S3 bucket also created by the template. The second template will show how to use CloudFormation to create multiple client node instances in AWS EC2 and have them automatically bootstrap into the new Chef 12 Server instance. Links will be provided to the CloudFormation template code used for the demo for example purposes.
https://youtu.be/WXLDdGxfEsI
Amazon Web Services and the AWS SDK for PHP continue to put more power into the hands of PHP developers to build robust and scalable web applications. With version 2 of the SDK, developers now have an even more powerful library for interacting with AWS built on top of existing open source software like the Guzzle HTTP framework and the Symfony 2 Event Dispatcher. In this session you will learn about Amazon Web Services, how to use the AWS SDK for PHP, and how you can easily deploy and scale your applications to the cloud with AWS services, including AWS Elastic Beanstalk.
Spring and Cloud Foundry; a Marriage Made in HeavenJoshua Long
Spring and Cloud Foundry: a Marriage Made in Heaven. This talk introduces how to build Spring applications on top of Cloud Foundry, the open source PaaS from VMware
This document introduces GradleFx, a Flex build tool that uses Gradle. It discusses key features of GradleFx such as supporting SWC, SWF, and AIR compilation; tasks for cleaning, compiling, packaging, and testing; and conventions for project structure and dependencies. Advanced topics covered include compiler options, JVM arguments, dependency configurations, and additional steps for AIR projects and FlexUnit testing. An example Gradle build script is provided.
This document discusses microservices architectures and provides examples of tools used in microservices architectures like those implemented at Netflix. It describes common microservices patterns like service discovery (Eureka), configuration management (Archaius), load balancing (Ribbon), circuit breaking (Hystrix), monitoring (Turbine), edge services (Zuul), and logging (Blitz4j). It also discusses using these tools with Spring Cloud and provides code samples for configuring services using Netflix OSS and Spring Cloud.
This document discusses an alternative approach to web application development using JavaScript and web services instead of the traditional approach of serving HTML fragments from a servlet. The key points of this approach are:
1) The browser makes AJAX requests directly to web services instead of to a servlet, and uses JavaScript to manipulate the DOM instead of receiving HTML fragments.
2) Performance is improved by distributing the load across clients instead of a single server.
3) It follows a SOA approach by separating the presentation, business logic, and data layers.
Disaster Recovery Site on AWS - Minimal Cost Maximum Efficiency (STG305) | AW...Amazon Web Services
Disaster Recovery Site on AWS: Minimal Cost Maximum Efficiency discusses setting up disaster recovery sites on AWS for minimal cost and maximum efficiency. Common disaster recovery architectures on AWS include pilot light, where a scaled-down copy of production resources is kept running, and backup and restore, where backups are taken and restored in an outage. Customer case studies demonstrate cost savings of up to 70% for disaster recovery sites on AWS compared to on-premises solutions.
This document discusses serverless computing on AWS using AWS Lambda and AWS Fargate. It provides an overview of the anatomy of an AWS Lambda function, including the handler function, event and context objects, dependencies and common helper functions. It also describes how to structure serverless applications using Lambda functions and how AWS Lambda layers can be used to share common code between functions. Finally, it outlines the architecture of running serverless containers on AWS Fargate without having to manage servers or clusters.
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Malibou Pitch Deck For Its €3M Seed Roundsjcobrien
French start-up Malibou raised a €3 million Seed Round to develop its payroll and human resources
management platform for VSEs and SMEs. The financing round was led by investors Breega, Y Combinator, and FCVC.
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
14 th Edition of International conference on computer visionShulagnaSarkar2
About the event
14th Edition of International conference on computer vision
Computer conferences organized by ScienceFather group. ScienceFather takes the privilege to invite speakers participants students delegates and exhibitors from across the globe to its International Conference on computer conferences to be held in the Various Beautiful cites of the world. computer conferences are a discussion of common Inventions-related issues and additionally trade information share proof thoughts and insight into advanced developments in the science inventions service system. New technology may create many materials and devices with a vast range of applications such as in Science medicine electronics biomaterials energy production and consumer products.
Nomination are Open!! Don't Miss it
Visit: computer.scifat.com
Award Nomination: https://x-i.me/ishnom
Conference Submission: https://x-i.me/anicon
For Enquiry: Computer@scifat.com
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
Mobile App Development Company In Noida | Drona InfotechDrona Infotech
Drona Infotech is a premier mobile app development company in Noida, providing cutting-edge solutions for businesses.
