Intelligent query performance analysis system for fleet of multi-tenant database servers

At least one non-transitory machine-readable storage medium that provides instructions that, when executed by at least one processor, are configurable to cause the at least one processor to perform operations comprising;

• receiving queries from at least one database server into an ingestion pipeline within a computing device, wherein keywords are extracted from the queries at multiple intervals;
• applying tokenization in the ingestion pipeline to remove uninformative terms when attempting to extract keywords from the queries;
• detecting at least one query from the received set of queries that are resource intensive at a fleet level, individual server level, or user level based on the keywords and using an enrichment analysis module, wherein the at least one query detected to be resource intensive is given a drill-down analysis to capture insights from execution profiles, wherein the enrichment analysis module performs a historical statistical analysis to detect, flag, and categorize each query and identifies which queries with a cpu footprint and execution time that have breached a configuration threshold and a drill down analysis to identify a cpu projection trend and average cpu time per execution;
• and
• providing alerts based on the at least one query detected to be resource intensive.

A computing device comprising:

• at least one non-transitory machine-readable storage medium that stores software for a dynamic localization service;
• and
• at least one processor, coupled to the at least one non-transitory machine-readable storage medium, to execute the software that implements the dynamic localization service and that is configurable to:
• receive queries from at least one database server into an ingestion pipeline, wherein keywords are extracted from the queries at multiple intervals;
• apply tokenization in the ingestion pipeline to remove uninformative terms when attempting to extract keywords from the queries;
• detect at least one query from the received set of queries that are resource intensive at a fleet level, individual server level, or user level based on the keywords and using an enrichment analysis module, wherein the at least one query detected to be resource intensive is given a drill-down analysis to capture insights from execution profiles, wherein the enrichment analysis module performs a historical statistical analysis to detect, flag, and categorize each query and identifies which queries with a computer processing unit (cpu) footprint and execution time that have breached a configuration threshold and a drill down analysis to identify a cpu projection trend and average cpu time per execution;
• and
• provide alerts based on the at least one query detected to be resource intensive.