Create total count metric type that supports time frames

Background

Currently we offer two ways of counting with Redis (RedisMetric and RedisHLL).

They behave a bit different as outlined here

	Redis	RedisHLL
Counts	Total number of invocations	Number of distinct arguments passed
Time frames reported	All time	7d, 28d
Precision	Accurate	Probabilistic
Memory footprint per metric	Few 100 bytes	Up to 12kB x 29

(The memory footprint is an over-approximation and we might have to look at the actual usage)

We have experienced (example 1) that our users sometimes want to count the total number of times an event happen with a time frame.

Two examples are:

• Number of pipelines created (7d and 28d)
• Number of merge requests created (7d and 28d)

Currently they have two options:

1. Use a Redis metric and calculate the time framed values in the data warehouse - which is error prone.
2. Use a RedisHLL metric and always pass a unique number - ex. pass the id of a merge request when they want to count how many merge requests were created. (It works because a merge request only is created once). redis_hll_counters.code_review.i_code_review_create_mr_monthly and it's weekly metric cousin are an example for doing this.

Desired Outcome

1. Users can use 7d and 28d timeframes together with total count metrics when using data_source: internal_events.
2. 7d and 28d version of https://gitlab.com/gitlab-org/gitlab/blob/master/ee/config/metrics/counts_all/20230502122452_analytics_dashboard_views.yml is created

Suggested Solution

Based on the suggestion and POC code in #411264 (comment 1392077260) we suggest to use Redis as a storage solution for this. The outcome are these steps:

• The logic to generate keys for event storage should be refactored for general usage in both Redis and RedisHLL within #415046 (closed)
• Add usage of the refactored logic to the way we handle events with Redis
• enable time_frame: 7d / 28d for data_source: events

NOT IN SCOPE: We do not intend to add the availability of those time_frames to the legacy metrics using data_source: redis, however if this is an unintended side-effect, we also do not have to go though extra steps to prevent them from being added.