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Boost your query performance for mission critical workloads using the new AI-powered Db2 Query Optimizer. It can help your business to harness the power of AI directly within your database…

Streamline database management with our AI-powered chatbot, designed to help DBAs like you resolve issues quickly, manage growing environments efficiently, and get new team members up to speed…

This video demonstrates how to navigate the process of creating views using IntelliMagic Vision for z/OS.

Effective exploitation of Buffer Pools is essential to achieving good Db2 performance, so it is key to effectively monitor Db2 buffer pool data.

This video demonstrates using Db2 IFCID 199 and SMF 42 data to gauge Db2 GETPAGE efficiency, showing percentages for buffer pool hits, disk cache hits, and actual disk I/Os.

IFCID 199 and SMF 42 data integration offers insights into buffer efficiency, breaking down buffer misses into cache hits and misses. This helps refine buffer pool tuning methods.

A brief introduction to some of the “other” (non-buffer pool related) metrics available in Db2 Statistics data

Automated assessments of key Db2 metrics aid proactive analysis, preventing outages by pinpointing areas needing investigation and highlighting crucial metrics for analysis.

High-volume Db2 data sharing groups rely on responsive coupling facility performance, so Db2 teams closely monitor RMF 74.4 metrics like service times and request/reclaim rates.

Db2 teams are particularly interested in RMF 71 data for memory, paging, and large frame metrics, as Db2 is a major memory user, including 1 MB and 2 GB large frames.

RMF 70 data reveals Db2 CPU usage at processor and system levels. RMF 72 data covers CPU consumption by workload, service class, report class, WLM service goals, delays, and DDF transaction metrics.

Easy accessibility to key Db2 buffer metrics enhances buffer pool tuning analyses so that they can be quickly completed. This video explores key metrics for one buffer pool tuning methodology.

Access easy visibility into key Db2 metrics through SMF records to proactively prevent availability risks and effectively manage and optimize performance.

This video demonstrates correlating Db2 and CICS data to identify transactions with high CPU usage in Db2, including details such as transaction rate, CPU per transaction, and SQL calls.

This video shows how viewing CICS Call Attach work by Correlation ID enables both CICS and Db2 teams to view elapsed time profiles within Db2 corresponding to each CICS transaction ID.

Learn how a US retailer built an interactive AI assistant using watsonx Assistant, Db2 for real-time product catalog information, and NeuralSeek, a no-code gen AI integration platform.