AWS Summit Auckland - Smaller is Better - Microservices on AWS

To find out more about training on AWS, visit: www.globalknowledge.co.uk/aws AWS Pop-up Loft | London, April 28, 2016

AWS Lambda enables developers to build scalable applications without managing servers. Come learn how Lambda's event driven approach helps build backend ingestion systems, real time stream processing, and scalable API backends. We will deep dive into the different approaches that customers have taken to building applications with Lambda, typical architectures that customers use Lambda for, and best practices for authoring, deploying, and managing Lambda functions. Speaker: Ajay Nair, Sr Product Manager Lambda, Amazon Web Services

In this session, you will learn how to deploy complex Windows workloads and ways AWS CloudFormation, AWS OpsWorks, and AWS CodeDeploy enable you to automate your Windows application life-cycle management. We will also discuss the monitoring, logging, and automatically scaling of Windows applications. Learn More: https://aws.amazon.com/government-education/

Scalable applications are by nature resource intensive, expensive to build and difficult to manage. What if we can change this perception and help developers design full-stack applications that are low cost and low maintenance? This session describes the underlying architecture behind www.deep.mg, the microservices marketplace built by Mitoc Group using AngularJS, NodeJS and powered by abstracted services like AWS Lambda, Amazon CloudFront, Amazon DynamoDB, and so on. Eugene Istrati, Technology Partner at Mitoc Group, will dive deep into their approach to microservices architecture using serverless platform from AWS and demonstrate how anyone can use serverless computing to achieve high scalability, high availability, and high performance without huge efforts or expensive resources allocation.

The document provides an overview of a workshop on building serverless microservices using AWS Lambda. The workshop will introduce AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon Cognito. Attendees will work in teams to build a secure, scalable chat service for zombie apocalypse survivors using these AWS serverless technologies. The workshop includes breakout sessions where attendees will add features like typing indicators, SMS integration with Twilio, messaging search with Elasticsearch, integration with Slack, and zombie sensor data integration with Intel Edison.

How do you do continuous delivery when using Docker and Amazon ECS? In this session, we’ll explore basic continuous integration and delivery concepts and how they can be applied to Docker and Amazon ECS. We will discuss how you can use AWS CodePipeline to monitor a GitHub repository for new commits, AWS CodeBuild to create a new Docker container image and to push it into Amazon ECR, and AWS CloudFormation to deploy the new container image to production on Amazon ECS. We will end with a demo of this entire toolchain.

When it comes to managing the security of your AWS environment, traditional, on-premise, perimeter-only tactics must evolve to be environment-aware, data-centric, and automated wherever possible. Speed of detection and agility in recovery are your new challenges and AWS Config, Cloudwatch, and Lambda are your new allies that help address them. Learn about high-speed security incident response and recovery at the push of a button perhaps. This talk provides an overview with detailed examples of configuration management, event notification, and automatic execution to rapidly detect and react to potential security concerns within your AWS environment. Speaker: Don Bailey, Principal Security Engineer, Amazon Web Services & Joshua Du Lac, Senior Security Consultant, Amazon Web Services

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.

Learning Objectives: - Securing network access to Amazon EC2 Instances with Security Groups, Launch and configure a Windows virtual machine - Bootstrapping using Powershell - Creating Key Pairs for authentication AWS helps you build, deploy, scale, and manage Microsoft applications quickly, easily, more securely, and more cost-effectively. This Hands on Lab workshop will give you everything you need to get started deploying Windows Workloads on AWS, starting with creating and securing a new EC2 Windows instance.

Large Web Applications are by nature resource intensive, expensive to customize, and difficult to manage at scale. What if we can change this perception and help developers architect a web application that is high performance and low cost, high security and low maintenance? This talk will focus on 3 key topics: 1) serverless infrastructure, 2) microservices architecture and 3) hands-on demos. We will describe a serverless solution and propose a scalable architecture that will help Generator Hub community to adopt cloud-native approach without huge efforts or expensive resources allocation.

In this session, we will help you use existing and recently launched services to automate configuration governance so that security is embedded in the development process. We outline four easy steps (Control, Monitor, Fix, and Audit) and demonstrate how different services can be used to meet your governance needs.

