CI&amp;CD with AWS - AWS Prague User Group - May 2015

Continuous Integration and Deployment on Amazon Web Services - AWS Prague User Group Presentation - May 2015

Agenda
• The Age of DevOps
• AWS Offering for DevOps
• CodeCommit
• CodePipeline
• CodeDeploy
• Demos
• Q&A

Software is eating the world1
1 Wall Street Journal article by Marc Andreessen (2011)

Software distribution and development changes

DevOps Principles
Definition
Collaboration - work as one team end to
end
Breakdown the barriers between
developers and IT ops
Continuous integration & deployment
Treat Infrastructure as code
Support business and IT agility
Automate everything
Test everything
Measure & monitor everything

AWS Offering for CI & CD
MonitorProvisionDeployTestBuildCode
Elastic Beanstalk
OpsWorks
Cloud
Watch
Cloud
Formation
Code
Deploy
Code
Commit
(preview)
Code
Pipeline
(preview)

Coding Phase
Developer creates a code.
How and where to store it? How to get the following functionality?
• Tracking all changes
• Distributed to allow collaboration
• Branching and merging
• Option to switch across different versions
Version Control System

AWS CodeCommit
git push CodeCommit
Git objects
in Amazon S3
Git index
in Amazon
DynamoDB
Encryption key
in AWS KMS
SSH or Smart HTTP
• Data redundancy across Availability Zones
• Data-at-rest encryption
• Integrated with AWS Identity and Access Management
• No repo size limit
Secure, scalable and managed source control

Build and Test Phase
1. Developers deploy code to the version control system (CodeCommit, Git)
2. SysOps build and deploy the software to the testing / staging environment
3. Q&A team executes load and performance test so the software can be
released for production use

AWS CodePipeline
Continuous Delivery and Release Automation
• Customizable workflow engine
• Integrate with partner and custom systems
• Visual editor and status
Source Staging Region 2
Region 3
Build
Unit
Tests
Deploy
UI
Test
DeployDeploy
Region 1

Deployment Phase
Software has to be deployed to different environments (dev/test/staging/production)
Deployment has to be automated as much as possible to minimize downtime
In case of issues, it has to allow roll-back to the previous version

AWS CodeDeploy
• Automated application deployments to EC2,
and any Internet-connected computer
• Consistent and reliable releases, without downtime
• Scale from 1 instance to thousands
• Centralize deployment control and monitoring
Coordinate automated deployments, just like Amazon

How CodeDeploy Works
Agent Agent
Agent Agent
Agent
Agent
Deployment Group
Deployment
Amazon S3
GitHub
Application
Bundle
Coordinate automated deployments, just like Amazon

Deployment config – choose speed
v2 v1 v1 v1 v1 v1 v1 v1One at a time
v2 v2 v2 v2 v1 v1 v1 v1
v2 v2 v2 v2 v2 v2 v2 v2
Half-at-a-time
All-at-once

Rolling update – Deploy without downtime
Load Balancer
v1 v1 v1v1

Rolling update – Deploy without downtime
Load Balancer
v1 v1 v1v2

Rolling update – Deploy without downtime
Load Balancer
v1 v1v2 v2

Rolling update – Deploy without downtime
Load Balancer
v1 v2v2 v2

Health Tracking – Catch Deployment Problems
Load Balancer
v1 v2v2 v2

Health Tracking – Catch Deployment Problems
Load Balancer
v1 v2v3 v2Stop

Health Tracking – Catch Deployment Problems
Load Balancer
v1 v2v3 v2
Rollback

- Two companies faced challenges processing big data on-premises, including high fixed costs, slow deployment, lack of scalability, and outages impacting production. - Amazon Elastic MapReduce (EMR) provides a managed Hadoop service that allows companies to launch clusters within minutes in the AWS cloud at lower costs by using elastic and scalable infrastructure. - AOL moved their 2PB on-premises Hadoop cluster to EMR, reducing costs by 4x while gaining automatic scaling and high availability across availability zones. EMR addressed their challenges and allowed faster restatement of historical data.

Travel hackathon

This document discusses Amazon Web Services (AWS) global infrastructure and services. It describes AWS regions and availability zones, which are clusters of data centers isolated from failures in other zones. It provides an overview of AWS compute, network, storage, database, analytics, application, and developer services. Specific services covered include Amazon EC2, EBS, S3, RDS, DynamoDB, Elastic Beanstalk, Lambda, API Gateway, and the AWS CLI.

