In the production Oracle environment, it is essential to change AWR retention and performance data snapshot collection frequency from 1-hour to 15 minutes. Our F500 major clients use 15 minutes with no impact on production performance. Having 15 minutes of data snapshots vs. 1 hour dramatically increases the ability to troubleshoot. Also, AWR data contains ASH information collected from memory. Switch to 15 minutes collection intervals dramatically improves the quality of ASH information.
Two weeks is the default period of retention. At least four months of AWR data is required in a production context compared to four months of monthly seasonal data. Compare one month from the current quarter to the same month from the previous quarter. As a result, storing new gigabytes of AWR data is not a budgetary issue. Also, we strongly suggest keeping 13 months of data to investigate annual seasonality.
Below command switches AWR to 4 months (172800 minutes) data retention and 15 minutes collection frequency.
exec DBMS_WORKLOAD_REPOSITORY.modify_snapshot_settings(retention => 172800,interval => 15);
Overall, keeping several years of AWR performance data for capacity planning and predictive analytics employing advanced machine learning technologies to discover and predict mid-and long-term performance trends and probable “Black-Swan” events. Events that have the potential to dramatically and catastrophically impair the production environment will hold.
For these purposes, Oracle introduced The Enterprise Manager AWR Warehouse. As a result, Enteros UpBeat fully supports database performance analysis across AWR Warehouses and individual production database systems.
Enteros’ expert team has deep expertise in predictive analytics on database performance data. Contact us at support@enteros.com, and we will gladly discuss how our experts can create machine and deep learning models to predict the performance of your critical database systems.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
How to Drive Intelligent Cloud Governance with Enteros Database Management Platform and AIOps
- 22 May 2026
- Database Performance Management
Introduction Cloud computing has become the foundation of modern digital transformation. Organizations across industries increasingly rely on cloud-native infrastructures, distributed applications, AI-driven services, and real-time analytics platforms to support innovation, scalability, and operational agility. Today’s enterprises operate highly complex cloud ecosystems that support: Business-critical applications Database environments Customer engagement platforms AI and machine learning workloads … Continue reading “How to Drive Intelligent Cloud Governance with Enteros Database Management Platform and AIOps”
How to Enhance Media Growth Strategies with Enteros Generative AI and Cost Management Analytics
Introduction The media industry is undergoing rapid transformation as organizations embrace digital platforms, cloud-native infrastructures, streaming technologies, AI-driven content strategies, and real-time audience analytics. Modern media companies must manage increasingly complex operational ecosystems while delivering personalized, high-quality experiences across multiple digital channels. Today’s media organizations rely heavily on digital technologies to support: Streaming platforms Content … Continue reading “How to Enhance Media Growth Strategies with Enteros Generative AI and Cost Management Analytics”
Enhancing Digital Banking Performance and Scalability with AI-Driven Database Analytics
- 21 May 2026
- Database Performance Management
Introduction Digital banking has transformed the global financial landscape. Customers now expect instant account access, real-time transactions, personalized financial services, and seamless digital experiences across mobile and web platforms. To meet these expectations, banks and financial institutions rely heavily on high-performance data infrastructure powered by complex database environments. Every digital banking operation—whether it involves payments, … Continue reading “Enhancing Digital Banking Performance and Scalability with AI-Driven Database Analytics”
How Intelligent Database Analytics Improves Performance and Reliability in Modern Healthcare Platforms
Introduction Healthcare organizations today operate in an increasingly data-driven environment. Hospitals, clinics, diagnostic centers, telemedicine platforms, and healthcare networks rely heavily on digital systems to manage patient records, medical imaging, billing systems, analytics platforms, and clinical workflows. At the center of these operations lies a complex healthcare data infrastructure powered by databases. These databases process … Continue reading “How Intelligent Database Analytics Improves Performance and Reliability in Modern Healthcare Platforms”