As serverless architectures become more popular, customers need a framework of patterns to help them to identify how to leverage AWS to deploy their workloads without managing servers or operating systems. In this session, we describe reusable serverless patterns while considering costs. For each pattern, we provide operational, security, and reliability best practices and discuss potential challenges. We also demonstrate the implementation of some of the patterns in a reference solution. This session can help you recognize services and applications for serverless architectures in your own organization and understand areas of potential savings and increased agility and reliability.
This document discusses building continuous integration and continuous delivery (CI/CD) pipelines for serverless applications. It covers topics like understanding CI/CD for serverless applications given their event-driven nature, developing a CI/CD workflow checklist, using infrastructure as code with AWS CloudFormation templates and the AWS Serverless Application Model (SAM) to deploy serverless applications, configuring multiple environments, and using variables in Lambda functions and API Gateway stages.
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.
Build and run applications without thinking about serversAmazon Web Services
Organizations need to gain insight and knowledge from a growing number of Internet of Things (IoT) APIs clickstreams comprised of unstructured and log data sources. However, organizations are often limited by legacy data warehouses and ETL processes that were designed for transactional data. In this session, we’ll introduce the key ETL features of AWS Glue through use cases ranging from scheduled nightly data warehouse loads to near real-time, event-driven ETL flows for your data lake. We’ll also discuss how to build scalable, efficient and serverless ETL pipelines using AWS Glue.
This document provides an overview of serverless development using AWS Lambda. It discusses common use cases for serverless applications including web apps, data processing, chatbots, backends, and IT automation. It also covers topics like pricing, resource allocation, available event sources and services, and development tools. The document contains code samples and screenshots related to building serverless applications on AWS Lambda.
This document discusses new features of AWS Lambda including:
- AWS Serverless Application Model (SAM) which provides a common language for describing serverless applications across the ecosystem.
- Serverless continuous integration/continuous delivery (CI/CD) pipelines using services like AWS CodePipeline and AWS CodeBuild to build and deploy Lambda applications.
- Dead letter queues which allow unprocessed events to be sent to an SQS queue or SNS topic to preserve events if the function code has an issue.
- Environment variables which can now be used within Lambda functions.
- Support for C# and .NET Core runtimes for Lambda functions.
- AWS Step Functions which allows orchestrating multiple Lambda
Serverless Architectural Patterns and Best Practices (ARC305-R2) - AWS re:Inv...Amazon Web Services
The document discusses serverless architectures and best practices. It covers topics like serverless foundations, web applications, stream processing, data lakes, and machine learning. It provides an overview of AWS serverless offerings and architectural patterns for building serverless applications and processing streaming data with services like AWS Lambda, Amazon API Gateway, Amazon Kinesis, Amazon S3, and AWS Step Functions.
SRV203 Getting Started with AWS Lambda and the Serverless CloudAmazon Web Services
Serverless computing allows you to build and run applications without the need for provisioning or managing servers. With serverless computing, you can build web, mobile, and IoT backends; run stream processing or big data workloads; run chatbots, and more. In this session, you'll learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We'll introduce you to the basics of building with Lambda and how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We'll also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.
This document discusses building continuous integration and continuous delivery (CI/CD) pipelines for serverless applications. It covers topics like understanding CI/CD for serverless applications given their event-driven nature, developing a CI/CD workflow checklist, using infrastructure as code with AWS CloudFormation templates and the AWS Serverless Application Model (SAM) to deploy serverless applications, configuring multiple environments, and using variables in Lambda functions and API Gateway stages.
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.
Build and run applications without thinking about serversAmazon Web Services
Organizations need to gain insight and knowledge from a growing number of Internet of Things (IoT) APIs clickstreams comprised of unstructured and log data sources. However, organizations are often limited by legacy data warehouses and ETL processes that were designed for transactional data. In this session, we’ll introduce the key ETL features of AWS Glue through use cases ranging from scheduled nightly data warehouse loads to near real-time, event-driven ETL flows for your data lake. We’ll also discuss how to build scalable, efficient and serverless ETL pipelines using AWS Glue.
This document provides an overview of serverless development using AWS Lambda. It discusses common use cases for serverless applications including web apps, data processing, chatbots, backends, and IT automation. It also covers topics like pricing, resource allocation, available event sources and services, and development tools. The document contains code samples and screenshots related to building serverless applications on AWS Lambda.
This document discusses new features of AWS Lambda including:
- AWS Serverless Application Model (SAM) which provides a common language for describing serverless applications across the ecosystem.
- Serverless continuous integration/continuous delivery (CI/CD) pipelines using services like AWS CodePipeline and AWS CodeBuild to build and deploy Lambda applications.
- Dead letter queues which allow unprocessed events to be sent to an SQS queue or SNS topic to preserve events if the function code has an issue.
- Environment variables which can now be used within Lambda functions.
- Support for C# and .NET Core runtimes for Lambda functions.
- AWS Step Functions which allows orchestrating multiple Lambda
Serverless Architectural Patterns and Best Practices (ARC305-R2) - AWS re:Inv...Amazon Web Services
The document discusses serverless architectures and best practices. It covers topics like serverless foundations, web applications, stream processing, data lakes, and machine learning. It provides an overview of AWS serverless offerings and architectural patterns for building serverless applications and processing streaming data with services like AWS Lambda, Amazon API Gateway, Amazon Kinesis, Amazon S3, and AWS Step Functions.
