Key metrics for monitoring Pivotal Platform

In part two of this three-part series on monitoring your Pivotal Platform deployment, we will take a closer look at some key metrics that can provide insight into the performance and health of various components within the platform. We will cover metrics related to the Cloud Controller, Diego, BBS, Locket, Cells/Rep, Route-Emitter, and Loggregator. The following are some of the most important Pivotal Platform metrics for monitoring component availability, utilization, and performance: |Component |Metric Name |Description |Metric type |Cloud Controller |ccdb.indexingPassesCompleted |Total number of indexing passes completed by the Cloud Controller database |Work: Performance |ccdb.indexingPassDuration |Average time (in nanoseconds) for an indexing pass to complete in the Cloud Controller database |Work: Performance |Diego |diego.cellsTotal |Total number of Diego cells registered with the BBS |Other |diego.tasksRunningTotal |Total number of tasks currently running on all Diego cells |Resource: Utilization |diego.lrpInstancesRunningTotal |Total number of LRP instances currently running on all Diego cells |Resource: Utilization |Auctioneer |auctioneer.LRPAuctionsStarted |Number of times the Auctioneer has started an auction for placing LRPs on cells |Work: Performance |auctioneer.TaskAuctionsStarted |Number of times the Auctioneer has started an auction for placing tasks on cells |Work: Performance |BBS |bbs.convergenceLRPDuration |Total time (in nanoseconds) that the BBS takes to run a convergence pass |Work: Performance |Locket |locket.<component>.LockHeld |Indicates whether a component lock is held; returns 1 if held, 0 if not |Other |cell.Rep |rep.ActivePresencesTotal |Total number of active cell presences registered with the BBS |Resource: Availability |Loggregator |doppler.dropped |The lifetime number of messages dropped by the Doppler without being delivered to a downstream component |Resource: Saturation These metrics provide insight into the overall health and performance of your Pivotal Platform deployment, as well as the status of individual components within that deployment. By monitoring these metrics, you can gain valuable information about how effectively your platform is operating and whether it needs scaling up or other adjustments to ensure optimal performance for developers and end users. In part three of this series, we will demonstrate several methods of collecting Pivotal Platform metrics and logs. We will cover both how to tap the Firehose stream of deployment metrics and application logs, and how to utilize a syslog drain to view component system logs.