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Continuous Delivery for Java Apps: Build a CD Pipeline Step by Step Using Kubernetes, Docker, Vagrant, Jenkins, Spring, Maven and Artifactory – B078B3FJ7J, 2017

See: Continuous Delivery for Java Apps: Build a CD Pipeline Step by Step Using Kubernetes, Docker, Vagrant, Jenkins, Spring, Maven and Artifactory, Publisher ‏ : ‎ Leanpub (December 14, 2017)

See also: Spring Bibliography, Spring Framework and Cloud Native

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This book will guide you through the implementation of the real-world Continuous Delivery using top-notch technologies. Instead of finishing this book thinking “I know what Continuous Delivery is, but I have no idea how to implement it”, you will end up with your machine set up with a Kubernetes cluster running Jenkins Pipelines in a distributed and scalable fashion (each Pipeline run on a new Jenkins slave dynamically allocated as a Kubernetes pod) to test (unit, integration, acceptance, performance and smoke tests), build (with Maven), release (to Artifactory), distribute (to Docker Hub) and deploy (on Kubernetes) a Spring Boot app to testing, staging and production environments implementing the Canary Release deployment pattern.

TABLE OF CONTENTS:

INTRODUCTION
Agile
Scrum
Scrum and Continuous Integration
Deployed vs Released
Scrum and Continuous Delivery
XP and Continuous Delivery
Automated Tests
Continuous Integration
Feature Branch
Continuous Delivery
Continuous Delivery Pipeline
Continuous Delivery vs Continuous Deployment
Canary Release
A/B Tests
Feature Flags

NOTEPAD APP: AUTOMATED TESTS, MAVEN AND FLYWAY
Pre-Requisites
The Notepad Application
Automated Tests
Unit Tests
Integration Tests
 Acceptance Tests
  Page Object
  Distributed Acceptance Tests with Selenium-Grid
 Smoke Tests
 Performance Tests with Gatling.io
Apache Maven
Maven Snapshot vs Release
The Default Lifecycle and its Phases
Maven Repositories
Repository Manager (Artifactory)
Maven Plugins: Surefire and Failsafe
Maven Profile
Running Unit Tests
Running Integration Tests
Running Acceptance Tests
Running Smoke Tests
Running Performance Tests
Publish Artifacts to Artifactory with Maven
Publish a Snapshot to Artifactory
Publish a Release to Artifactory
The release:prepare Goal
The release:perform Goal
 Flyway

DOCKER
Introduction to Docker
Difference Between Container and Image
Docker Hub
Create your Account
Official Docker Repositories
Image Tags
Non-Official Docker Images
Create a Repository, an Image and Push it to Docker Hub
 Running Containers on Docker
  Running Containers as Daemons
  Container Clean Up
  Naming Containers
  Exposing Ports
  Persistent Data with Volumes
  Environment Variables
Docker Networking
  Create a Bridge Network
  Container Static IP Address
  Linking Containers
 Most Used Docker Commands
  Images
  Containers
  Misc
 Building Docker Images: Dockerfile

JENKINS: PIPELINE AS CODE AND CHATOPS
 Jenkins Overview
 Jenkins Concepts
  Job (or Project)
  Build
  Artifact
  Workspace
  Executor
  Plugin
  Node, Master, and Agent (or Slave)
 ChatOps
  Create a Slack Workspace
  Integrate Slack with Jenkins
  Slack Notification Plugin
  Use Hubot to Interact with Jenkins
 Jenkins Pipeline
  Declarative Pipeline vs Scripted Pipeline
  Scripted Pipeline
  Using Docker with Jenkins Pipelines
  Running Docker from Within the Jenkins Container
Scaling Jenkins with Slaves

KUBERNETES
 Why Kubernetes?
 Set up a Kubernetes Cluster using Vagrant
 Hands-on Introduction to Kubernetes
 Kubernetes Concepts
  Namespaces
  Pods
  Labels
  Replica Sets
  Services
  Service Discovery using DNS
  Service Discovery using Namespaces
  Volumes
  Handling External Configurations
  Config Maps
  Changing Logback Log Level at Runtime
  Secrets
  Using Secrets as Environment Variables
  Using Secrets as Files from a Pod
  Deployments
  Readiness Probes
  Liveness Probes
  Canary Release
Kubernetes Architecture
Kubernetes Master Components
Etcd
API Server
Controller Manager
Scheduler
 Kubernetes Node Components
  Service Proxy
  Kubelet
  cAdvisor
 Kubernetes Add-ons
  Web UI (Dashboard)
   Monitoring Kubernetes with Heapster, InfluxDB and Grafana
   Web UI Overview
  DNS