SRV203 Getting Started with AWS Lambda and the Serverless CloudAmazon Web Services
Serverless computing allows you to build and run applications without the need for provisioning or managing servers. With serverless computing, you can build web, mobile, and IoT backends; run stream processing or big data workloads; run chatbots, and more. In this session, you'll learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We'll introduce you to the basics of building with Lambda and how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We'll also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.
The document discusses securing serverless applications. It provides an overview of AWS Identity and Access Management (IAM), AWS Lambda, Amazon API Gateway, and Amazon Cognito. It then covers securing serverless microservices by discussing securing AWS Lambda functions using IAM roles and resource policies. It also covers securing Amazon API Gateway by discussing authorization types including Cognito, IAM, and custom authorizers. The document concludes by discussing auditing serverless applications using CloudWatch logs, CloudTrail, and AWS Config.
This document discusses serverless development using AWS Lambda. It provides an overview of common use cases for serverless applications like web apps, data processing, chatbots, backends, and IT automation. It also describes Lambda's event-driven execution model and the various services that can trigger Lambda functions. The document outlines the benefits of serverless such as fine-grained pricing where customers pay for compute time used. It also introduces the AWS Serverless Application Model (SAM) which provides a simplified way to define Lambda functions, APIs, and other resources in a CloudFormation template.
Build and Deploy Serverless Applications with AWS SAM - SRV316 - Chicago AWS ...Amazon Web Services
AWS Serverless Application Model (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. Learn best practices and tricks for using AWS SAM at scale, including how to make the most of its dynamic template capabilities, how to use advanced features, and how to debug serverless applications. Also explore the new open-source AWS SAM translator, and see how AWS SAM works under the hood.
SRV301-Optimizing Serverless Application Data Tiers with Amazon DynamoDBAmazon Web Services
"As a fully managed database service, Amazon DynamoDB is a natural fit for serverless architectures. In this session, we dive deep into why and how to use DynamoDB in serverless applications, followed by a real-world use case from CapitalOne.
First, we dive into the relevant DynamoDB features, and how you can use it effectively with AWS Lambda in solutions ranging from web applications to real-time data processing. We show how some of the new features in DynamoDB, such as Auto Scaling and Time to Live (TTL), are particularly useful in serverless architectures, and distill the best practices to help you create effective serverless applications. In the second part, we talk about how CapitalOne migrated billions of transactions to a completely serverless architecture and built a scalable, resilient and fast transaction platform by leveraging DynamoDB, AWS Lambda and other services within the serverless ecosystem."
¿Qué es eso del desarrollo sin servidores? ¿Qué lenguajes puedo utilizar? ¿Cómo hago cosas como autenticación, o guardar en base de datos, o enviar notificaciones? ¿Esto escala? A todas estas preguntas, y a alguna más, intentaré dar respuesta en esta sesión, donde haré una pequeña demo de montar una app muy sencilla y desplegarla en la nube sin preocuparnos de gestionar infraestructura. Charla realizada por primera vez para AlcarriaConf 2021
Serverless Architecture - Design Patterns and Best PracticesAmazon Web Services
As serverless architectures become more popular, customers are looking for a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems.
This webinar session describes reusable serverless patterns. For each pattern, operational and security best practices with potential pitfalls and nuances will be described. The patterns involve services including but not limited to AWS Lambda, Amazon API Gateway, Amazon Kinesis Data Streams and Data Firehose, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena.
This session can help audience recognise candidates for various serverless architectures in an organisation and understand areas of potential savings and increased agility. For example, using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; CI/CD development pipelines for serverless, which includes testing, deploying, and versioning (SAM tools); working with services from AI/ML area; plus tips to optimise Lambda functions for performance and cost-effectiveness.
Productionize Serverless Application Building and Deployments with AWS SAM - ...Amazon Web Services
Learning Objectives:
- Learn abou the SAM template design best practices (e.g., use of globals, mappings, parameters, and conditionals)
- Learn how to test and debug serverless applications with SAM Local
- Learn how to customize SAM itself with the open source SAM implementation
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.
Voxxed Athens 2018 - Serverless by DesignVoxxed Athens
This document discusses serverless application design principles. It recommends separating business logic from event handlers using an adapter pattern and designing applications to be event-driven using event sourcing. It also recommends managing infrastructure as code using AWS Serverless Application Model (SAM) and AWS CloudFormation for safe deployments with canary/linear deployments, alarms, and hooks. Additionally, it suggests building CI/CD pipelines to speed up the feedback cycle.
Serverless Architectural Patterns and Best Practices - Madhu Shekar - AWSCodeOps Technologies LLP
This presentation was made by Madhusudan Shekar (Principal Evangelist) at AWS - on 9th June 2018 in Bridgei2i Analytics, Bangalore as part of Cloud Native meetup.
AWS August Webinar Series - Building Serverless Backends with AWS Lambda and ...Amazon Web Services
AWS Lambda is a compute service that runs your code in response to triggers and automatically manages the compute resources for you. 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 webinar 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 DynamoDB.
