| Work group:
|
Q19/13 (Presentation Web page is available here)
|
| Title:
|
End-to-end management, governance, and security for computing including cloud computing and data handling
|
| Description:
|
1 Motivation
Digital transformation is the strategic adoption of new, fast and frequently changing technology to improve process and productivity, manage risk, reduce cost, etc. The competitiveness of digital transformation depends on evolving technology, that is, its ability to quickly adapt to future computing technologies. In particular, cloud computing and data handling are driving digital transformation. In addition, future computing technologies take into account artificial intelligence including machine learning, distributed computing, edge computing, data-centric computing, memory-centric computing, quantum cloud computing and etc. Therefore, the telecommunication industry has an important role to play in the fields of future computing and the integration and development of future computing technologies in future networks will drive a rapid move towards a digital transformation.
Cloud computing is a model for enabling service user's ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services), that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Data is of high value to building applications and services based on future computing. For this reason, not only the big data capabilities but also technologies and standards to support data usage, processing, analysing, exchanging, sharing, data quality assessment, data privacy and security, data management and data governance (as defined as a term in ITU-T Y.4052) are essential in terms of data handling.
The primary focus of this Question is to develop standards on end-to-end management, governance, security, and production operation for future computing including cloud computing and data handling from the perspective of telecommunication. The novel methods based on artificial intelligence and machine learning are essential to handle complexity of future computing management and optimally orchestrate its operation and lifecycle management.
This Question aims to provide new Recommendations in the following areas:
? end-to-end service management, orchestration, governance (e.g. microservices governance), and production operation of future computing (including cloud computing and data handling);
? end-to-end resource (including software infrastructure) management and orchestration of future computing;
? data management and governance of future computing;
? security mechanisms and methods of future computing.
It should be noted that the term "end-to-end" is used here in information technology context, and does not refer to the management of endpoints or user devices, as it would have otherwise been implied if the telecommunication technology context were used. The term end-to-end refers to multi-layer, multi-component and multi-domain in future computing for telecommunications environment, which is in the scope of this Question.
The following major Recommendations, in force at the time of approval of this Question, fall under its responsibility:
? ITU-T Y.3514, Y.3517, Y.3518, Y.3520, Y.3521, Y.3522, Y.3523, Y.3524, Y.3525, Y.3526, Y.3527, Y.3528, Y.3529, Y.3538, and Y.3539
? ITU-T Y.3604
2 Study items
Study items to be considered include, but are not limited to:
? What new Recommendation should be developed for end-to-end service management, orchestration, governance, and production operation of future computing, including but not limited to distributed/edge computing, inter-cloud computing, multi-cloud computing and cloud native related computing, on the aspects of maintenance, monitoring, measurement, scheduling, development and operations (DevOps) and continuous integration/continuous delivery (CI/CD), etc.?
? What new Recommendation should be developed for end-to-end resource (including software infrastructure) management and orchestration of future computing?
? What new Recommendation should be developed for data management and governance of future computing including but not limited to data analysis, data management, data preservation, data mobility management as well as lifecycle management of data?
? What new Recommendation should be developed for specific identity, access and security mechanisms that enable effortless trusted access to future computing?
? What collaboration is necessary to minimize duplication of efforts with other SDOs?
3 Tasks
Tasks include, but are not limited to:
? Developing Recommendations for overview, framework, high level and functional requirements and capabilities, data models, and application programming interfaces for end-to-end service management, orchestration, governance, and production operation of future computing, including but not limited to distributed/edge computing, inter-cloud computing, multi-cloud computing and cloud native related computing, on the aspects of maintenance, monitoring, measurement, scheduling, development and operations (DevOps) and continuous integration/continuous delivery (CI/CD), etc.
? Developing Recommendations for overview, framework, high level and functional requirements and capabilities, data models for end-to-end resource (including software infrastructure) management and orchestration of future computing.
? Developing Recommendations for data management and governance of future computing including but not limited to data analysis, data management, data preservation, data mobility management as well as lifecycle management of data.
? Developing Recommendations for specific identity, access and security mechanisms that enable effortless trusted access to future computing.
? Providing the necessary collaboration with external SDOs, consortia and forums working on future computing to minimize duplication of efforts.
? Maintaining and enhancing of the Recommendations for which the Question is responsible.
An up-to-date status of work under this Question is contained in the SG13 work programme: https://www.itu.int/ITU-T/workprog/wp_search.aspx?sp=18&q=19/13.
4 Relationships
Recommendations:
? Other relevant Y-series Recommendations, in particular in the Y.3500- and Y.3600-series
? Y-series and cloud computing and data handling related Recommendations in the M-, Q- and X-series Recommendations
Questions:
? Cloud computing and data handling related Questions
? Artificial intelligence and machine learning (AI/ML) related Questions
Study groups:
? ITU-T study groups and ITU-D study groups involved in cloud computing and data handling related studies
Other bodies:
? Artificial intelligence and machine learning (AI/ML) related ITU-T focus group
? Institute of Electrical and Electronics Engineers (IEEE)
? Internet Engineering Taks Force (IETF)
? International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) Joint Technical Committee (JTC) 1/Subcommittee (SC) 27, SC 38, SC 40 and SC 42
? Distributed Management Task Force (DMTF)
? Linux Foundation projects
? Metro Ethernet Forum (MEF)
? Storage Networking Industry Association (SNIA)
? TM Forum
? Organization for the Advancement of Structured Information Standard (OASIS)
? The 3rd Generation Partnership Project (3GPP)
? European Telecommunications Standards Institute (ETSI) including Industry Specification Group on Network Function Virtualization (ISG NFV), Industry Specification Group on Zero Touch Networks & Service Management (ISG ZSM), Industry Specification Group on Experienced Networked Intelligence (ISG ENI) and Industry Specification Group on Multi-access Edge Computing (ISG MEC)
? Cloud Security Alliance (CSA)
? World Wide Web Consortium (W3C)
? National Institutes of Standards and Technology (NIST)
? Open Computing Project (OCP)
? OpenInfra Foundation
WSIS Action Lines:
- C2, C3, C5
Sustainable Development Goals:
- 9
|
| Comment:
|
Continuation of Q19/13
|
|
Rapporteur:
| Ms. | Ying | CHENG |
|
Associate rapporteur:
| Mr. | Dae Won | KIM |
|
|