HANDS-ON PROJECT

APPENDICES

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B00D3VH4IO

See: Vagrant: Up and Running: Create and Manage Virtualized Development Environments 1st Edition

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List of Linux containers

Linux containers are implementations of operating system-level virtualization for the Linux operating system. Several implementations exist, all based on the virtualization, isolation, and resource management mechanisms provided by the Linux kernel, notably Linux namespaces and cgroups.[1] These include:” (WP)

See also

References

  1. ^ Rami, Rosen. “Namespaces and Cgroups, the basis of Linux Containers” (PDF). Retrieved 18 August 2016.
  2. ^ “LXC – Linux Containers”linuxcontainers.org. Retrieved 2014-11-10.
  3. ^ “LXD”linuxcontainers.org. Retrieved 2021-02-11.
  4. ^ “Rkt container engine”.
  5. ^ “CNCF Archives RKT”. CNCF. Retrieved 19 Aug 2019.
  6. ^ “Red Hat to Acquire CoreOS”. Red Hat inc. Retrieved 30 Jan 2018.
  7. ^ Poettering, Lennart. “systemd For Administrators, Part XXI”. Retrieved 2 July 2016.
  8. ^ Rootless containers with Podman and fuse-overlayfs, CERN Workshop, 2019-06-04
  9. ^ https://hpc.github.io/charliecloud/. Retrieved 4 October 2020. Missing or empty |title= (help)
  10. ^ “Bottlerocket is a Linux-based operating system purpose-built to run containers”.
This Linux-related article is a stub. You can help Wikipedia by expanding it.

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DevOps toolchain

See also: CloudOps, toolchain

“A DevOps toolchain is a set or combination of tools that aid in the delivery, development, and management of software applications throughout the systems development life cycle, as coordinated by an organization that uses DevOps practices.

Generally, DevOps tools fit into one or more activities, which supports specific DevOps initiatives: Plan, Create, Verify, Package, Release, Configure, Monitor, and Version Control.[1][2]” (WP)

Toolchains

“In software, a toolchain is the set of programming tools that is used to perform a complex software development task or to create a software product, which is typically another computer program or a set of related programs. In general, the tools forming a toolchain are executed consecutively so the output or resulting environment state of each tool becomes the input or starting environment for the next one, but the term is also used when referring to a set of related tools that are not necessarily executed consecutively.[3][4][5]

As DevOps is a set of practices that emphasizes the collaboration and communication of both software developers and other information technology (IT) professionals, while automating the process of software delivery and infrastructure changes, its implementation can include the definition of the series of tools used at various stages of the lifecycle; because DevOps is a cultural shift and collaboration between development and operations, there is no one product that can be considered a single DevOps tool. Instead a collection of tools, potentially from a variety of vendors, are used in one or more stages of the lifecycle.[6][7]” (WP)

Stages of DevOps

Further information: DevOps

Plan

Plan is composed of two things: “define” and “plan”.[8] This activity refers to the business value and application requirements. Specifically “Plan” activities include:

  • Production metrics, objects and feedback
  • Requirements
  • Business metrics
  • Update release metrics
  • Release plan, timing and business case
  • Security policy and requirement

A combination of the IT personnel will be involved in these activities: business application owners, software developmentsoftware architects, continual release management, security officers and the organization responsible for managing the production of IT infrastructure.

Create

Create is composed of the building (see also build automation), coding, and configuring of the software development process.[8] The specific activities are:

Tools and vendors in this category often overlap with other categories. Because DevOps is about breaking down silos, this is reflective in the activities and product solutions.[clarification needed]

Verify

Verify is directly associated with ensuring the quality of the software release; activities designed to ensure code quality is maintained and the highest quality is deployed to production.[8] The main activities in this are:

Solutions for verify related activities generally fall under four main categories: Test automation , Static analysis , Test Lab, and Security.