Learning Objectives:
Understand key AWS Lambda and Amazon API Gateway features
Learn how to set up a serverless backend using Amazon API Gateway and AWS Lambda
Explore sample use cases, best practices and tips on using AWS Lambda with Amazon API Gateway
Serverless architecture with AWS Lambda (June 2016)Julien SIMON
The document discusses serverless architecture using AWS Lambda. It describes how AWS Lambda allows developers to deploy code without provisioning or managing servers. Lambda runs code in response to events and automatically scales with traffic. The document provides examples of building serverless applications and data pipelines using Lambda along with other AWS services like API Gateway, DynamoDB, Kinesis and S3. It emphasizes that serverless applications on AWS can be built with no servers to manage and scale to any level of traffic.
AWS Serverless Application Model (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. Learn best practices and tricks for using AWS SAM at scale, including how to make the most of its dynamic template capabilities, how to use advanced features, and how to debug serverless applications. Also explore the Approved open-source AWS SAM translator, and see how AWS SAM works under the hood.
AWS Lambda allows you to run your code on a Serverless infrastructure, while AWS takes care of all the heavy lifting of Provisioning and utilization, Availability and fault tolerance, Scaling and Operations and management. In this session, we will take few use cases, from common development scenarios, and show how we can use AWS Lambda to build smarter and better systems.
by Brent Rabowsky, Solutions Architect & Itzik Paz, Solutions Architect, AWS
As serverless architectures become more popular, customers need a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems. This session describes re-usable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. The patterns use services like AWS Lambda, Amazon API Gateway, Amazon Kinesis Streams, Amazon Kinesis Analytics, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility. What’s new in 2017: using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; how a query can be achieved using Athena; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; how to validate API parameters in API Gateway to protect your API back-ends; and a solid focus on CI/CD development pipelines for serverless –that includes testing, deploying, and versioning (SAM tools).
Getting Started with Serverless Computing Using AWS Lambda - ENT332 - re:Inve...Amazon Web Services
With serverless computing, you can build and run applications without the need for provisioning or managing servers. Serverless computing means that you can build web, mobile, and IoT backends, run stream processing or big data workloads, run chatbots, and more. In this session, learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We introduce you to the basics of building with Lambda. As part of that, we show how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.
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.
As presented at the May 24 2018 Boston Serverless Meetup: https://www.meetup.com/Serverless-Boston/events/249744701/
AWS Serverless Application Models (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. We’ll get deep in to best practices and tricks for using SAM at scale, including how to make the most of the dynamic template capabilities of SAM, how to use advanced features such as deployment preferences and policy templates, and how to debug serverless applications with SAM Local. We’ll also explore the newly released open source SAM translator and explain how SAM works beneath the hood.
Presentation from the developer track at I Love APIs London 2016 featuring Matt McClean, Amazon Web Services.
Developers have been jumping on the microservices bandwagon because of the obvious benefits of faster release cycles and innovation. However, microservices' downside is the increased server costs, operational costs, and performance costs. To reduce this complexity, Amazon Web Services created AWS Lambda - a compute platform that lets you build microservices with no provisioning and servers.
Matt McClean, Solution Architect from AWS, presents how to use AWS Lambda to build your microservices. He covers various architectural patterns and anti-patterns for using AWS Lambda.
Best Practices for CI/CD with AWS Lambda and Amazon API Gateway (SRV355-R1) -...Amazon Web Services
Building and deploying serverless applications introduces new challenges for developers whose development workflows are optimized for traditional VM-based applications. In this session, we discuss a method for automating the deployment of serverless applications running on AWS Lambda. First, we cover how you can model and express serverless applications using the open source AWS Serverless Application Model (AWS SAM). Then, we discuss how you can use CI/CD tooling from AWS CodePipeline and AWS CodeBuild, and how to bootstrap the entire toolset using AWS CodeStar. We also cover best practices to embed in your deployment workflow specific to serverless applications.
AWS Lambda Powertools is an open-source library to help organizations discover and incorporate serverless best practices early and quickly. In two years, Powertools went from a tiny pilot program to a fast-growing project. This rapid growth led to challenges ranging from balancing new features with operational excellence, triaging bug reports and RFCs, and scaling and redesigning documentation, to lowering the bar for contribution and providing a public road map. In this session, learn about the current state of Lambda Powertools, how this growth was supported, key lessons learned in the past two years, and what’s next on the horizon.
AWS Lambda Powertools is a developer toolkit to implement Serverless best practices and increase developer velocity. It started as an open-source project in 2020 focused in making Tracing, Logging, and Metrics easier. Fast-forward, Powertools added 13 more features, grew a vibrant community who regularly contributes up to 60% of our releases, now covering a plethora of use cases: REST and GraphQL APIs, Batch processing, Idempotency, Feature Flags, Data Validation, and more.
You’ll learn why this developer toolkit was created, key use cases, and find out how you can adopt common industry and AWS best practices in seconds. We’ll also cover two of the most anticipated new features coming in 2023, and live demo(s).
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The document discusses securing serverless applications. It provides an overview of AWS Identity and Access Management (IAM), AWS Lambda, Amazon API Gateway, and Amazon Cognito. It then covers securing serverless microservices by discussing securing AWS Lambda functions using IAM roles and resource policies. It also covers securing Amazon API Gateway by discussing authorization types including Cognito, IAM, and custom authorizers. The document concludes by discussing auditing serverless applications using CloudWatch logs, CloudTrail, and AWS Config.
