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Automated assessments of key Db2 metrics facilitate proactive analysis and prevention of outages by identifying areas that may warrant investigation. These views also expedite learning by highlighting metrics that are important to understand and analyze.

Automated assessments of key Db2 metrics facilitate proactive analysis and prevention of outages by identifying areas that may warrant investigation. These views also expedite learning by highlighting metrics that are important to understand and analyze.

How to approach measuring the benefits of buffer pool tuning initiatives, which are likely to be primarily realized in this small set of average elapsed time metrics

How to approach measuring the benefits of buffer pool tuning initiatives, which are likely to be primarily realized in this small set of average elapsed time metrics

Integrating IFCID 199 and SMF 42 data provides a view of buffer efficiency enabling buffer misses (I/Os) to be further subdivided into cache hits and misses, which can be leveraged to further refine buffer pool tuning methodologies.

This session suggests capabilities to keep in mind as you seek to modernize how you access and analyze your Db2 SMF data, both to promote rapid learning as well as boost the value you derive from your data.

Db2 IFCID 199 data provides buffer pool statistics at the dataset level. Integrating this with SMF 42 dataset I/O performance data provides extensive insights into I/O activity and response time data at the Db2 buffer pool and database levels.

Integrating IFCID 199 and SMF 42 data provides extensive insights into I/O cache characteristics and response time data at the Db2 buffer pool and Db2 database levels.