In this session, you’ll hear from GitHub and Accenture Federal Services, a trusted advisor to the US government, on why they have continued to invest in the adoption of and transition to cloud services. After migrating to AWS cloud, one agency deployed GitHub, the cloud-hosted, distributed version control and collaboration platform, as the backbone of its DevOps program. Now, thousands of users on software development teams at the agency collaborate both internally and with other agencies faster and more efficiently than ever before. Learn how they decreased duplicative work, raised the quality of their code, and greatly increased delivery velocity. Our Accenture Federal Services speaker will share details on what it’s like to run GitHub Enterprise on AWS for a federal agency, including the unique challenges and solutions that stem from running an appliance in the cloud, and advice for others considering this path. Session sponsored by GitHub. AWS Competency Partner

Amazon WorkSpaces is a desktop computing service that runs in the cloud, and now offers GPU configurations to support design and engineering applications and three-dimensional modeling. We show you how running these applications on Amazon WorkSpaces graphics bundles, in close proximity to data you already store on AWS, can help you process and visualize the results you need. We discuss the economics of running Amazon WorkSpaces graphics bundles, and demonstrate the experience of running a graphics-intensive application on a GPU-enabled Amazon WorkSpace. We also invite Autodesk (or TRC or ESRi) to discuss how they are using Amazon WorkSpaces graphics bundles in their business.

Today’s cutting-edge companies have software release cycles measured in days instead of months. This agility is enabled by the DevOps practice of continuous delivery, which automates building, testing, and deploying all code changes. This automation helps you catch bugs sooner and accelerates developer productivity. In this session, we’ll share the processes that Amazon’s engineers use to practice DevOps and discuss how you can bring these processes to your company by using a new set of AWS tools (AWS CodePipeline and AWS CodeDeploy). These services were inspired by Amazon's own internal developer tools and DevOps culture.

This document provides an overview of Amazon EC2 and autoscaling. It discusses EC2 basics like instance lifecycle, types, and using Amazon Machine Images. It also covers bootstrapping EC2 instances using metadata and user data. Monitoring EC2 with CloudWatch and different types of autoscaling like vertical, horizontal, and using Auto Scaling groups are explained. Autoscaling helps ensure applications have the correct resources to handle varying load and reduces manual scaling efforts.

VMware Cloud on AWS brings VMware's enterprise class Software-Defined Data Center software to Amazon's public cloud. VMware is delivered as an on-demand, elastically scalable, and cloud-based and is a sold, operated and supported service for any application. Its software is optimized for next-generation, elastic, bare metal AWS infrastructure. This solution enables customers to use a common set of software and tools to manage both their AWS-based and on-premises vSphere resources consistently. Further virtual machines in this environment have seamless access to the broad range of AWS services. This session will introduce this new service and examine some of the use cases, benefits, and go-to market approaches of the service. We will also include an overview of the underlying AWS architecture, key enabling services, and the feature roadmap. Learn More: https://aws.amazon.com/government-education/

This document discusses serverless application lifecycle management (ALM) techniques. It provides an overview of common serverless use cases like web applications and data processing. It then outlines a serverless ALM checklist including configuration/management, deployment methods, and tracing/troubleshooting. Specific AWS services for packaging, deploying, automating deployment, and monitoring serverless applications like AWS Lambda, AWS Serverless Application Model (SAM), AWS CodePipeline, and AWS CloudWatch are also discussed. The document concludes with a call for feedback and further exploration of serverless ALM best practices.

Browser Support & Device Recommendations – 2015 4Q The latest Device and Browser Support updates, courtesy of MCD Partners. Browser support recommendations for desktop and mobile browsers are constantly changing and close attention should be paid to updates as the slightest change can significantly impact user experience. On a quarterly basis, MCD Partners tracks the use of stable releases of browsers, operating systems, and devices for the general U.S. population, identifying the current share of the user base and potential velocity for large-scale adoption of new and obsolesce of old platforms. The device and browser support recommendations outlined in this report are based on the general U.S. consumer market; with a couple of noted exceptions. An individual project’s browser support requirements should be identified based on measurement analytics for the target site and inform the design and development specifications throughout the project. Browser Support: The recommendation changes for this report include: Drop support for versions of IE prior to IE 11. Add full support of Firefox 42 and Firefox 43 to Win XP, Win 7, Win 8.1, Mac 10.10 and Mac 10.11. Drop support for versions of Firefox prior to version 42. Add full support of Chrome 46 and Chrome 47 to Win XP, Win 7, Win 8.1 Mac 10.10 and Mac 10.11. Drop support for versions of Chrome prior to version 46. Chrome 48 and Chrome 49 are not added since the stable versions were recently released. As of this report, support isn’t warranted but we expect full support by the end of the 1st quarter 2016 due to automatic upgrades. Device Support: The recommendation changes for this report include: Add full support of Samsung Galaxy S5 on Android v5.0 and Android v5.1. Please view the full Device and Browser Support Recommendations below. For future Browser Support updates please visit MCDPartners.com and submit your contact information.