This document discusses serverless development using AWS Lambda. It provides an overview of common use cases for serverless applications like web apps, data processing, chatbots, backends, and IT automation. It also describes Lambda's event-driven execution model and the various services that can trigger Lambda functions. The document outlines the benefits of serverless such as fine-grained pricing where customers pay for compute time used. It also introduces the AWS Serverless Application Model (SAM) which provides a simplified way to define Lambda functions, APIs, and other resources in a CloudFormation template.
Build and Deploy Serverless Applications with AWS SAM - SRV316 - Chicago AWS ...Amazon Web Services
AWS Serverless Application Model (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. Learn best practices and tricks for using AWS SAM at scale, including how to make the most of its dynamic template capabilities, how to use advanced features, and how to debug serverless applications. Also explore the new open-source AWS SAM translator, and see how AWS SAM works under the hood.
SRV301-Optimizing Serverless Application Data Tiers with Amazon DynamoDBAmazon Web Services
"As a fully managed database service, Amazon DynamoDB is a natural fit for serverless architectures. In this session, we dive deep into why and how to use DynamoDB in serverless applications, followed by a real-world use case from CapitalOne.
First, we dive into the relevant DynamoDB features, and how you can use it effectively with AWS Lambda in solutions ranging from web applications to real-time data processing. We show how some of the new features in DynamoDB, such as Auto Scaling and Time to Live (TTL), are particularly useful in serverless architectures, and distill the best practices to help you create effective serverless applications. In the second part, we talk about how CapitalOne migrated billions of transactions to a completely serverless architecture and built a scalable, resilient and fast transaction platform by leveraging DynamoDB, AWS Lambda and other services within the serverless ecosystem."
¿Qué es eso del desarrollo sin servidores? ¿Qué lenguajes puedo utilizar? ¿Cómo hago cosas como autenticación, o guardar en base de datos, o enviar notificaciones? ¿Esto escala? A todas estas preguntas, y a alguna más, intentaré dar respuesta en esta sesión, donde haré una pequeña demo de montar una app muy sencilla y desplegarla en la nube sin preocuparnos de gestionar infraestructura. Charla realizada por primera vez para AlcarriaConf 2021
Serverless Architecture - Design Patterns and Best PracticesAmazon Web Services
As serverless architectures become more popular, customers are looking for a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems.
This webinar session describes reusable serverless patterns. For each pattern, operational and security best practices with potential pitfalls and nuances will be described. The patterns involve services including but not limited to AWS Lambda, Amazon API Gateway, Amazon Kinesis Data Streams and Data Firehose, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena.
This session can help audience recognise candidates for various serverless architectures in an organisation and understand areas of potential savings and increased agility. For example, using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; CI/CD development pipelines for serverless, which includes testing, deploying, and versioning (SAM tools); working with services from AI/ML area; plus tips to optimise Lambda functions for performance and cost-effectiveness.
Productionize Serverless Application Building and Deployments with AWS SAM - ...Amazon Web Services
Learning Objectives:
- Learn abou the SAM template design best practices (e.g., use of globals, mappings, parameters, and conditionals)
- Learn how to test and debug serverless applications with SAM Local
- Learn how to customize SAM itself with the open source SAM implementation
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.
Voxxed Athens 2018 - Serverless by DesignVoxxed Athens
This document discusses serverless application design principles. It recommends separating business logic from event handlers using an adapter pattern and designing applications to be event-driven using event sourcing. It also recommends managing infrastructure as code using AWS Serverless Application Model (SAM) and AWS CloudFormation for safe deployments with canary/linear deployments, alarms, and hooks. Additionally, it suggests building CI/CD pipelines to speed up the feedback cycle.
Serverless Architectural Patterns and Best Practices - Madhu Shekar - AWSCodeOps Technologies LLP
This presentation was made by Madhusudan Shekar (Principal Evangelist) at AWS - on 9th June 2018 in Bridgei2i Analytics, Bangalore as part of Cloud Native meetup.
AWS August Webinar Series - Building Serverless Backends with AWS Lambda and ...Amazon Web Services
AWS Lambda is a compute service that runs your code in response to triggers and automatically manages the compute resources for you. 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 webinar 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 DynamoDB.
Learning Objectives:
Understand key AWS Lambda and Amazon API Gateway features
Learn how to set up a serverless backend using Amazon API Gateway and AWS Lambda
Explore sample use cases, best practices and tips on using AWS Lambda with Amazon API Gateway
Serverless architecture with AWS Lambda (June 2016)Julien SIMON
The document discusses serverless architecture using AWS Lambda. It describes how AWS Lambda allows developers to deploy code without provisioning or managing servers. Lambda runs code in response to events and automatically scales with traffic. The document provides examples of building serverless applications and data pipelines using Lambda along with other AWS services like API Gateway, DynamoDB, Kinesis and S3. It emphasizes that serverless applications on AWS can be built with no servers to manage and scale to any level of traffic.
AWS Serverless Application Model (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. Learn best practices and tricks for using AWS SAM at scale, including how to make the most of its dynamic template capabilities, how to use advanced features, and how to debug serverless applications. Also explore the Approved open-source AWS SAM translator, and see how AWS SAM works under the hood.
