Tag: HashiCorp Terraform DevOps

Puppet Configuration Management DevOps – Heterogeneous infrastructure, frequently provisioned, short lived, and automated provisioning on-demand. Infrastructure as Code, Enable self-service infrastructure

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See: Bootstrapping Microservices with Docker, Kubernetes, and Terraform: A project-based guide

See also Kubernetes and Cloud Native

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See: Pipeline as Code: Continuous Delivery with Jenkins, Kubernetes, and Terraform

See also Kubernetes and Cloud Native

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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 development, software 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 automation, configuration 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 Introduction. Lecture Notes in Computer Science. 9416. pp. 371–380. doi:10.1007/978-3-319-26138-6_40. ISBN 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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IaC Infrastructure as Code

Return to Timeline of the History of Computers, Networking

Infrastructure as code (IaC) is the process of managing and provisioning computer data centers through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools.[1] The IT infrastructure managed by this process comprises both physical equipment, such as bare-metal servers, as well as virtual machines, and associated configuration resources. The definitions may be in a version control system. It can use either scripts or declarative definitions, rather than manual processes, but the term is more often used to promote declarative approaches.

Overview

IaC grew as a response to the difficulty posed by utility computing and second-generation web frameworks. In 2006, the launch of Amazon Web Services’ Elastic Compute Cloud and the 1.0 version of Ruby on Rails just months before[2] created widespread scaling problems in the enterprise that were previously experienced only at large, multi-national companies.[3] With new tools emerging to handle this ever growing field, the idea of IaC was born. The thought of modelling infrastructure with code, and then having the ability to design, implement, and deploy applications infrastructure with known software best practices appealed to both software developers and IT infrastructure administrators. The ability to treat infrastructure like code and use the same tools as any other software project would allow developers to rapidly deploy applications.[4]

Added value and advantages

The value of IaC can be broken down into three measurable categories: cost, speed, and risk.[citation needed] Cost reduction aims at helping not only the enterprise financially, but also in terms of people and effort, meaning that by removing the manual component, people are able to refocus their efforts towards other enterprise tasks.[citation needed] Infrastructure automation enables speed through faster execution when configuring your infrastructure and aims at providing visibility to help other teams across the enterprise work quickly and more efficiently. Automation removes the risk associated with human error, like manual misconfiguration; removing this can decrease downtime and increase reliability. These outcomes and attributes help the enterprise move towards implementing a culture of DevOps, the combined working of development and operations.[5]

Types of approaches

There are generally two approaches to IaC: declarative (functional) vs. imperative (procedural). The difference between the declarative and the imperative approach is essentially ‘what’ versus ‘how’ . The declarative approach focuses on what the eventual target configuration should be; the imperative focuses on how the infrastructure is to be changed to meet this.[6] The declarative approach defines the desired state and the system executes what needs to happen to achieve that desired state. Imperative defines specific commands that need to be executed in the appropriate order to end with the desired conclusion. [7]

Methods

There are two methods of IaC: ‘push‘ and ‘pull‘ . The main difference is the manner in which the servers are told how to be configured. In the pull method the server to be configured will pull its configuration from the controlling server. In the push method the controlling server pushes the configuration to the destination system.[8]

Tools

There are many tools that fulfill infrastructure automation capabilities and use IaC. Broadly speaking, any framework or tool that performs changes or configures infrastructure declaratively or imperatively based on a programmatic approach can be considered IaC.[9] Traditionally, server (lifecycle) automation and configuration management tools were used to accomplish IaC. Now enterprises are also using continuous configuration automation tools or stand-alone IaC frameworks, such as Microsoft’s PowerShell DSC[10] or AWS CloudFormation.[11]

Continuous configuration automation

All continuous configuration automation (CCA) tools can be thought of as an extension of traditional IaC frameworks. They leverage IaC to change, configure, and automate infrastructure, and they also provide visibility, efficiency and flexibility in how infrastructure is managed.[3] These additional attributes provide enterprise-level security and compliance.

Community content

See also: List of systems management systems and Comparison of open-source configuration management software

An important aspect when considering CCA tools, if they are open source, is the community content. As Gartner states, the value of CCA tools is “as dependent on user-community-contributed content and support as it is on the commercial maturity and performance of the automation tooling.”[3] Vendors like Puppet and Chef, those that have been around a significant amount of time, have created their own communities. Chef has Chef Community Repository and Puppet has PuppetForge.[12] Other vendors rely on adjacent communities and leverage other IaC frameworks such as PowerShell DSC.[10] New vendors are emerging that are not content driven, but model driven with the intelligence in the product to deliver content. These visual, object-oriented systems work well for developers, but they are especially useful to production oriented DevOps and operations constituents that value models versus scripting for content. As the field continues to develop and change, the community based content will become ever important to how IaC tools are used, unless they are model driven and object oriented.