This document discusses securing container-based applications. It covers container and OS security best practices like using Linux namespaces and cgroups for isolation, reducing the container attack surface, and hardening container images. It also discusses securing the container lifecycle through vulnerability scanning, configuration governance with Amazon ECS, and using secrets management. Finally, it shows how to automate security deployments through the CI/CD pipeline and tools like CloudFormation and CodeDeploy.

This document discusses AWS CodeDeploy, a service that automates software deployments to EC2 instances and on-premises servers. It provides an overview of CodeDeploy's key concepts including applications, deployment groups, deployment configurations, and hooks. It also shows examples of how CodeDeploy can be used for automated deployments across development, test, and production environments. The document suggests additional features like CloudFormation support and integration with CI/CD tools.

An ode to the underrepresented and underused pattern of events and asynchrony in the design and development of Microservices. Prepared by Saul Caganoff, and delivered by Saul at Melbourne Microservices, and by Yamen Sader at Sydney Microservices.

This document outlines Martin Cronjé's talk on establishing a craftsmanship culture in a team. The talk discusses how software development is becoming more like a craft, and the need to grow people through deliberate practice and learning by doing. It suggests creating space regularly for coding practice sessions, with a focus on collaboration, learning new techniques, and experimenting. Getting feedback and reflecting on what works and doesn't work is important to constantly improve and make the learning opportunities last.

This document discusses microservices and the motivations for adopting a microservices architecture. It begins by describing some of the issues that arise with traditional monolithic architectures over time, as new features and concerns are added. These include low cohesion between layers, high coupling between components, and changes requiring understanding too many parts of the system. The document then introduces the concept of microservices as an architecture where services are defined around business capabilities and organized vertically rather than horizontally. It discusses some of the challenges of developing and managing microservices at both the domain and infrastructure levels. Overall, the document provides an introduction to microservices and why decomposing monolithic applications into independently deployable microservices can help address many of the issues that arise for systems

In this presentation, we introduce AWS to Broadcast and OTT Workloads. References, customers, stories and details of Broadcast and OTT workloads implemented on the AWS Cloud. Originally presented at AWS Toronto - by Bhavik Vyas

The PanCancer Analysis of Whole Genomes (PCAWG) project is a large-scale, highly distributed research collaboration designed to identify common patterns of mutations across 2,800 cancer genomes. The use of public and private clouds were instrumental in analyzing this dataset using current best practice containerized pipelines. This session describes the technical infrastructure built for the project, how we leveraged cloud environments to perform the “core” analysis, and the lessons learned along the way.

Process your data immediately after ingest or upload without needing to manage or maintain infrastructure while achieving cost-optimized scaling that avoids idle compute. Come learn about how AWS Lambda can be used to process sensor data as it is produced in real-time.This session will feature two demos. The first will show how to use AWS Lambda to automatically process Landsat satellite imagery as it is produced. Development Seed will then introduce how they process geospatial OpenStreetMap data as it is created in real-time by contributors around the world. AWS Lambda provides a low-cost and efficient solution for Development Seed by scaling from little activity to thousands of commits per hour during sponsored "mapathons.”

This document discusses building a serverless data pipeline using AWS Lambda and other AWS managed services like DynamoDB, Kinesis Firehose and S3. It provides steps to create a DynamoDB table with streams enabled, a Lambda function to read from the DynamoDB streams and write to Kinesis Firehose, and a Kinesis Firehose delivery stream to deliver data to S3. With these serverless components, data can be ingested and processed without having to provision or manage any servers.

This session is recommended for anyone considering using the AWS cloud to augment their current capabilities. Adoption of cloud computing provides access to the benefits of new deployment models with significant cost and agility benefits. But how can the cloud benefit existing government organizations that have invested large amounts of resources in existing on-premises technologies? This session outlines several key factors to consider from the point of view of the large-scale IT shop stakeholder. Because each organization has its unique set of challenges in cloud adoption, this session compares some of the opportunities and risks of several hybrid cloud use-case models and then helps customers understand the cloud-native and third-party vendor options available that bridge the gap to the cloud for large-scale government environments. Speaker: Craig Roach, Solutions Architect, Amazon Web Services