AWS Lambda allows you to run your code on a Serverless infrastructure, while AWS takes care of all the heavy lifting of Provisioning and utilization, Availability and fault tolerance, Scaling and Operations and management. In this session, we will take few use cases, from common development scenarios, and show how we can use AWS Lambda to build smarter and better systems.
by Brent Rabowsky, Solutions Architect & Itzik Paz, Solutions Architect, AWS
As serverless architectures become more popular, customers need a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems. This session describes re-usable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. The patterns use services like AWS Lambda, Amazon API Gateway, Amazon Kinesis Streams, Amazon Kinesis Analytics, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility. What’s new in 2017: using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; how a query can be achieved using Athena; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; how to validate API parameters in API Gateway to protect your API back-ends; and a solid focus on CI/CD development pipelines for serverless –that includes testing, deploying, and versioning (SAM tools).
Getting Started with Serverless Computing Using AWS Lambda - ENT332 - re:Inve...Amazon Web Services
With serverless computing, you can build and run applications without the need for provisioning or managing servers. Serverless computing means that you can build web, mobile, and IoT backends, run stream processing or big data workloads, run chatbots, and more. In this session, learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We introduce you to the basics of building with Lambda. As part of that, we show how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.
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.
As presented at the May 24 2018 Boston Serverless Meetup: https://www.meetup.com/Serverless-Boston/events/249744701/
AWS Serverless Application Models (AWS SAM) is a tool for developing, deploying, and managing your serverless applications on AWS. We’ll get deep in to best practices and tricks for using SAM at scale, including how to make the most of the dynamic template capabilities of SAM, how to use advanced features such as deployment preferences and policy templates, and how to debug serverless applications with SAM Local. We’ll also explore the newly released open source SAM translator and explain how SAM works beneath the hood.
Presentation from the developer track at I Love APIs London 2016 featuring Matt McClean, Amazon Web Services.
Developers have been jumping on the microservices bandwagon because of the obvious benefits of faster release cycles and innovation. However, microservices' downside is the increased server costs, operational costs, and performance costs. To reduce this complexity, Amazon Web Services created AWS Lambda - a compute platform that lets you build microservices with no provisioning and servers.
Matt McClean, Solution Architect from AWS, presents how to use AWS Lambda to build your microservices. He covers various architectural patterns and anti-patterns for using AWS Lambda.
Best Practices for CI/CD with AWS Lambda and Amazon API Gateway (SRV355-R1) -...Amazon Web Services
Building and deploying serverless applications introduces new challenges for developers whose development workflows are optimized for traditional VM-based applications. In this session, we discuss a method for automating the deployment of serverless applications running on AWS Lambda. First, we cover how you can model and express serverless applications using the open source AWS Serverless Application Model (AWS SAM). Then, we discuss how you can use CI/CD tooling from AWS CodePipeline and AWS CodeBuild, and how to bootstrap the entire toolset using AWS CodeStar. We also cover best practices to embed in your deployment workflow specific to serverless applications.
Similar to re:Invent ARC307 - Serverless architectural patterns and best practices.pdf (20)
AWS Lambda Powertools is an open-source library to help organizations discover and incorporate serverless best practices early and quickly. In two years, Powertools went from a tiny pilot program to a fast-growing project. This rapid growth led to challenges ranging from balancing new features with operational excellence, triaging bug reports and RFCs, and scaling and redesigning documentation, to lowering the bar for contribution and providing a public road map. In this session, learn about the current state of Lambda Powertools, how this growth was supported, key lessons learned in the past two years, and what’s next on the horizon.
AWS Lambda Powertools is a developer toolkit to implement Serverless best practices and increase developer velocity. It started as an open-source project in 2020 focused in making Tracing, Logging, and Metrics easier. Fast-forward, Powertools added 13 more features, grew a vibrant community who regularly contributes up to 60% of our releases, now covering a plethora of use cases: REST and GraphQL APIs, Batch processing, Idempotency, Feature Flags, Data Validation, and more.
You’ll learn why this developer toolkit was created, key use cases, and find out how you can adopt common industry and AWS best practices in seconds. We’ll also cover two of the most anticipated new features coming in 2023, and live demo(s).
AWS Community Day Ireland - Building roads and bridges in the last decade of ...Heitor Lessa
This document discusses the evolution of organizational structures and team topologies over time for software development teams utilizing microservices architectures. It covers early discoveries from 2015-2019 around topics like sizing microservices, standardization, and terminology for concepts like squads and tribes. It also outlines experiments from 2021-2023 with different types of teams including product teams, platform teams, and collaboration between teams. Key discoveries are discussed around balancing experimentation with other concerns like complexity, enablement, and governance.
AWS Community Day Ireland - Refactoring a serverless appHeitor Lessa
This talk covers the ongoing refactoring of a single service in the Serverless Airline sample project. It includes DynamoDB remodeling, ports & adapters to ease testing & evolve the architecture, cost optimization, and how we addressed new challenges with batching, least-privilege on DynamoDB, etc.
This document discusses AWS Lambda Powertools, a Python library that simplifies implementing serverless best practices for structured logging, distributed tracing, and metrics collection. It provides utilities and pre-built solutions for collecting and managing logs, traces, and metrics that help build observability into serverless applications. The document outlines how AWS Lambda Powertools can help standardize logs, automatically collect traces across functions and services, and publish metrics to CloudWatch, making it easier to monitor and troubleshoot serverless applications.
