AWS prescriptive-guidance documentation change
Summary
Updated wording for clarity: added 'plan' to business case description, specified 'additional' for data collection, and changed tooling process timeframe from 'weeks or months' to 'weeks'.
Security assessment
Changes are editorial improvements without addressing vulnerabilities or security mechanisms. Mention of 'security' in procurement processes is incidental to migration planning timelines, not security documentation.
Diff
diff --git a/prescriptive-guidance/latest/application-portfolio-assessment-guide/initiating-data-collection.md b/prescriptive-guidance/latest/application-portfolio-assessment-guide/initiating-data-collection.md index 06e9e5d01..a29030297 100644 --- a//prescriptive-guidance/latest/application-portfolio-assessment-guide/initiating-data-collection.md +++ b//prescriptive-guidance/latest/application-portfolio-assessment-guide/initiating-data-collection.md @@ -9 +9 @@ -Data collection is the process of gathering metadata from applications and infrastructure. The process is iterative throughout all stages of assessment. In each stage, data quantity and fidelity will increase. At this stage, the focus is on gathering general data that can help to establish an initial inventory. The inventory will be used to create a directional business case and the identification of initial migration candidates. +Data collection is the process of gathering metadata from applications and infrastructure. The process is iterative throughout all stages of assessment. In each stage, data quantity and fidelity will increase. At this stage, the focus is on gathering general data that can help to establish an initial inventory. The inventory will be used to create a directional business case and plan, and it will be used to identify initial migration candidates. @@ -13 +13 @@ After the current data sources have been identified, we recommend gathering info -This approach has the benefit of helping to update the current portfolio view and the organization's knowledge of their applications and services. It also helps with determining what is targeted to move. The recommended approach is to review existing data, such as configuration management database (CMDB) outputs and information technology service management (ITSM) systems. Then construct a list of assets targeted for data collection. If your organization has complete clarity of what is in scope and out of scope for the migration, you might restrict data collection to the systems that are in scope. +This approach has the benefit of helping to update the current portfolio view and the organization's knowledge of their applications and services. It also helps with determining what is targeted to move. The recommended approach is to review existing data, such as configuration management database (CMDB) outputs and information technology service management (ITSM) systems. Then construct a list of assets targeted for additional data collection. If your organization has complete clarity of what is in scope and out of scope for the migration, you might restrict data collection to the systems that are in scope. @@ -21 +21 @@ Note that the initial output, when combining existing data sources, could be inc -The gap analysis helps you understand the quantity and quality of data you are working with. The analysis also helps you to establish the level of assumptions that must be made to create a directional business case and prioritize applications for migration. Discovery tooling can help to fill the gaps and collect high-fidelity data. To increase the confidence levels in data and accelerate migration outcomes, we recommend deploying discovery tooling as early as possible. Early action is also important because internal procurement, security, and implementation processes for new tools could require several weeks or months to complete. +The gap analysis helps you understand the quantity and quality of data you are working with. The analysis also helps you to establish the level of assumptions that must be made to create a directional business case and prioritize applications for migration. Discovery tooling can help to fill the gaps and collect high-fidelity data. To increase the confidence levels in data and accelerate migration outcomes, we recommend deploying discovery tooling as early as possible. Early action is also important because internal procurement, security, and implementation processes for new tools could require several weeks to complete.