Visit Us For : https://www.dronainfotech.com/mobile-application-development/
How Can Hiring A Mobile App Development Company Help Your Business Grow?ToXSL Technologies
ToXSL Technologies is an award-winning Mobile App Development Company in Dubai that helps businesses reshape their digital possibilities with custom app services. As a top app development company in Dubai, we offer highly engaging iOS & Android app solutions. https://rb.gy/necdnt
14. GET
Static HTML
CSS/Media
Rich JavaScript Apps
S3 StorageCloudFront
GET
POST
PUT
DELETE
Dynamic Data
Data from Database
Data from External Service
dataAPI Gateway Lambda
ajax
http
event
USER
15. LAMBDA
- AWS Computing Service
- Designed to reflect async Actor Model
- Resilient and Scaleable
- 512 RAM
- Supports Runtimes
- Java
- Python
- NodeJS
- Go (implicitly)
- Max Timeout 5 mins
- Pricing:
- 0.20$ per million requests.
- Billable 100 milliseconds
17. API Gateway
Lambda
+
- API Management Tool
- Authorization + Custom Authorizer
- Defines: Environment Variables for Lambda
- Can be defined with Swagger and imported
- Code Supports Versioning
- Integrated with CloudWatch
- Lambda Containers are Cached for 5 minutes
- Can be deployed with “apex.run” tool
- User can write files in /tmp
29. BUILD SERVERLESS APPLICATION
• COGNITO - MAKE IT SECURE
• DYNAMODB – STORE DATA
• S3 BUCKET - KEEP WEB CONTENT
• LAMBDA - DYNAMIC CONTENT
• TERRAFORM - BUILD INFRASTRUCTURE
30. USER
AWS
Services
Amazon
Cognito
Client
Application
Identity
Provider
1. Using the
Application
2. Send Identity
Provider Credentials
3. Get
Authentication
Token
4. Send Identity Pool ID +
Authentication Token
5. Check Authebtication
Token with Identity Provider
6. Get Identity ID + AWS
Temp Credentials for the
Authenticated Role
7. Call AWS Services using
AWS Temp Credentials
All AWS Services
Cognito
Serverless is a hot topic in the software architecture world. We’re already seeing books, open source frameworks, plenty of vendor products, and even a conference dedicated to the subject. But what is Serverless and why is (or isn’t) it worth considering? Through this session I will try to enlighten you a little on these questions.Like many trends in software there’s no clear view of what ‘Serverless’ is:
1. Serverless was first used to describe applications that significantly or fully depend on 3rd party applications / services (‘in the cloud’) to manage server-side logic and state. These are typically ‘rich client’ applications (think single page web apps, or mobile apps) that use the vast ecosystem of cloud: databases, authentication services etc.
2. Serverless can also mean applications where some amount of server-side logic is still written by the application developer but unlike traditional architectures it runs in stateless compute containers that are event-triggered, ephemeral (may only last for one invocation), and fully managed by a 3rd party. (Thanks to ThoughtWorks for their definition in their most recent Tech Radar.)
One way to think of this is ‘Functions as a service / FaaS’ .
3. AWS Lambda is one of the most popular implementations of FaaS at present, but there are others
The term ‘Serverless’ is confusing since with such applications there are both server hardware and server processes running somewhere, but the difference to normal approaches is that the organization building and supporting a ‘Serverless’ application is not looking after the hardware or the processes - they are outsourcing this to a vendor.
You can host your static website entirely on Amazon S3. Once you enable your bucket for static website hosting, all your content is accessible to web browsers via the Amazon S3 website endpoint for your bucket.
Each bucket serves a website namespace (e.g. "www.example.com"). Requests for your host name (e.g. "example.com" or "www.example.com") can be routed to the contents in your bucket. You can also redirect requests to another host name (e.g. redirect "example.com" to "www.example.com").
AWS Lambda is arguably the most exciting service released in AWS since EC2. Lambda is a service that lets you run code on someone else’s machine. All you need to do is pick the runtime your code can run in, and provide the code.
