Database Monitoring and Performance Tuning with Supported Diagnostics

Jakub Dunak

Abstract: This article focuses on database monitoring and performance tuning using supported diagnostic tools in Oracle and Microsoft SQL Server. The topic's relevance stems from the need to reduce the frequency of critical incidents and service recovery times while adhering to industry standards for IT service management. The novelty of the work lies in the analytical integration of DBMS telemetry (AWR/ASH/ADDM, Query Store/Intelligent Query Processing) with incident management processes and diagnostic platforms that use generative AI to accelerate the prototyping of fixes. The paper describes Oracle's diagnostic artifacts and the IQP mechanisms in SQL Server, examines their operational effects on MTTR and plan stability, and their connection with ITIL/ISO 20000 practices. Special attention is given to comparing the "observability" and "manageability" of incidents, as well as the role of LLM prompts in accelerating the "detection -> resolution" cycle. The work aims to develop practical recommendations for reducing incidents and speeding up recovery. To achieve this, comparative analysis, analytical generalization, and systematization of practices were applied. The conclusion describes the obtained effects and limitations of applicability. The article will be useful for architects, DBAs, and operations managers in industries with strict SLAs.

Keywords: database monitoring, performance diagnostics, Oracle AWR/ASH/ADDM, SQL Server IQP, Query Store

How to Cite?: Jakub Dunak, "Database Monitoring and Performance Tuning with Supported Diagnostics", Volume 14 Issue 11, November 2025, International Journal of Science and Research (IJSR), Pages: 264-268, https://www.ijsr.net/getabstract.php?paperid=SR251029165903, DOI: https://dx.doi.org/10.21275/SR251029165903