Architecting on The Cloud

Micrsoservices unleashed with containers and ECS

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AWS OpsWorks for Chef Automate provides a fully managed Chef server and suite of automation tools that give you workflow automation for continuous deployment, automated testing for compliance and security, and a user interface that gives you visibility into your nodes and their status. The Chef server gives you full stack automation by handling operational tasks such as software and operating system configurations, package installations, database setups, and more. The Chef server centrally stores your configuration tasks and provides them to each node in your compute environment at any scale, from a few nodes to thousands of nodes. OpsWorks for Chef Automate is completely compatible with tooling and cookbooks from the Chef community and automatically registers new nodes with your Chef server.

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AWS offers several EC2 purchasing options to optimize costs for different workload types. On-Demand is for short-term or unpredictable workloads, Reserved Instances provide significant discounts for steady workloads by reserving capacity long-term, and Spot Instances allow unused capacity to be purchased at steep discounts. Customers can optimize costs by right-sizing instances, increasing elasticity through automation, and continuously monitoring usage to identify optimization opportunities across purchasing options.

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AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. Learning Objectives: • Learn about the capabilities and features of AWS Batch • Learn about the benefits of AWS Batch • Learn about the different use cases • Learn how to get started using AWS Batch

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Amazon EC2 allows you to bid for and run spare EC2 capacity, known as Spot instances, in a dynamically priced market. On average, customers save 80% to 90% compared to On Demand prices by using Spot instances. Achieving these savings has historically required time and effort to find the best deals while managing compute capacity as supply and demand fluctuate. In this session, we dive into how customers who have designed scalable, cloud friendly application architectures can leverage new Spot features to realize immediate cost savings while maintaining availability. Attendees will leave with practical knowledge of how, via well architected applications, they can run production services on the Spot instances just like IFTTT and Mapbox.

Deep Dive on Elastic Load Balancing

Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances for fault tolerance and load distribution. In this session, we go into detail about Elastic Load Balancing's configuration and day-to-day management, as well as its use in conjunction with Auto Scaling. We explain how to make decisions about the service and share best practices and useful tips for success.

Introduction to AWS Batch

AWS Batch is a fully managed batch computing service that makes it easy to run batch computing workloads on AWS. It dynamically provisions compute resources and schedules jobs across EC2 instances. Users can define jobs, job queues, compute environments and have AWS Batch automatically manage the underlying infrastructure. The service is integrated with other AWS services and has no upfront costs, with users only paying for the resources used to run jobs.

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As software teams transition to cloud-based architectures and adopt more agile processes, the tools they need to support their development cycles will change. In this session, we'll take you through the transition that Amazon made to a service-oriented architecture over a decade ago. We will share the lessons we learned, the processes we adopted, and the tools we built to increase both our agility and reliability. We will also introduce you to AWS CodeCommit, AWS CodePipeline, and AWS CodeDeploy, three new services born out of Amazon's internal DevOps.

DevOps on AWS: DevOps Day San Francisco

DevOps Day at the San Francisco Loft: DevOps on AWS Software release cycles are now measured in days instead of months. Cutting edge companies are continuously delivering high-quality software at a fast pace. In this session, we will cover how you can begin your DevOps journey by sharing best practices and tools used by the engineering teams at Amazon. We will showcase how you can accelerate developer productivity by implementing continuous Integration and delivery workflows. We will also cover an introduction to AWS CodeStar, AWS CodeCommit, AWS CodeBuild, AWS CodePipeline, AWS CodeDeploy, AWS Cloud9, and AWS X-Ray the services inspired by Amazon's internal developer tools and DevOps practice. Level: 200 Speaker: Sam Hennessy - Solutions Architect, AWS

Developer Tools at AWS 2018.pdf

Software release cycles are now measured in days instead of months. Cutting edge companies are continuously delivering high-quality software at a fast pace. In this session, we will cover how you can begin your DevOps journey by sharing best practices and tools used by the engineering teams at Amazon. We will showcase how you can accelerate developer productivity by implementing continuous Integration and delivery workflows. We will also cover an introduction to AWS CodeStar, AWS CodeCommit, AWS CodeBuild, AWS CodePipeline, AWS CodeDeploy, AWS Cloud9, and AWS X-Ray the services inspired by Amazon's internal developer tools and DevOps practice.

DevOps on AWS - Building Systems to Deliver Faster

by Nick Brandaleone, Solutions Architect AWS Join us to learn about continuous integration, continuous delivery, and DevOps. The AWS Developer Tools have been designed based on the tools used by Amazon engineers to rapidly and reliably deliver products and features to customers. We’ll provide overviews of the services and best practices followed by a hands-on workshop to help you learn how to automate your software release processes, deploy application code, and monitor your application and infrastructure performance.

