Cloudwatch Logs: customize time range for "Load more"

via IDE feedback:

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Hi there!

I was trying to use AWS Toolkit for Visual Studio Code to look up CloudWatch logstream with 1-week range of logs data. I was hoping this will provide me more intuitive and easier experience to export that much logs and save them to disk than using AWS CloudWatch Console (in web). However, I was quickly disappointed to see that I can only load CloudWatch logstream with 1h increments (pagination default in AWS Toolkit for VS Code).

I am struggling to quickly get 1-week range of logs exported so I can attach it to the support case we have open with another 3rd-party service (MongoDB Cloud Health Manager). So at this point, both AWS CloudWatch Console (web) and AWS Toolkit for VSCode have failed me in this task.

It would be really beneficial and good feature if you could add settings to the AWS Toolkit (VSCode plugin) that allows users to configure the pagination ranges when grabbing CloudWatch logstream data. For example, in my task, I wouldn't mind doing 7 clicks to load more logs if I was able to get 1-day range of logs loaded with each click. However, without this setting being available as configuration option of the AWS Toolkit and with default being 1h range of logs, I would need to do 24x7 clicks and wait in between each. Additionally, I have to do this for 3 nodes of the distributed cluster (replica group) so I would have to do this 3x7x24 times, which is not pleasant experience. I am going to look at the AWS CLI APIs next for CloudWatch and see if that can be of more help, but I wanted to let you know that this would be nice configurable option in AWS Toolkit as well.

The issue concerns CloudWatch logstream pagination in the AWS Toolkit for VS Code, but it names no files, tests, or entry points. Start by locating the logstream loading flow and its one-hour pagination default, then determine how a configurable range should affect “Load more” and verify that users can retrieve longer ranges with fewer clicks.

Written by the indexing model from the issue text.