Serverless days Stockholm - How to build a full-stack airline ticketing web appHeitor Lessa
As serverless computing grows in popularity, finding how to start can be a challenge. In this talk, we picked a sample “airline ticketing" web app to demonstrate the process of building a full stack serverless application. We’ll share tips and tricks for building your idea, creating a prototype and deploying quickly and safely in production. You’ll also learn how Vue.js applications can integrate with AWS AppSync (for GraphQL backends), Amazon API Gateway (for REST APIs), AWS Lambda functions, Amazon DynamoDB tables, Amazon Cognito (for user management), AWS Step Functions for implementing Booking using Saga pattern, using AWS Amplify to seamlessly provision and manage your cloud backend.
ArmadaJS - how to build a full-stack airline ticketing web appHeitor Lessa
As serverless computing grows in popularity, finding how to start can be a challenge. In this talk, we picked a sample “airline ticketing" web app to demonstrate the process of building a full stack serverless application. We’ll share tips and tricks for building your idea, creating a prototype and deploying quickly and safely in production. You’ll also learn how Vue.js applications can integrate with AWS AppSync (for GraphQL backends), Amazon API Gateway (for REST APIs), AWS Lambda functions, Amazon DynamoDB tables, Amazon Cognito (for user management), AWS Step Functions for implementing Booking using Saga pattern, using AWS Amplify to seamlessly provision and manage your cloud backend.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
23. Pattern: The “cherry-pick” (GraphQL API)
AWS AppSync
Client
Best practices
Use Lambda for complex logic
Resolvers
listFlights
Data sources
flightsDB
Query
Amazon DynamoDB
getLoyalty loyaltyFn Amazon DynamoDB
Apache Velocity
template
getLoyalty(customer: 1234) { tier, totalPoints }
Fetch loyalty points
24. Pattern: The “cherry-pick” (GraphQL API)
AWS AppSync
Client
Best practices
Use Lambda for complex logic
Use state machines for long
transactions. Pipeline resolvers for
simpler transactions
Resolvers
listFlights
Data sources
flightsDB
Query
Amazon DynamoDB
Apache Velocity
template
getLoyalty loyaltyFn Amazon DynamoDB
Mutation
initBooking procBooking AWS Step
Functions
Create new booking
initBooking(cust: 123..) { bookingId, bookingRef }
25. Pattern: The “cherry-pick” (GraphQL API)
AWS AppSync
Client
Best practices
Use Lambda for complex logic
Use state machines for long
transactions. Pipeline resolvers for
simpler transactions
Enforce authorization at API, data
field and operation level
Resolvers
listFlights
Data sources
flightsDB
Query
Amazon DynamoDB
Apache Velocity
template
getLoyalty loyaltyFn Amazon DynamoDB
Mutation
initBooking procBooking AWS Step
Functions
Amazon Cognito
createFlights(flightNumber: 1234, ticketPrice: 300)
Admin only
26. Pattern: The “cherry-pick” (GraphQL API)
AWS AppSync
Client
Best practices
Use Lambda for complex logic
Use state machines for long
transactions. Pipeline resolvers for
simpler transactions
Enforce authorization at API, data
field and operation level
Use purpose-built databases
Resolvers
listFlights
Data sources
flightsDB
Query
Amazon DynamoDB
Apache Velocity
template
getLoyalty loyaltyFn Amazon DynamoDB
Mutation
initBooking procBooking AWS Step
Functions
Amazon Cognito
Fetching orders
getOrder(id: 1234) { customer, flights, points… }
ordersDB
addOrder Amazon RDS
AWS Secrets
Manager
27. Pattern: The “cherry-pick” (GraphQL API)
AWS AppSync
Client
Resolvers
listFlights
Data sources
flightsDB
Query
Amazon DynamoDB
Apache Velocity
template
Amazon Cognito
getLoyalty loyaltyFn Amazon DynamoDB
ordersDB
addOrder Amazon RDS
AWS Secrets
Manager
Mutation
initBooking procBooking AWS Step
Functions
Fetch booking
listBookings { bookingRef, departureDate… }
Best practices
Use Lambda for complex logic
Use state machines for long
transactions. Pipeline resolvers for
simpler transactions
Enforce authorization at API, data
field and operation level
Use purpose-built databases
Select only data you need
Enable caching
31. Pattern: Call me, “Maybe” (Webhook)
Amazon API Gateway
Client
AWS Lambda
Best practices
Limit concurrency to protect non-
scalable/stateful downstream
services
Amazon RDS
Concurrency 5
32. Pattern: Call me, “Maybe” (Webhook)
Amazon API Gateway
Client
AWS Lambda
Best practices
Limit concurrency to protect non-
scalable/stateful downstream
services
Kinesis as a buffer + a better
mechanism to limit concurrency
Use Lambda Destinations for failed
requests; set max retries
Amazon RDS
Amazon Kinesis
Data Streams
DLQ
33. Pattern: Call me, “Maybe” (Webhook)
Amazon API Gateway
Client
AWS Lambda
Best practices
Limit concurrency to protect non-
scalable/stateful downstream
services
Kinesis as a buffer + a better
mechanism to limit concurrency
Use Lambda Destinations for failed
requests; set max retries
Enforce authorization and obfuscate
sensitive data on the stream
Amazon RDS