Notable CCA tools include:

ToolReleased byMethodApproachWritten inComments
ChefChef (2009)PullDeclarative and imperativeRuby–
OtterInedoPushDeclarative and imperative–Windows oriented
PuppetPuppet (2005)PullDeclarative and imperativeC++ & Clojure since 4.0, Ruby–
SaltStackSaltStackPush and PullDeclarative and imperativePython–
CFEngineNorthern.techPullDeclarativeC–
TerraformHashiCorp (2014)PushDeclarativeGo–
Ansible / Ansible TowerRed Hat (2012)PushDeclarative and imperativePython–

Other tools include AWS CloudFormation, cdist, StackStorm, Juju, and Pulumi.

Relationship to DevOps

IaC can be a key attribute of enabling best practices in DevOps – Developers become more involved in defining configuration and Ops teams get involved earlier in the development process.[13] Tools that utilize IaC bring visibility to the state and configuration of servers and ultimately provide the visibility to users within the enterprise, aiming to bring teams together to maximize their efforts.[14] Automation in general aims to take the confusion and error-prone aspect of manual processes and make it more efficient, and productive. Allowing for better software and applications to be created with flexibility, less downtime, and an overall cost effective way for the company. IaC is intended to reduce the complexity that kills efficiency out of manual configuration. Automation and collaboration are considered central points in DevOps; Infrastructure automation tools are often included as components of a DevOps toolchain.[15]

Relationship to security

The 2020 Cloud Threat Report released by Unit 42 (the threat intelligence unit of cybersecurity provider Palo Alto Networks) identified around 200,000 potential vulnerabilities in infrastructure as code templates.[16]

See also

References

  1. ^ Wittig, Andreas; Wittig, Michael (2016). Amazon Web Services in Action. Manning Press. p. 93. ISBN 978-1-61729-288-0.
  2. ^ Bower, Joseph L.; Christensen, Clayton M. “Disruptive Technologies: Catching the Wave”. Harvard Business Review.
  3. ^ a b c Fletcher, Colin; Cosgrove, Terrence (26 August 2015). Innovation Insight for Continuous Configuration Automation Tools. Gartner (Report).
  4. ^ Riley, Chris (12 November 2015). “Version Your Infrastructure”. DevOps.com.
  5. ^ Phillips, Andrew (14 May 2015). “Moving from Infrastructure Automation to True DevOps”. DevOps.com.
  6. ^ “Declarative v. Imperative Models for Configuration Management: Which Is Really Better?”. Scriptrock.com. Retrieved 14 December 2015.
  7. ^ Loschwitz, Martin (14 November 2014). “Choosing between the leading open source configuration managers”. Admin Network & Security. Lawrence, KS USA: Linux New Media USA LLC.
  8. ^ Venezia, Paul (21 November 2013). “Puppet vs. Chef vs. Ansible vs. Salt”. networkworld.com. Network World. Retrieved 14 December 2015.
  9. ^ Garner Market Trends: DevOps – Not a Market, but Tool-Centric Philosophy That supports a Continuous Delivery Value Chain (Report). Gartner. 18 February 2015.
  10. ^ a b Chaganti, Ravikanth (5 January 2016). “DevOps, Infrastructure as Code, and PowerShell DSC: The Introduction”. PowerShell Magazine. PowerShell Magazine. Retrieved 11 January 2016.
  11. ^ https://aws.amazon.com/about-aws/whats-new/2011/02/25/introducing-aws-cloudformation/
  12. ^ Sturgeon, Phil (28 October 2012). “Puppet or Chef?”.
  13. ^ Ramos, Martin (4 November 2015). “Continuous Integration: Infrastructure as Code in DevOps”. easydynamics.com. Archived from the original on 6 February 2016. Retrieved 29 January 2016.
  14. ^ Infrastructure As Code: Fueling the Fire for Faster Application Delivery (Report). Forrester. March 2015.
  15. ^ Wurster, Laurie F.; Colville, Ronni J.; Height, Cameron; Tripathi, Somendra; Rastogi, Aditi. Emerging Technology Analysis: DevOps a Culture Shift, Not a Technology (Report). Gartner.
  16. ^ “Cloud Threat Report Shows Need for Consistent DevSecOps”. InformationWeek. Retrieved 24 February 2020.

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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 engineering, software 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 cards, tapes, 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.2012.6170935. ISBN 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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