Orchestration (computing) explained

In system administration, orchestration is the automated configuration, coordination,[1] deployment, development, and management of computer systems and software.[2]

Many tools exist to automate server configuration and management, including Airflow, Kubernetes, Ansible, Puppet, Salt, Terraform,[3] and AWS CloudFormation.[4]

Usage

Orchestration is often discussed in the context of service-oriented architecture, virtualization, provisioning, converged infrastructure and dynamic data center topics. Orchestration in this sense is about aligning the business request with the applications, data, and infrastructure.[5]

In the context of cloud computing, the main difference between workflow automation and orchestration is that workflows are processed and completed as processes within a single domain for automation purposes, whereas orchestration includes a workflow and provides a directed action towards larger goals and objectives.

In this context, and with the overall aim to achieve specific goals and objectives (described through the quality of service parameters), for example, meet application performance goals using minimized cost[6] and maximize application performance within budget constraints,[7] cloud management solutions also encompass frameworks for workflow mapping and management.

See also

Notes and References

  1. Book: Sarma, Anita . https://doi.org/10.1007/978-3-030-00262-6_10 . Handbook of Software Engineering . 978-3-030-00262-6 . Coordination Technologies . Sungdeok Cha . Richard N. Taylor . Kyochul Kang . Springer Cham . 11 Feb 2019 . 15 July 2024.
  2. Book: Erl, Thomas . 2005 . Service-Oriented Architecture: Concepts, Technology & Design . Prentice Hall . 0-13-185858-0.
  3. Web site: Why we use Terraform and not Chef, Puppet, Ansible, SaltStack, or CloudFormation. Brikman. Yevgeniy. 2016-09-26. 2018-12-17. 2016-10-05. https://web.archive.org/web/20161005221443/https://blog.gruntwork.io/why-we-use-terraform-and-not-chef-puppet-ansible-saltstack-or-cloudformation-7989dad2865c. live.
  4. Web site: AWS CloudFormation Introduction. Giangntc. 2019-04-12. 2019-04-12. 2013-01-03. https://web.archive.org/web/20130103043302/https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html. live.
  5. Book: Menychtas . Andreas . Gatzioura . Anna . Varvarigou . Theodora . A Business Resolution Engine for Cloud Marketplaces . IEEE Third International Conference on Cloud Computing Technology and Science (CloudCom) . 2011 . 462–469 . . 10.1109/CloudCom.2011.68 . 2011 IEEE Third International Conference on Cloud Computing Technology and Science . 978-1-4673-0090-2 . 14985590.
  6. Book: Mao, Ming. M. Humphrey. Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis . Auto-scaling to minimize cost and meet application deadlines in cloud workflows . 2011 . 1–12 . 10.1145/2063384.2063449. 978-1-4503-0771-0. 11960822.
  7. Book: Mao, Ming. M. Humphrey. 2013 IEEE 27th International Symposium on Parallel and Distributed Processing . Scaling and Scheduling to Maximize Application Performance within Budget Constraints in Cloud Workflows . 2013. 10.1109/IPDPS.2013.61. 978-0-7695-4971-2. 67–78. 5226147.

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