Packaging

Packaging refers to the activities involved once the release is ready for deployment, often also referred to as staging or Preproduction / “preprod”.[8] This often includes tasks and activities such as:

  • Approval/preapprovals
  • Package configuration
  • Triggered releases
  • Release staging and holding

Release

Release related activities include schedule, orchestration, provisioning and deploying software into production and targeted environment.[9] The specific Release activities include:

  • Release coordination
  • Deploying and promoting applications
  • Fallbacks and recovery
  • Scheduled/timed releases

Solutions that cover this aspect of the toolchain include application release automation, deployment automation and release management.

Configure

Configure activities fall under the operation side of DevOps. Once software is deployed, there may be additional IT infrastructure provisioning and configuration activities required.[8] Specific activities including:

  • Infrastructure storage, database and network provisioning and configuring
  • Application provision and configuration.

The main types of solutions that facilitate these activities are continuous configuration automationconfiguration management, and infrastructure as code tools.[10]

Monitor

Monitoring is an important link in a DevOps toolchain. It allows IT organization to identify specific issues of specific releases and to understand the impact on end-users.[8] A summary of Monitor related activities are:

  • Performance of IT infrastructure
  • End-user response and experience
  • Production metrics and statistics

Information from monitoring activities often impacts Plan activities required for changes and for new release cycles.

Version Control

Version Control is an important link in a DevOps toolchain and a component of software configuration management. Version Control is the management of changes to documents, computer programs, large web sites, and other collections of information.[8] A summary of Version Control related activities are:

  • Non-linear development
  • Distributed development
  • Compatibility with existent systems and protocols
  • Toolkit-based design

Information from Version Control often supports Release activities required for changes and for new release cycles.

See also

References

  1. ^ Edwards, Damon. “Integrating DevOps tools into a Service Delivery Platform”dev2ops.org.
  2. ^ Seroter, Richard. “Exploring the ENTIRE DevOps Toolchain for (Cloud) Teams”infoq.com.
  3. ^ “Toolchain Overview”nongnu.org. 2012-01-03. Retrieved 2013-10-21.
  4. ^ “Toolchains”elinux.org. 2013-09-08. Retrieved 2013-10-21.
  5. ^ Imran, Saed; Buchheit, Martin; Hollunder, Bernhard; Schreier, Ulf (2015-10-29). Tool Chains in Agile ALM Environments: A Short IntroductionLecture Notes in Computer Science9416. pp. 371–380. doi:10.1007/978-3-319-26138-6_40ISBN 978-3-319-26137-9.
  6. ^ Loukides, Mike (2012-06-07). “What is DevOps?”.
  7. ^ Garner Market Trends: DevOps – Not a Market, but Tool-Centric Philosophy That supports a Continuous Delivery Value Chain (Report). Gartner. 18 February 2015.
  8. a b c d e f g Avoid Failure by Developing a Toolchain that Enables DevOps (Report). Gartner. 16 March 2016.
  9. ^ Best Practices in Change, Configuration and Release Management (Report). Gartner. 14 July 2010.
  10. ^ Roger S. Pressman (2009). Software Engineering: A Practitioner’s Approach (7th International ed.). New York: McGraw-Hill.

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SCM Software Configuration Management – S/W CM

See also: Configuration management (CM)

Not to be confused with Version Control System.

In software engineeringsoftware configuration management (SCM or S/W CM) is the task of tracking and controlling changes in the software, part of the larger cross-disciplinary field of configuration management.[1] SCM practices include revision control and the establishment of baselines. If something goes wrong, SCM can determine what was changed and who changed it. If a configuration is working well, SCM can determine how to replicate it across many hosts.

The acronym “SCM” is also expanded as source configuration management process and software change and configuration management.[2] However, “configuration” is generally understood to cover changes typically made by a system administrator.

Purposes

The goals of SCM are generally:[citation needed]

  • Configuration identification – Identifying configurations, configuration items and baselines.
  • Configuration control – Implementing a controlled change process. This is usually achieved by setting up a change control board whose primary function is to approve or reject all change requests that are sent against any baseline.
  • Configuration status accounting – Recording and reporting all the necessary information on the status of the development process.
  • Configuration auditing – Ensuring that configurations contain all their intended parts and are sound with respect to their specifying documents, including requirements, architectural specifications and user manuals.
  • Build management – Managing the process and tools used for builds.
  • Process management – Ensuring adherence to the organization’s development process.
  • Environment management – Managing the software and hardware that host the system.
  • Teamwork – Facilitate team interactions related to the process.
  • Defect tracking – Making sure every defect has traceability back to the source.