Whether you’re planning a data center shut down or just need to move large volumes of archived data from your on-premises environment, attend this webinar and learn more about how AWS Snowmobile and AWS Snowball Edge can help you migrate your terabytes or petabytes of critical data in a fast, secure and cost effective way. Hear how customers are using these two new services to transform their business model and advance their IT strategy in a way that was not possible before from a time and cost perspective. Learning Objectives: • Learn about the capabilities, features, and benefits of AWS Snowball Edge and AWS Snowmobile • Learn key use cases for AWS Snowball Edge and AWS Snowmobile • Learn how AWS Snowball Edge is more than just a data transfer service • Be able to determine when to use which data transfer service from AWS

This document discusses using big data and machine learning techniques on AWS for content recommendations. It describes three common approaches: search with boosting which adjusts search rankings based on popularity signals; collaborative filtering which identifies similar users and items; and neural networks which use historical user events to create a model that predicts favorites. It also introduces Amazon DSSTNE (Deep Scalable Sparse Tensor Network Engine) for automating GPU-accelerated training and prediction at scale for recommendation systems.

The document discusses different customer journeys in using video services on AWS, including GoPro's use of Amazon Elastic Transcoder to process user generated content at scale and the BBC's use of Elemental Cloud to live stream the 2014 World Cup from multiple venues. It also provides an overview of AWS video transcoding and delivery services like Elastic Transcoder and Elemental Cloud that help customers manage media workflows and processing. Case studies highlight how these services provide scalability, integration with other AWS offerings, and the ability to optimize video for delivery across many devices.

This document discusses best practices for managing infrastructure on AWS using infrastructure as code. It covers choosing the right EC2 instances based on workload requirements and Intel processor technologies. It then discusses using infrastructure as code with AWS services like CloudFormation to define templates that provision AWS resources declaratively based on dependencies. The document outlines the infrastructure as code workflow and how AWS services help manage operating systems, applications, and infrastructure through code.

This document summarizes a presentation on real-time streaming data on AWS. It discusses Amazon Kinesis, Spark Streaming, AWS Lambda, and Amazon EMR. The presentation covers an overview of streaming vs batch processing, common streaming data use cases and design patterns, a deep dive on Amazon Kinesis, examples of ingesting and processing streaming data, and a case study of how Sizmek uses these services for their real-time analytics needs.

Deep learning is an implementation of machine learning that uses neural networks to solve difficult and complex problems, such as computer vision, natural language processing, and recommendations. Due to the availability of deep learning libraries and frameworks, developers have the ability to enhance the capabilities of their applications and projects. In this workshop, you learn how to build and deploy a powerful deep learning framework called MXNet on containers. The portability and resource management benefit of containers means developers can focus less on infrastructure and more on building. The labs start by demonstrating the automation capabilities of AWS CloudFormation to stand up core infrastructure; as an added bonus, you use Spot Fleet to leverage the cost benefits of using Spot Instances, especially for developer environments. Then, you walk through creating an MXNet container in Docker and deploying it with Amazon ECS. Finally, you walk through an image classification demo of MXNet to validate that everything is working as expected. All you need to participate is a laptop and AWS account.

Learn best practices for taking advantage of Amazon Redshift's columnar technology and parallel processing capabilities to improve your data warehouse performance.

Comcast's X1 Platform delivers a dramatically new entertainment experience to viewers. And not just to Comcast subscribers, but to several other major cable companies. This requires a massive integration layer between companies. A big part of that integration is delivering billions of data points per day to syndication partners. Find out how the X1 Platform uses Amazon Kinesis as a data bus, drastically simplifying data integration with others. As part of this, see how X1 uses Lambda, EMR Spark, and S3 - all leading to a near serverless big data backbone.

This document provides an overview of building mobile web applications using the AWS Mobile SDK. It discusses authentication and authorization, static asset hosting, notifications, API interactions, architecture considerations around scale, costs and security, and frontend tooling like React and Angular. It also describes using Amazon Cognito for user pools and identity management, API Gateway for routing, and hosting static content on S3 with API integration. The document focuses on serverless architectures using Lambda and providing analytics via Mobile Analytics. It emphasizes building reactive and high-performance mobile web apps on AWS.