Amazon Kinesis
Data Streams
Custom
authorizer
Obfuscate DLQ
34. Pattern: Call me, “Maybe” (Webhook)
Amazon API Gateway
Client
AWS Lambda
Best practices
Limit concurrency to protect non-
scalable/stateful downstream
services
Kinesis as a buffer + a better
mechanism to limit concurrency
Use Lambda Destinations for failed
requests; set max retries
Enforce authorization and obfuscate
sensitive data on the stream
For low-volume traffic, Kinesis can
batch records for up to 5 minutes
Amazon RDS
Amazon Kinesis
Data Streams
Custom
authorizer
Obfuscate DLQ
35. Pattern: Call me, “Maybe” (Webhook)
Amazon API Gateway
Client
AWS Lambda
Best practices
Limit concurrency to protect non-
scalable/stateful downstream
services
Kinesis as a buffer + a better
mechanism to limit concurrency
Use Lambda Destinations for failed
requests; set max retries
Enforce authorization and obfuscate
sensitive data on the stream
For low-volume traffic, Kinesis can
batch records for up to 5 minutes
Alternatively, DynamoDB+SQS to
easily scale webhooks
Amazon RDS
Amazon Kinesis
Data Streams
Custom
authorizer
Obfuscate DLQ
Client
Amazon API Gateway Amazon SQS AWS Lambda
DLQ
Amazon DynamoDB
37. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
AWS Lambda Amazon Simple
Notification Service
Lambda Amazon SQS
Consumer
Lambda
38. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
Lambda Amazon SQS
Consumer
Lambda
Best practices
API Gateway can integrate with AWS
services directly
39. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
Consumer
Amazon SQS
Consumer
DLQ
DLQ
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
40. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
Consumer
Amazon SQS
Consumer
DLQ
DLQ
Custom
authorizer
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
Enforce authorization. Verify
signature of Amazon SNS messages
41. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
DLQ
Custom
authorizer
Consumer
Amazon SQS
Consumer
Amazon SQS
Consumer
Amazon SQS
Multiple consumers w/ DLQ
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
Enforce authorization. Verify
signature of Amazon SNS messages
42. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
DLQ
Custom
authorizer
Consumer
Amazon SQS
Consumer
Amazon SQS
Consumer
Amazon SQS
Multiple consumers w/ DLQ
Status=Created
Status=Processed
Status=Refunded
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
Enforce authorization. Verify
signature of Amazon SNS messages
Use message filtering for efficient
processing
43. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
DLQ
Custom
authorizer
Consumer
Amazon SQS
Consumer
Amazon SQS
Consumer
Amazon SQS
Multiple consumers w/ DLQ
Status=Created
Status=Processed
Status=Refunded
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
Enforce authorization. Verify
signature of Amazon SNS messages
Use message filtering for efficient
processing
Compress and aggregate messages
when possible
44. Pattern: The big “Fan” (fan-out)
Amazon API
Gateway
Client
Amazon Simple
Notification Service
Best practices
API Gateway can integrate with AWS
services directly
Integrate with Amazon SQS for
higher durability, batching, and DLQ
Enforce authorization. Verify
signature of Amazon SNS messages
Use message filtering for efficient
processing
Compress and aggregate messages
when possible
Consider Kinesis for larger payloads
DLQ
Custom
authorizer
Consumer
Amazon SQS
Consumer
Amazon SQS
Consumer
Amazon SQS
Multiple consumers w/ DLQ
Status=Created
Status=Processed
Status=Refunded
Amazon API
Gateway
Client
Amazon Kinesis
Data Streams
Consumer
47. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
Client
AWS Lambda Amazon Kinesis
Data Firehose
Amazon S3
48. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
Client
AWS Lambda Amazon Kinesis
Data Firehose
Amazon S3
Best practices
Enable source stream record backup
Backup
49. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
Client
AWS Lambda
Best practices
Enable source stream record backup
Favor dedicated Data Firehose per
context/domain
S3 bucket
Kinesis Data
Firehose
S3 bucket
S3 bucket
Kinesis Data
Firehose
Kinesis Data
Firehose
Backup
50. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
Client
AWS Lambda
Best practices
Enable source stream record backup
Favor dedicated Data Firehose per
context/domain
Enforce authorization
Obfuscate/remove sensitive stream
data
S3 bucket
Kinesis Data
Firehose
S3 bucket
S3 bucket
Kinesis Data
Firehose
Kinesis Data
Firehose
Custom
authorizer
Backup
Obfuscate
51. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
Client
AWS Lambda
Best practices
Enable source stream record backup
Favor dedicated Data Firehose per
context/domain
Enforce authorization
Obfuscate/remove sensitive stream
data
Enable Parquet transformation. Use
Glue to discover data schema and
Athena to query
Kinesis Data
Firehose
Kinesis Data
Firehose
Kinesis Data
Firehose
Custom
authorizer
Backup
Obfuscate
S3 bucket AWS Glue crawler
Amazon Athena Data Catalog
S3 bucket AWS Glue crawler
