AWS CodeDeploy + Github
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1. This document discusses using AWS CodeDeploy to automatically deploy code from GitHub to Auto Scaling groups and load balancers. 2. It covers two deployment types: in-place deployments that replace application revisions directly on instances, and blue/green deployments that deploy to unused instances behind a load balancer. 3. It provides details on lifecycle events, the appspec.yml file used by CodeDeploy, and how to manually or automatically set up CodeDeploy deployments triggered by GitHub pushes through the deployment wizard.
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AWS CodeDeploy
AWS CodeDeploy is the new service announced at AWS re:Invent in Las Vegas!!!
AWS CodeDeploy is a fully managed, scalable deployment service that lets AWS certified developers and engineers quickly and simply automate the process of deploying and updating applications on Amazon EC2.
The presentation includes an introduction to Code Deploy, benefits of using Code Deploy, understanding various components and workflows of Code Deploy, ways to deploy an application, commands to create and push application using Code Deploy, steps to deploying code on instances, troubleshooting and limitations of Code Deploy. It begins with a section which gives a brief introduction to Code Deploy. The next section is about the benefits of using Code Deploy. It explains the benefits of using Code Deploy like automated deployments, centralized control etc. Specific to the benefits section comes components and workflows of Code Deploy. It briefly describes the components of Code Deploy like content, appsec file and also includes the steps to the workflow of Code Deploying. Then deploying an application which explains not just the steps to deploy an application but also answers what to deploy, how to deploy and where to deploy at the same time.
Then, comes a section about commands used to create and push application. It tells about the commands which are not just used to create an application to s3 but also push applications to s3. Then it covers the steps for deploying code on instances. It becomes really interesting as it explains the steps a user can use to deploy codes on instances by just creating an application and following the other steps.
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AWS CodeDeploy Getting Started
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Similar to AWS CodeDeploy + Github
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AWS CodeDeploy is a fully managed deployment service that allows deploying code and applications to EC2 instances and on-premise servers. It is technology agnostic and supports deploying from Amazon S3 buckets or GitHub repositories. The document provides an overview of CodeDeploy, including how to get started, the execution flow using appspec.yml files, deployment configurations and groups, and considerations for using CodeDeploy.
Tame Your Build And Deployment Process With Hudson, PHPUnit, and SSH
The document discusses setting up continuous integration using Hudson. It explains that Hudson automates build and deployment processes, provides instant feedback, and helps keep teams honest about tests. Setup involves installing Java, Hudson, and configuring a sample project in Hudson to build from a Git repository on each commit.
DevFest 2022 - Cloud Workstation Introduction TaiChung
Cloud Workstations provides preconfigured, customizable, and secure managed development environments on Google Cloud. Cloud Workstations is accessible through a browser-based IDE, from multiple local code editors (such as IntelliJ IDEA Ultimate or VS Code), or through SSH. Instead of manually setting up development environments, you can create a workstation configuration specifying your environment in a reproducible way
Journey to Microservice architecture via Amazon Lambda
Microservices are one of the latest trends in architecture design.
Made popular by the introduction of Amazon Lambda, Google Cloud Functions and Azure Functions. They seem to offer a way to structure code as a set of independent services that interact together to work as one, making each part simpler and offering an easy way to scale up. But just as every other technology they bring their own set of challenges.
Join us on lessons we learned while converting simple application to work on Lambda.
How to manage Azure with open source
This document provides instructions for managing Microsoft Azure with open source tools. It discusses Bash on Ubuntu on Windows, the Azure CLI, Juju, and running Docker on Bash on Ubuntu on Windows. Specific commands and steps are provided to install tools, connect to Azure, deploy services with Juju, and configure Docker.
How to manage Microsoft Azure with open source
This document provides instructions for managing Microsoft Azure with open source tools. It discusses Bash on Ubuntu on Windows, the Azure CLI, Juju, and running Docker on Bash on Ubuntu on Windows. Specific commands and steps are provided to install tools, manage resources on Azure, deploy services, and connect Docker between the Windows and Ubuntu environments.
Capifony. Minsk PHP MeetUp #11
Capistrano is an open source tool for running scripts on multiple servers. It’s primary use is for easily deploying applications. While it was built specifically for deploying Rails apps, it’s pretty simple to customize it to deploy other types of applications.
capifony is a deployment recipes collection that works with both symfony and Symfony2 applications.
JDD 2017: 7 things which you should care about before release your code to pr...
You have finished working on your new Java project and it's time to release it to the rest of the World? What's now? Do you remember about all important things? This talk aims to highlight the most important things before the first release. Those topics will be covered on presentation:
- Versioning
- Profiling
- Health checks
- Logs
- Performance
- Monitoring and alarming
- Release process
Nodejs in Production
This document provides best practices for running Node.js in production including: using tools like istanbul for test coverage and jshint for static code analysis; optimizing for speed by using async patterns and clustering; structuring code with object literals; minimizing modules and headers; using functional programming patterns; leveraging ES6 features; choosing template engines like Nunjucks; naming middlewares; centralizing error handling; using debug tools; logging appropriately; monitoring with New Relic; using promise libraries like Bluebird; managing processes with npm scripts, Forever, or systemd/Upstart services; configuring a reverse proxy like Nginx; and referencing additional resources.