Microservice oriented architectures have been implemented and deployed by many and are on the near-term agenda of many others. However, the distributed nature of microservices is a double edged sword, being the source of many of the benefits, but also the source of the pain and confusion that teams have endured. We will review best practices and recommended architectures for deploying microservices on AWS with a focus on how to exploit the benefits of microservices to decrease feature cycle times and costs while increasing reliability, scalability, and overall operational efficiency. Speaker: Craig Dickson, Solutions Architect, Amazon Web Services Featured Customer - MYOB

1) The document discusses best practices for running microservices at scale, including breaking monolithic architectures into loosely coupled microservices, using the right tools for each job, securing services, focusing on organizational transformation, and automating everything. 2) Five principles for running microservices are outlined: microservices only rely on each other's public APIs, using the right tool for the job, securing services with defense-in-depth, focusing on cross-functional teams for alignment, and automating everything. 3) Examples of event-driven serverless architectures using AWS Lambda and other AWS services are provided.

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.

The document discusses microservices and provides information on: - The benefits of microservices including faster time to market, lower deployment costs, and more revenue opportunities. - What defines a microservice such as being independently deployable and scalable. - Differences between monolithic and microservice architectures. - Moving applications to the cloud and refactoring monolithic applications into microservices. - Tools for building microservices including Azure Service Fabric and serverless/Functions. - Best practices for developing, deploying, and managing microservices.

The business case and ROI for MicroServices, DevOps / Agile, adopting CI/CD, and Kubernetes with best practices. (Draft 2)

Talk about how to improve the architecture and reduce the technical debt of your applications. By gradually separating away responsibilities from your monolithic apps into single responsibility services.

Docker concepts and microservices architecture are discussed. Key points include: - Microservices architecture involves breaking applications into small, independent services that communicate over well-defined APIs. Each service runs in its own process and communicates through lightweight mechanisms like REST/HTTP. - Docker allows packaging and running applications securely isolated in lightweight containers from their dependencies and libraries. Docker images are used to launch containers which appear as isolated Linux systems running on the host. - Common Docker commands demonstrated include pulling public images, running interactive containers, building custom images with Dockerfiles, and publishing images to Docker Hub registry.

The document discusses 3 key ways that developing software for the cloud differs from traditional approaches: 1. Incremental delivery, with frequent small releases of new features rather than large periodic releases. 2. Increased automation, including automated testing and continuous integration/deployment pipelines to support more agile development and deployment. 3. Analytics of usage data to inform product decisions and ensure features are valuable to users. Developing with the cloud in mind requires rethinking processes to focus on agility, automation and data-driven insights.

Microservices involve breaking up monolithic applications into smaller, independent services that work together. This allows for increased efficiency through scaling individual services as needed, easier updates by updating smaller code bases, and improved stability if one service fails. Containers are well-suited for microservices due to their lightweight nature and ability to easily move workloads.

This document provides guidance on building a minimum viable product (MVP) and scaling a startup using AWS services. It recommends starting with a simple MVP focused on the core idea with minimal features. Traditional hosting poses scaling challenges, so AWS is suggested for its ability to fail faster at lower cost through services like Elastic Beanstare and auto-scaling. The document outlines iterative steps to scale from MVP to supporting millions of users through refining the architecture, adding services like S3, CloudFront, databases, and analytics on EMR. Overall it emphasizes the Lean Startup approach of failing fast and adapting quickly using AWS capabilities.

Java Agile ALM: OTAP and DevOps in the Cloud Bas Van Oudenaarde job Technical Manager at VX Company.

When Cisco started envisioning the future of its application development platforms, the ability to create applications that are cloud-native with elastic services, network-aware application policies, and micro-services was strategic to the company. When the decision to build and operate a Cisco cloud service delivery platform for collaboration, video, and Internet of Things (IoT) application development was made, OpenStack and micro-services became central to our application architectures and strategic to our vision as a company. This presentation will look at the journey Cisco developers took to transform to an application-centric OpenStack platform for application development in a secure, network-centric, and completely open source manner. The importance of the platform being Red Hat Enterprise Linux OpenStack Platform and using OpenShift by Red Hat and the contribution to the community will be described. The micro-services architecture and service-oriented DevOps lessons learned for enabling massive scalable and continuous delivery of software will be presented and demoed.

This deck, presented at DevNexus 2017 in Atlanta, describes Chick-fil-A's approach to changing the way we deliver software to our enterprise by shifting to Cloud Native architectures, DevOps delivery models, and microservices. Contact Brian Chambers on LinkedIn at https://www.linkedin.com/in/brian-chambers-65960168/ if there are questions

For enterprises trying to stay ahead of the game, having a robust and fast application development program can make or break their market presence. The challenge for developers, however, is to build responsive, devise-agnostic applications in days, not months.