S3 bucket AWS Glue crawler
52. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
AWS Lambda
Best practices
Enable source stream record backup
Favor dedicated Data Firehose per
context/domain
Enforce authorization
Obfuscate/remove sensitive stream
data
Enable Parquet transformation. Use
Glue to discover data schema and
Athena to query
Use message filtering to prevent
unwanted events. Tune
buffer/compression
Kinesis Data
Firehose
Kinesis Data
Firehose
Kinesis Data
Firehose
Custom
authorizer
Backup
Obfuscate
S3 bucket AWS Glue crawler
Amazon Athena Data Catalog
S3 bucket AWS Glue crawler
S3 bucket AWS Glue crawler
SNS topic
SNS topic
SNS topic
DLQ
53. Pattern: They say “I’m a Streamer” (streaming)
Amazon API
Gateway
AWS Lambda
Best practices
Enable source stream record backup
Favor dedicated Data Firehose per
context/domain
Enforce authorization
Obfuscate/remove sensitive stream
data
Enable Parquet transformation. Use
Glue to discover data schema and
Athena to query
Use message filtering to prevent
unwanted events. Tune
buffer/compression
Kinesis Data
Firehose
Kinesis Data
Firehose
Kinesis Data
Firehose
Custom
authorizer
Backup
Obfuscate
S3 bucket AWS Glue crawler
Amazon Athena Data Catalog
S3 bucket AWS Glue crawler
S3 bucket AWS Glue crawler
SNS topic
SNS topic
SNS topic
DLQ
CloudFront Lambda@Edge
Go Global
58. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
AWS Direct
Connect
AWS NLB
Targets
Private IP
Corporate
data center
Server Server Server
DB DB DB
59. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
AWS Direct
Connect
AWS NLB
Targets
Private IP
Corporate
data center
Server Server Server
DB DB DB
Amazon CloudWatch
Logs & metrics
AWS X-Ray
Best practices
Centralize logs, metrics, and
distributing tracing
60. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
AWS Direct
Connect
AWS NLB
Corporate
data center
Load Balancer
Server Server Server
DB DB DB
Best practices
Centralize logs, metrics, and
distributing tracing
Use a corporate Load balancer virtual
IP to send traffic to
Amazon CloudWatch
Logs & metrics
AWS X-Ray
Targets
Virtual IP
61. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
Targets
Virtual IP
Corporate
data center
Load Balancer
Server Server Server
DB DB DB
Best practices
Centralize logs, metrics, and
distributing tracing
Use a corporate Load balancer virtual
IP to send traffic to
Enforce authorization
Custom
authorizer
Amazon CloudWatch
Logs & metrics
AWS X-Ray
AWS Direct
Connect
AWS NLB
62. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
Targets
Virtual IP
Corporate
data center
Load Balancer
Server
DB
Best practices
Centralize logs, metrics, and
distributing tracing
Use a corporate Load balancer virtual
IP to send traffic to
Enforce authorization
Gradually shift functionalities to
newer compute/database platforms
Custom
authorizer
Amazon CloudWatch
Logs & metrics
AWS X-Ray
AWS Direct
Connect
AWS NLB
Amazon EC2
Amazon ECS
Amazon RDS
63. Pattern: The “Strangler”
Amazon API Gateway
Client
VPC
Targets
Virtual IP
Corporate
data center
Load Balancer
Server
DB
Best practices
Centralize logs, metrics, and
distributing tracing
Use a corporate Load balancer virtual
IP to send traffic to
Enforce authorization
Gradually shift functionalities to
newer compute/database platforms
Use serverless for new functionalities
Custom
authorizer
Amazon CloudWatch
Logs & metrics
AWS X-Ray
AWS Direct
Connect
AWS NLB
Amazon EC2
Amazon ECS
Amazon RDS
Amazon DynamoDB
AWS Lambda
64. Practical example: HSBC Part 1
EU-West-1-A EU-West-1-B EU-West-1-C
Platform VPC
Bank bound VPC
Endpoint
VPC subnet
1 X
…
VPC subnet
1 X
…
VPC subnet
1 X
…
Large CIDR block
Bank Bound
Proxy Fleet
EU-West-1-A
Bank Bound
Proxy Fleet
EU-West-1-B EU-West-1-C
Bank Bound
Proxy Fleet
Platform DX VPC
Endpoint service
Network
Load
Balancer
Small CIDR block
HSBC UK
Direct
Connect
• As VPC attached Lambda function scales, subnets must have available IP addresses to
match the number of ENIs = large CIDR block required to your VPC
• Access to on-premise provided via VPC endpoint which encapsulates a set of proxy servers
located on a VPC with Direct Connect = small CIDR used on VPC connected to on-premise
65. Practical example: HSBC Part 2
HSBC UK
Mainframes
Mapper
EMR
Spark
Kinesis
Streams
Direct
Connect
Customer Preferences
DynamoDB Lambda API Gateway
Data Service
Aurora
EMR
DynamoDB
API Gateway
Kinesis
Streams
Event Engine
Kinesis
Streams
Lambda
Push Notifications
Notification Service
API Gateway
Kinesis
Streams
Lambda
Message Service
API Gateway
DynamoDB
Kinesis
Streams
Lambda
JSON
ASCII
Dead Letter Queues
SNS
SQS
VPC CloudWatch KMS
Common Services
EU-West-1
AVRO
EBCDIC
Kafka
AVRO
EBCDIC
69. Related breakouts
SVS311 Serverless at scale: design patterns and optimizations
SVS401-R Optimizing your serverless applications
SVS403-R Best practices for AWS Lambda and Java
API304 Scalable serverless event-driven applications using Amazon SQS
and Lambda
SVS309 Architecting and operating resilient serverless systems at scale