Currently, the supported runtimes are:
- Node.js: v0.10.36, v4.3.2
- Java: Java 8
- Python: Python 2.7
In AWS Lambda, Lambda functions and event sources are the core components in AWS Lambda. An event source is the entity that publishes events, and a Lambda function is the custom code that processes the events. Supported event sources refer to those AWS services that can be preconfigured to work with AWS Lambda. The configuration is referred to as event source mapping, which maps an event source to a Lambda function. It enables automatic invocation of your Lambda function when events occur.
Examples:
1. Akka actor chain can be implemented with help of two services: Dynamodb and Lambda
2. Lifecycle hooks which triggered when autoscaling group fired an up/down policy event. Lambda could make some preparation before a new vm is up
3. CRON/ Periodic task which check one metric or another. For instance, Lambda which monitors number of tasks in a custom tasks queue and sends metrics/alarm into CW when it cross the threshold
4. CI/CD
5. Backend for Api Gateway
API Gateway is another exciting service on AWS that aims to ease the task of creating APIs. You define your resources and their models, request transformations, locations where requests should be proxied to, response transformations; and you get a functioning API without deploying a single machine. An API Gateway endpoint can use a Lambda function as its backend, which is the sweet spot touted by serverless architecture advocates.
Like every system in its early life, API Gateway and Lambda have minor bugs and areas of improvement. Overall, the combination of these technologies is lethal, and I’m interested in seeing how functionality in existing applications can be chipped away to harness the strengths of these so-called serverless architectures.
You can use Maven or Gradle to build you Lambda function in Java.
You can use Maven or Gradle to build you Lambda function in Java.
Allow the lambda direct access to our database
Add Lambda and DB in the same VPC
Assign a private ip to DB
Use this IP from Lambda
Introduce Authorizer, yet another feature in Api Gateway
It makes sure an access token is present in HTTP request, token is valid and verifies presence of necessary data in the tokenBase on the token content it accepts or denies the request
Introduce SSO service which issues access tokens
It talks to federation-sts and helps end user to authenticate against Accenture IDP
Disadvantages:
We have to manage infrastructure for SSO service
With Elastic Beanstalk, you can quickly deploy and manage applications in the AWS Cloud without worrying about the infrastructure that runs those applications. AWS Elastic Beanstalk reduces management complexity without restricting choice or control. You simply upload your application, and Elastic Beanstalk automatically handles the details of capacity provisioning, load balancing, scaling, and application health monitoring.
Amazon Cognito lets you easily add user sign-in to your mobile and web apps. With Amazon Cognito, you can also authenticate users through social identity providers such as Facebook, Twitter, or Amazon, or by using your own identity solution.
This call is possible thanks to Fine-Grained Access Control for DynamoDB
To implement this kind of fine-grained access control, you write an IAM permissions policy that specifies conditions for accessing database.
The permissions policy grants permissions that allow a set of DynamoDB actions on the answers table. It uses the dynamodb:LeadingKeys condition key to restrict access for unauthorized users.
The Condition entry in this policy uses a substitution variable to grab the Cognito ID from the request. This ensures that only authenticated Cognito users can access the table, and that they only have access to the documents that they created.
All you need is to attach this policy to Cognito IAM Role and you will be able to access DB from client’s code completely secure
Sometimes you may want to hide the logic from prying eyes for security reason or don’t want to share the code
This could be put into Lambda
Lambda supports Java runtime
One major pain point of using Lambda/API Gateway/Cognito is the difficulty of setting things up. So the project uses Terraform to ease that difficulty. Terraform is a tool that lets you define configurations, which it can run to provision resources on datacenters by providers such as AWS, Azure and Google Cloud. In this project, Terraform is used to provision the Lambda function/Cognito Identity Pool/DynamoDb/S3 Bucket. With Terraform installed, the project can be deployed by simply invoking:
- terraform apply
- terraform destroy
Developing applications using Lambda differs from the way we are typically used to, in terms of codebase management, tooling, frameworks, testing and deployment. On one hand, Lambda offers us the entire AWS ecosystem with simple configurations, and on the other, it requires us to rethink how we approach building even small applications. There aren’t yet enough success stories and best practices out there to give one the confidence to build large applications using Lambda, but there’s enough information to start farming out computation heavy processes to Lambda. Lambda especially shines because of its ability to scale along with its workload.