DevOps at Amazon: A Look at Our Tools and Processes

1) Amazon developed DevOps practices and tools to support microservices architectures and continuous delivery at scale for their own applications. They launched three new AWS services - CodeCommit, CodePipeline, and CodeDeploy - to provide similar capabilities to other organizations. 2) CodeCommit provides fully-managed Git source control in the cloud. CodePipeline allows users to model and visualize their release processes. CodeDeploy automates application deployments across different environments. 3) These services aim to help users achieve continuous delivery, deploy applications without downtime, and catch deployment problems through health tracking and rollbacks, as Amazon has done internally for their many services.

Introduction to DevOps and the AWS Code Services

DevOps combines cultural philosophies, practices, and tools to increase collaboration between development and operations teams. It aims to improve reliability, speed, and scale through practices like microservices, continuous integration and delivery, infrastructure as code, and monitoring. AWS provides services like CodeCommit, CodePipeline, CodeDeploy, CloudFormation, OpsWorks, Config, CloudWatch, and CloudTrail to help customers implement DevOps practices on AWS.

Continuous Integration and Deployment Best Practices on AWS

With AWS, organizations now have the ability to develop and run their applications with speed and flexibility like never before. Working with an infrastructure that can be 100% API-driven enables organizations to use lean methodologies and realize these benefits. In this session, we will explore some key concepts and design patterns for continuous deployment and continuous integration, two elements of lean application and infrastructure development. We will look at several use cases where IT organizations leveraged AWS to rapidly develop and iterate on applications for scale, high availability and cost optimization. Speaker: Adrian White, Solutions Architect, Amazon Web Services

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DevOps in Amazon.com

DevOps on AWS: DevOps Day San Francisco

Developer Tools at AWS 2018.pdf

DevOps on AWS - Building Systems to Deliver Faster

DevOps at Amazon: A Look at Our Tools and Processes

Introduction to DevOps and the AWS Code Services

Continuous Integration and Deployment Best Practices on AWS

More from Vladimir Simek

Machine Learning with Amazon SageMaker

The document discusses Amazon SageMaker, a fully managed machine learning service. It provides an overview of SageMaker's capabilities for preparing, building, training and deploying machine learning models. Key features highlighted include SageMaker Studio for an integrated development environment, Autopilot for automatic model creation, JumpStart for pre-built solutions, and Data Wrangler for preparing data. Use cases and demos are presented to illustrate how customers can use SageMaker's services and features to develop machine learning applications.

AWS CZSK Webinář 2020.03: AWS Outposts

Spoločnosti na celom svete presúvajú svoje aplikácie do cloudu tak rýchlo, ako sa len dá, aby sa stali flexibilnejšími a znížili náklady. Niektoré aplikácie však musia ostať v lokálnych dátacentrách, či už z dôvodu nízkej latencie alebo požiadaviek na miestne spracovanie údajov. Riešenie AWS Outposts prináša plne spravované cloudové služby a infraštruktúru do akéhokoľvek dátového centra. Rovnaké API rozhranie cez grafickú konzolu, príkazový riadok či SDK bez ohľadu na to, či je aplikácia v cloude alebo v AWS Outpost umožňuje naplno využiť model hybridného cloudu bez kompromisov. V tomto webinári vám predstavíme fungovanie AWS Outposts, rovnako ako prípady použitia v reálnej zákazníckej prevádzke.

AWS CZSK Webinar - Migrácia desktopov a aplikácií do AWS cloudu s Amazon Work...

V polovici januára 2020 skončila rozšírená podpora operačného systému Windows 10. Mnoho organizácií stojí pred rozhodnutí, či investovať do existujúcej infraštrukúry alebo radšej poskytnú svojim používateľom flexibilnejšie a modernejšie riešenie - dostupné odkiaľkoľvek a na akomkoľvek zariadení. Presun desktopov a aplikácií do AWS cloudu ponúka vylepšené zabezpečenie, škálovateľnosť, flexibilitu a vyšší výkon. V tomto webinári vám poskytneme prehľad služieb Amazon WorkSpaces a Amazon AppStream 2.0 a ukážeme vám, aké ľahké je začať ich používať.

News from re:Invent 2019

The document summarizes announcements from AWS re:Invent 2019, including new AWS services and capabilities: - AWS Outposts brings AWS infrastructure on-premises for applications requiring low latency; it offers EC2, EBS, and other services. - Local Zones place AWS compute and storage closer to end-users for applications requiring single-digit millisecond latencies. - Wavelength extends AWS to 5G networks by hosting infrastructure in communication service providers' networks, enabling very low latency applications over 5G.

