![Capture d’écran 2022-09-09 à 17.12.51.png](ecQA0TW9vnwU)

The [compute_resource_usage_logs](dataset:compute_resource_usage_logs) is the input folder containing all the compute resource usage logs that you want to monitor. Those logs come either from an event server or directly from the audit logs of your instance.
The [compute_logs_clean](recipe:compute_logs_clean) recipe makes sure that whatever the origin of the CRU logs, we get the same schema and only keep CRU-related rows.
The [compute_logs_normalized](recipe:compute_logs_normalized) recipe is used to clean the data and precompute the date at day, hour, and minute levels. It is done early in the flow so that we have the possibility to use SQL engines later on (the date parsing is not compatible with SQL recipes).
The next steps  are used to split the data into three main categories : 
1. [logs_local_process](dataset:logs_local_process) : contains all the logs related to processes executed with the "local stream" engine
2. [logs_sql_connection](dataset:logs_sql_connection) : contains all the logs related to processes executed with the "In Database (SQL)" engine
3. [logs_k8s](dataset:logs_k8s) : contains all the logs related to processes executed with Kubernetes support

Each of those categories will have a specific format of logs, therefore specific data preparation, in their dedicated flow zones : [Local resources](article:6), [SQL resources](article:7), [Kubernetes resources](article:8).