Deploy your Python code on Azure Functions
This document discusses Python Azure Functions. Azure Functions is an event-driven serverless compute platform on Microsoft Azure. It allows building web APIs, processing data streams, and more using event triggers and bindings without managing infrastructure. The document covers setting up the Azure Functions Core tools and Azure CLI to create, develop and deploy Python functions to Azure from the command line. It also provides an overview of the deployment process, including creating resource groups and storage accounts, and publishing functions to Azure.
One-Man Ops
Krux operates a large infrastructure serving thousands of user requests per second. They use Puppet and tools like Cloudkick, Foreman, Boto, and Vagrant to manage their infrastructure in an automated and scalable way. Their Puppet configuration is split into modules, environments, and datacenters. They launch AWS nodes programmatically and configure them with Puppet. Cloudkick is used for monitoring and parallel SSH. Boto allows full Python API access to AWS. Vagrant allows consistently provisioning development machines locally. Automation and external configuration enable their small operations team to manage a large, dynamic infrastructure.
Development Setup of B-Translator
B-Translator helps to get feedback about l10n (translations of the programs). It tries to collect very small translation contributions from a wide crowd of people and to dilute them into something useful. It is developed as a Drupal7 profile and the code is hosted on GitHub. Here I describe the development setup and process that I use for this project. Most of the the tips are project specific, however some of them can be used on any Drupal project.
2018 RubyHACK: put git to work - increase the quality of your rails project...
This is the RubyHack 2018 presentation on automating your common tasks using git
The main idea is to use the tools you already have to improve your day to day work
2018 the conf put git to work - increase the quality of your rails project...
These are the slides I used in my presentation at #theconfbr this year.
If you have any questions or comments about the presentation, contact me through my twitter @urubatan.
if you want to subscribe to my weekly Ruby And Rails tips newsletter please do it in this address http://bit.ly/weekly_rails_tips
Instrumentación de entrega continua con Gitlab
Mostraremos el caso real de cómo tenemos implementado en nuestra empresa el flujo de desarrollo para integración y entrega continua, instrumentado con GitLab.
Sesión presentada por David Padilla en SG Next 2017
Distributing UI Libraries: in a post Web-Component world
Modern UI Component libraries influenced by Web Components will rely more heavily on package management than last generation UI Frameworks. In this 15 minute session we'll introduce package management for web graphical user interfaces, talk about the best package contents for a UI component, and some tactics for making smooth releases.
For video, skip to 57 minutes, 13 seconds (57:13), http://www.youtube.com/watch?v=BhP86d5IiM4&t=57m13s
Scaffolding for Serverless: lightning talk for AWS Arlington Meetup
Tools around a sample serverless app to automate the drudgery associated with a project. Testing with pytest and coverage; code smells with flake8; documentation with Sphinx for HTML/ePub output; different deployment environments based on code repo branch (dev, qa, prod, and per-developer); CI/CD pipeline to run all this, including deployment to separate AWS environments. And a simple app with API Gateway, Lambda, S3, DynamoDB.
Zero Downtime Deployment with Ansible
My talk from DevOpsCon Berlin 2016.
Ansible is a radically simple and lightweight provisioning framework which makes your servers and applications easier to provision and deploy. By orchestrating your application deployments you gain benefits such as documentation as code, testability, continuous integration, version control, refactoring, automation and autonomy of your deployment routines, server and application configuration. Ansible uses a language that approaches plain English, uses SSH and has no agents to install on remote systems. It is the simplest way to automate and orchestrate application deployment, configuration management and continuous delivery.
In this tutorial you will be given an introduction to Ansible and learn how to provision Linux servers with a web-proxy, a database and some other packages. Furthermore we will automate zero downtime deployment of a Java application to a load balanced environment.
An OpenShift Primer for Developers to get your Code into the Cloud (PTJUG)
Session given at the PTJUG (Portugal JUG):
Whether you're a seasoned Java developer looking to start hacking on EE6 or you just wrote your first line of Ruby yesterday, the cloud is turning out to be the perfect environment for developing applications in just about any modern language or framework. There are plenty of clouds and platform-as-a-services to choose from, but where to start? Join us for an action-packed hour of power where we'll show you how to deploy an application written in the language of your choice - Java, Ruby, PHP, Perl or Python, with the framework of your choice - EE6, CDI, Seam, Spring, Zend, Cake, Rails, Sinatra, PerlDancer or Django to the OpenShift PaaS in just minutes. And without having to rewrite your app to get it to work the way the cloud provider thinks your app should work.