Serverless on AWS: Architectural Patterns and Best Practices

When speaking about serverless on AWS, most people think about AWS Lambda. But there's more than than. AWS provides a set of fully managed services that you can use to build and run serverless applications. Serverless applications don’t require provisioning, maintaining, and administering servers for backend components such as compute, databases, storage, stream processing, message queuing, and more. You also no longer need to worry about ensuring application fault tolerance and availability. Instead, AWS handles all of these capabilities for you. This allows you to focus on product innovation while enjoying faster time-to-market.

AWS CZSK Webinar 2019.07: Databazy na AWS

Tak ako cloud znížil náklady na ukladanie a procesovanie dát a objavila sa nová generácia aplikácií, vznikli nové požiadavky na databázy. Tieto aplikácie potrebujú databázy na ukladanie tera- či petabajtov dát, nových typov údajov, odozvy v milisekundách, schopnosť spracovať milióny požiadaviek za sekundu od miliónov užívateľov kdekoľvek na svete. Na podporu takýchto požiadaviek potrebujete relačné aj nerelačné databázy, ktoré sú navrhnuté tak, aby vyhovovali špecifickým potrebám vašich aplikácií. Ak sa chcete dozvedieť viac, aké databázové systémy môžete použiť na AWS pre vaše aplikácie, pripojte sa k nášmu ďalšiemu AWS česko-slovenskému webináru. Budeme demonštrovať rôzne databázové riešenia na AWS, popíšeme prípady použitia, najlepšie postupy a ukážeme niekoľko ukážok. Premiéra: 09/07/2019

AWS CZSK Webinář 2019.05: Jak chránit vaše webové aplikace před DDoS útoky

Česko-Slovenský AWS Webinář 07 - Optimalizace nákladů v AWS

AWS Česko-Slovenský Webinár 03: Vývoj v AWS

Služba Amazon Web Services poskytuje vysoce spolehlivou, škálovatelnou a nízkorozpočtovou cloudovou platformu, kterou používají stovky tisíc firem v 190 zemích po celém světě. Startupy, malé a střední podniky, velké enterprise firmy a zákazníci ve veřejném sektoru mají přístup ke stavebním kamenům, které slouží na rychlý vývoj aplikací jako reakce na měnící se obchodní požadavky. Bez ohledu na to, zda chcete vytvářet webové nebo mobilní aplikace, prípadně postavené na klasických serverech či kontejnerech, AWS davá vývojářům do rukou mnoho nástrojů, které jim pomáhají vytvářet a nasazovat aplikace jednoduše, rychle a při nízkých nákladech.

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Artificial Intelligence (Machine Learning) on AWS: How to Start

Artificial Intelligence (Machine Learning) on AWS: How to Start

Amazon has been investing deeply in artificial intelligence (AI) for over 20 years. Machine learning (ML) algorithms drive many of its internal systems. It is also core to the capabilities Amazon's customers experience – from the path optimization in the fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, drone initiative Prime Air, and the new retail experience Amazon Go. This is just the beginning. Amazon's mission is to share learnings and ML capabilities as fully managed services, and put them into the hands of every developer and data scientist. If you are interested, how can you develop ML-based smart applications on the AWS platform, and want to see a couple of cool demos, join us for the next AWS meetup. AWS Solutions Architect, Vladimir Simek, will be presenting the full AWS portfolio for AI and ML - from virtual servers enabled for training Deep Learning models up to a fully managed API-based services.

AWS Webinar CZSK 02 Bezpecnost v AWS cloudu

AWS Webinar CZSK Uvod do cloud computingu

This document summarizes an introduction to cloud computing presentation by AWS. It discusses definitions of cloud computing, benefits such as cost savings and scalability, AWS global infrastructure and services, examples of AWS customers, and how organizations can get started with cloud migration. The presentation covers key cloud concepts in order to help audiences understand cloud computing with AWS.

Introduction to EKS (AWS User Group Slovakia)

This document discusses Amazon Elastic Container Service for Kubernetes (EKS), a managed Kubernetes service on AWS. EKS runs Kubernetes control planes for customers across multiple AWS availability zones to provide high availability and automatic healing. It allows customers to deploy and manage Kubernetes applications without having to stand up or maintain their own Kubernetes clusters. EKS integrates tightly with other AWS services and comes with features like VPC networking and IAM authentication for security.

Running Docker Containers on AWS