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AWS Introduces ‘Capabilities by Region’ to Streamline Cloud Deployment Planning

AWS has introduced a new planning tool called Capabilities by Region, designed to enhance the planning process for cloud deployments. This tool provides enterprises with critical visibility into the availability of AWS services, tools, and features across various global regions, mitigating the uncertainties often associated with cloud expansion plans.

One significant advantage of this tool is its ability to showcase whether specific services or features are slated for future implementation in certain regions. Such clarity is crucial for enterprises, as previously, they often encountered service gaps late in the deployment process, leading to costly delays and rework. Charlie Dai, a vice president and principal analyst at Forrester, emphasized that this new capability addresses these challenges by offering authoritative insights into service availability.

This feature sets AWS apart from its competitors. For instance, Microsoft Azure has a service availability portal, but it lacks the forward-looking timelines and comprehensive API comparability that AWS’s Capabilities by Region offers. Similarly, Google Cloud’s equivalent tool does not provide detailed, future-facing information, focusing instead on helping enterprises optimize costs and efficiency.

Analysts highlight that the misuse of cloud resources—due to lack of visibility into services—contributes to about 30% of cloud spending being wasted. Therefore, the Capabilities by Region tool not only streamlines planning processes but also aids enterprises in avoiding unnecessary expenses.

Interestingly, this tool is positioned outside the AWS Management Console, which is intentional to prevent disruption during live deployments. It provides a safe and accessible way for non-admins and partners to utilize without needing an AWS account. Moreover, all data within the Capabilities by Region is also accessible through the AWS Knowledge MCP Server, allowing developers to automate cloud planning and get insights for cloud deployments via generative AI assistants.


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