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Creating Continuous Deployment Pipeline for Cloud Platforms

Video Description

Automated testing and deploying of containers

About This Video

  • This comprehensive video tutorial will take you through the various methods of logging and monitoring containers.
  • Learn how to receive metrics from log files
  • Set up continuous delivery systems to automate testing and deploying Docker containers

In Detail

Continuous Delivery is a process whereby code changes are automatically built, tested, and prepared for release to production. This video course starts by showing you how to ship logs to a central location for easier viewing and configure monitoring services to check the health of your containers and services with AWS, Azure, and Google. You will begin by designing toolsets and components which will make up the Continuous Deployment pipeline of the future
You will learn about logging services such as AWS, Google, and Azure. You will also learn why centralized logging is important and how container logging differs from logging from physical servers. You will then master monitoring containers and see some examples involving monitoring dashboards that will be installed in this course.

Toward the end of the course, you will explore how monitoring and logging overlap, and how metrics can be retrieved from log files.

All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Creating-Continuous-Deployment-Pipeline-for-Cloud-Platforms

Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

Table of Contents

  1. Chapter 1 : Building the Continuous Deployment Pipeline
    1. The Course Overview 00:02:49
    2. What is a Continuous Deployment Pipeline? 00:02:58
    3. What is Infrastructure as Code and Why Is It Important? 00:03:45
    4. An introduction to Terraform 00:03:28
    5. Overview and Configuration of Concourse 00:05:53
    6. Overview and Configuration of Prometheus 00:02:40
    7. Overview and Configuration of Grafana 00:02:43
    8. Overview of AWS CloudWatch and Google Stackdriver 00:02:59
  2. Chapter 2 : Continuous Deployment in Action – Testing and Deploying Our Application to Production
    1. Creating Our First Docker Application 00:05:49
    2. Continuously Testing Changes to Our Docker Application 00:04:59
    3. Automatically Deploying Changes to Our Docker Application for the First Time 00:02:34
  3. Chapter 3 : Leveraging the Continuous Deployment Pipeline to Build the Production Environment
    1. Building Our Production Kubernetes Cluster with Terraform 00:10:22
    2. Automatically Changing the Production Environment with Concourse and Terraform 00:07:05
  4. Chapter 4 : Application Logging with Amazon CloudWatch, Google Stackdriver and Azure Log Analytics
    1. Installing Amazon CloudWatch Logs Agent to Store Application Logs in AWS 00:07:17
    2. Visualizing Application Logs within Amazon CloudWatch Logs 00:02:45
    3. Configuring Grafana to Show Application Logs Stored in Amazon CloudWatch 00:03:48
    4. Installing the Google Stackdriver Logging Agent to Store Application Logs in GCP 00:02:11
    5. Visualizing Application Logs within GCP 00:01:45
    6. Configuring Grafana to Show Application Logs Stored in Google Stackdriver 00:02:49
    7. A Brief Look into Microsoft Azure Log Analytics 00:01:19
  5. Chapter 5 : Monitoring the Application Behavior with Prometheus and Grafana
    1. Configuring Prometheus for Platform and Application Observability 00:09:16
    2. Configuring Grafana to Display Metrics Saved in Prometheus 00:01:51
    3. Creating a Dashboard to Monitor the Health of Our Production Cluster 00:03:02
    4. Creating a Dashboard to Monitor the Health of Our Application 00:01:50