Check the command-line fu as we leverage Git to onboard apps onto OpenShift Express in seconds, while also making use of the web browser do the heavy-lifting of provisioning clusters, deploying, monitoring and auto-scaling apps in OpenShift Flex.
If you want to learn how the OpenShift PaaS and investing an hour of your time can change everything you thought you knew about developing applications in the cloud, this session is for you!
End-to-end CI/CD deployments of containerized applications using AWS services
This document discusses setting up an end-to-end CI/CD pipeline on AWS to continuously deploy a containerized application. It begins with an introduction and background on the speaker. It then describes the sample application that will be deployed. The rest of the document goes through setting up the different AWS services needed for continuous integration, building Docker containers, and deploying the application via AWS Lambda and Amazon ECS/Fargate. It emphasizes using AWS Code services like CodeCommit, CodeBuild, CodePipeline and CodeDeploy to automate the process from code changes to production deployments.
Similar to AWS CodeDeploy + Github (20)
Tame Your Build And Deployment Process With Hudson, PHPUnit, and SSH
Tame Your Build And Deployment Process With Hudson, PHPUnit, and SSH
DevFest 2022 - Cloud Workstation Introduction TaiChung
DevFest 2022 - Cloud Workstation Introduction TaiChung
Journey to Microservice architecture via Amazon Lambda
Journey to Microservice architecture via Amazon Lambda
JDD 2017: 7 things which you should care about before release your code to pr...
JDD 2017: 7 things which you should care about before release your code to pr...
2018 RubyHACK: put git to work - increase the quality of your rails project...
2018 RubyHACK: put git to work - increase the quality of your rails project...
2018 the conf put git to work - increase the quality of your rails project...
2018 the conf put git to work - increase the quality of your rails project...
Distributing UI Libraries: in a post Web-Component world
Distributing UI Libraries: in a post Web-Component world
Scaffolding for Serverless: lightning talk for AWS Arlington Meetup
Scaffolding for Serverless: lightning talk for AWS Arlington Meetup
An OpenShift Primer for Developers to get your Code into the Cloud (PTJUG)
An OpenShift Primer for Developers to get your Code into the Cloud (PTJUG)
End-to-end CI/CD deployments of containerized applications using AWS services
End-to-end CI/CD deployments of containerized applications using AWS services
Recently uploaded
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Hematology Analyzer Machine - Complete Blood Count
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
For International shipping and maritime laws all wood must contain the ISPM 15 Stamp. Here is how and why.
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3:国家专业人才认证中心颁发入库证书
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6:个人职称评审加20分
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Comparative analysis between traditional aquaponics and reconstructed aquapon...
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
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KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
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Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...
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Generative AI leverages algorithms to create various forms of content
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Hematology Analyzer Machine - Complete Blood Count
Hematology Analyzer Machine - Complete Blood Count
john krisinger-the science and history of the alcoholic beverage.pptx
john krisinger-the science and history of the alcoholic beverage.pptx
Introduction to AI Safety (public presentation).pptx
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ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
AWS CodeDeploy + Github
- 2. Demo https://github.com/gumpcha/aws-codedeploy-demo Github -> CodeDeploy -> Auto Scaling / Load Balancer Deploy trigger - git push
- 3. Deployment Types 1. In-place deployment 2. Blue/green deployment
- 6. appspec.yml version: 0.0 os: linux files: - source: /index.html destination: /var/www/html/ hooks: ApplicationStop: - location: scripts/stop_server timeout: 300 runas: root BeforeInstall: - location: scripts/install_dependencies timeout: 300 runas: root - location: scripts/start_server timeout: 300 runas: root #!/bin/bash yum install -y httpd #!/bin/bash service httpd start #!/bin/bash isExistApp=`pgrep httpd` if [[ -n $isExistApp ]]; then service httpd stop fi
- 7. Setup - Manual - Application - Deployment group - staging/production/… - Auto Scaling group - Load balancer - Service role - AWSCodeDeployRole - Trust Relationships - Key pair name - AMI - IAM instance profile: AmazonEC2RoleforAWSCodeDeploy - install codedeploy-agent
- 8. Setup - Deployment Wizard
- 9. Github 연동(1/4) 1. AWS CodeDeploy에 deployment group까지 미리 생성 2. github에서 CodeDeploy에 접근할 수 있는 IAM User 생성 1. AWSCodeDeployDeployerAccess Policy
- 10. Github 연동(2/4) “AWS CodeDeploy” Service 추가(1/2)
- 11. Github 연동(2/4) “AWS CodeDeploy” Service 추가(2/2)
- 12. Github 연동(3/4) github 계정 설정에서 Github Personal Access Token 생성
- 13. Github 연동(4/4) “GitHub Auto-Deployment” Service 추가(1/2)
- 14. Github 연동(4/4) “GitHub Auto-Deployment” Service 추가(2/2)