Page Comparison

The goal of this page is to document the design of the Tracker Audit Metrics.

Use-Cases

1. As a user of Tracker, I would like to see total number of audit messages by type/subtype in the past T timeframe.
   1. "Show me the total number of reads in the system in the past 1 hour."
2. As a user of Tracker, I would like to see the top N datasets/streams by audit message type/subtype activity in the past T timeframe.
   1. "Show me the 5 datasets with the most writes in the past 24 hours."
   2. "Show me the 5 streams with the most metadata_changes in the past 7 days."
3. As a user of Tracker, I would like to see the top N namespaces with the most type/subtype activity in the past T timeframe.
   1. "Show me the 5 namespaces witht he most reads in the past 1 hour."

Initial High Level Plan

• As messages come from the Kafka broker and are written to the AuditLog Table, when a message matches one of the metrics criteria, update metrics in a separate OLAP Cube (but the same dataset) as required.
• In the service layer, expose a new endpoint that allows users to query the data in the metrics table and returns the results in JSON.

Storing Metrics in AuditLog Dataset

• Add an additional Cube table to the AuditLog custom dataset to hold metrics.
• The properties of the cube will be as follows
  • Resolutions: 1h, 1d, 7d, 30d
  • Aggs: 
    • access_type
    • access_type,subtype
    • namespace
    • namespace,entity_type,entity_name
  • Measurements: accesses, access_reads, access_writes, access_unknowns, creates, updates, truncates, deletes, metadata_changes