Integrating with RMF 74.4 Coupling Facility Metrics
High volume Db2 data sharing groups are very dependent on responsive coupling facility performance, giving Db2 teams keen interest in coupling facility metrics such as service times and request and reclaim rates captured in the RMF 74.4 records.
Integrating with RMF 71 Memory and Large Frame Metrics
Since Db2 is typically the largest exploiter of memory in general as well as of 1 MB and 2 GB large frames, visibility into memory, paging, and large frame metrics from RMF 71 data is of particular interest to Db2 teams.
Integrating with RMF 70 and 72 CPU and WLM Metrics
Insights into Db2 operation are provided by RMF 70 data in areas such as CPU utilization and consumption at the processor and system levels. Several relevant areas are provided by RMF 72 data, including CPU consumption at the workload / service-class / report-class levels, WLM data relative to how service goals are being achieved and delays inhibiting that, and transaction metrics for DDF workloads which are often visible to WLM.
Integrating with RMF Metrics (70, 71, 72, 74)
Since Db2 interacts heavily with z/OS and other subsystems, “outside” perspectives provided by RMF metrics are essential to effectively manage Db2 operational health and performance.
Sample Dashboard of Db2 Statistics Metrics
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.
Exploring Assessments of Key Metrics
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.
Exploring Other Db2 Statistics 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
Measuring Benefits of Db2 Buffer Pool Tuning
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
Buffer Efficiency from IFCID 199 and SMF 42
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.