With the introduction of cloud computing the purposes of SCM tools have become merged in some cases. The SCM tools themselves have become virtual appliances that can be instantiated as virtual machines and saved with state and version. The tools can model and manage cloud-based virtual resources, including virtual appliances, storage units, and software bundles. The roles and responsibilities of the actors have become merged as well with developers now being able to dynamically instantiate virtual servers and related resources.[3]

History

The history of software configuration management (SCM) in computing can be traced back as early as the 1950s, when CM (for Configuration Management), originally for hardware development and production control, was being applied to software development. Early software had a physical footprint, such as cardstapes, and other media. The first software configuration management was a manual operation. With the advances in language and complexity, software engineering, involving configuration management and other methods, became a major concern due to issues like schedule, budget, and quality. Practical lessons, over the years, had led to the definition, and establishment, of procedures and tools. Eventually, the tools became systems to manage software changes.[4] Industry-wide practices were offered as solutions, either in an open or proprietary manner (such as Revision Control System). With the growing use of computers, systems emerged that handled a broader scope, including requirements management, design alternatives, quality control, and more; later tools followed the guidelines of organizations, such as the Capability Maturity Model of the Software Engineering Institute.

See also

References

  1. ^ Roger S. Pressman (2009). Software Engineering: A Practitioner’s Approach (7th International ed.). New York: McGraw-Hill.
  2. ^ Gartner and Forrester Research
  3. ^ Amies, A; Peddle S; Pan T M; Zou P X (June 5, 2012). “Develop cloud applications with Rational tools”IBM DeveloperWorks. IBM.
  4. ^ “1988 “A Guide to Understanding Configuration Management in Trusted Systems” National Computer Security System (via Google)

Further reading

  • 828-2012 IEEE Standard for Configuration Management in Systems and Software Engineering. 2012. doi:10.1109/IEEESTD.2012.6170935ISBN 978-0-7381-7232-3.
  • Aiello, R. (2010). Configuration Management Best Practices: Practical Methods that Work in the Real World (1st ed.). Addison-Wesley. ISBN 0-321-68586-5.
  • Babich, W.A. (1986). Software Configuration Management, Coordination for Team Productivity. 1st edition. Boston: Addison-Wesley
  • Berczuk, Appleton; (2003). Software Configuration Management Patterns: Effective TeamWork, Practical Integration (1st ed.). Addison-Wesley. ISBN 0-201-74117-2.
  • Bersoff, E.H. (1997). Elements of Software Configuration Management. IEEE Computer Society Press, Los Alamitos, CA, 1-32
  • Dennis, A., Wixom, B.H. & Tegarden, D. (2002). System Analysis & Design: An Object-Oriented Approach with UML. Hoboken, New York: John Wiley & Sons, Inc.
  • Department of Defense, USA (2001). Military Handbook: Configuration management guidance (rev. A) (MIL-HDBK-61A). Retrieved January 5, 2010, from http://www.everyspec.com/MIL-HDBK/MIL-HDBK-0001-0099/MIL-HDBK-61_11531/
  • Futrell, R.T. et al. (2002). Quality Software Project Management. 1st edition. Prentice-Hall.
  • International Organization for Standardization (2003). ISO 10007: Quality management systems – Guidelines for configuration management.
  • Saeki M. (2003). Embedding Metrics into Information Systems Development Methods: An Application of Method Engineering Technique. CAiSE 2003, 374–389.
  • Scott, J.A. & Nisse, D. (2001). Software configuration management. In: Guide to Software Engineering Body of Knowledge. Retrieved January 5, 2010, from http://www.computer.org/portal/web/swebok/htmlformat
  • Paul M. Duvall, Steve Matyas, and Andrew Glover (2007). Continuous Integration: Improving Software Quality and Reducing Risk. (1st ed.). Addison-Wesley Professional. ISBN 0-321-33638-0.

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