Released: March 2018
This release provides a number of updates to improve visibility into the data that informs the calculations used in Capacity Planner. It also provides two new tabs on the interface, one that summarises cluster capacity and redundancy levels and another that provides the user with the facility to change the metric measures being used in calculations. Finally, a new report has been created that allows for detailed RAG status reports to be generated based on historic data and statistical measures, filtered by entities such as Cluster and VM Drives, or ‘groupings’, such as ‘Application’ and ‘Service’.
These are the highlights of this release:
- Models panel — the model panel was added to Capacity Planner.
- Clusters panel — the panel now provides a summary of all clusters shown in the current active baseline view.
- Time series available from headroom charts — the time series for each metric is now available directly from the headroom chart.
- 5 minute average data in metrics explorer — the metrics explorer now has a new option per metric to view 5 minute grain data.
- Entity baseline report — a new report was added allowing the user to summarise utilisation over any time period that has been modelled.
This tab allows the user to change the measure used in sunburst calculations. When first opened, it will use the default measures for each metric that can be configured.
The above example shows the contents of the Model tab with a number of metric configuration options. The user can select the drop down for each metric and pick the measure to be used from the following options:
- 5th Percentile
- 25th Percentile
- 75th Percentile
- 95th Percentile
- 99th Percentile
- Latest Value
Once the appropriate measures have been selected, click ‘Apply changes’ to update the sunburst. At this point, all features in the sunburst that use a summary metric (for example, the Headroomm dialog and the Demand Profile dialog) will update to use the selected measure.
This configuration will be saved with the baseline view. Note that it is not possible to change the measure settings within a Forward Thinking scenario. In order to model based on a non-default measure, please create a new view and then use that view when opening a new Forward Thinking scenario.
The clusters tab on the right hand side of the UI now provides a summary of all clusters shown in the current active baseline view. It will provide insight into how many redundant hosts are within that cluster and VM capacity to either HA policy or full cluster saturation.
Each row of the table represents a cluster present in the view. The columns are as follows:
|Policy breach warning||Should a cluster be in breach of HA policy, a warning icon wil be shown in this column.|
|Name||The name of the cluster.|
|N+x||The HA policy currently configured for that cluster. A value of 1 indicates that the cluster is expected to have a HA policy of N+1. This is default to 1 and can be changed by contacting your Capacity Planner representative.|
|VMH to HA||The number of reference workloads that can be added to this cluster before the redundancy policy is breached. This is based on the selected calculation metrics configured using the VM Headroom tab.|
|VMH to saturation||The number of reference workloads that can be added to this cluster before reaching full saturation. By default, saturation is considered to be full capacit minus the operational reserve. For CPU, the default reserve is 20% and for active memory, 40%.|
|Menu options||When a ros is highlighted, an icon will appear providing access to menu options for this cluster. 'Headroom' will open the headroom summary for that cluster, 'jump to' will orientate the sunburst to focus on this cluster.|
It is also possible to export a summary of all clusters shown in the table to CSV using the ‘Export to CSV’ option provided at the bottom left of the tab.
The time series for each metric is now available directly from the headroom chart. At a host and VM level, the user has the facility to open to the box-plot summary or time series. At a cluster level, only raw time series data will be available.
The timeseries will show all data for the entirety of the baseline at a 5 minute-average granularity.
The measure used for headroom calculations, as defined in the ‘models’ tab, will also be shown on this chart. In the above chart, the 95th %ile value for CPU on this VM is shown as a green line. All timeseries charts open in this way.
The following screenshot is an example of timeseries data at a cluster level. In this chart, the HA redundancy thresholds are shown as well as the current configured measure as defined by in the ‘models’ tab.
The metrics explorer now has a new option per metric to view 5 minute grain data. This is available from the metrics selection and configuration dialog as shown below:
This is an extremely flexible and powerful report, allowing the user to summarise utilisation over any time period that has been modelled create a RAG report indicating where any breaches may have occurred. The report offers 3 levels of filtering:
|Time frame||A summary of all data in the baseline.|
|Level 1 Entity Type||The first level filter to search against. Typically Cluster, Host, VM or Datastore|
|Grouping Filter ||The grouping filter to use to identify entities used in the level 1 entity type field.|
|Grouping Value ||The value to apply to grouping filter .|
|Level 1 Entity Name||Checkboxes to select the entities that map the level 1 filter to run the report against.|
|Level 2 Entity Type||The first level filter to search against. Typically Cluster, Host, VM or Datastore.|
|Grouping Filter ||The grouping filter to use to identify entities used in the level 2 entity type field.|
|Grouping Value ||The value to apply to grouping filter .|
|Level 2 Entity Name||Checkboxes to select the entities that map the level 1 filter to run the report against.|
|Level 3 Entity Type||The first level filter to search against. Typically Cluster, Host, VM or Datastore.|
|Grouping Filter ||The grouping filter to use to identify entities used in the level 3 entity type field.|
|Level 3 Entity Name||Checkboxes to select the entities that map the level 1 filter to run the report against.|
|Grouping Value ||The value to apply to grouping filter |
|Metric||The metric to report on.|
|Red Threshold||The threshold to use to indicate a Red RAG status.|
|Amber Threshold||The threshold to use to indicate an Amber RAG status.|
|Summary level||The type of model to base the report on. Baseline summary will threshold against a summary of all data over the entire baseline. Daily summary will threshold against summaries of each day in the baseline. Hourly Average will threshold against an hourly average time series. Unaggregated data will threshold against the raw time series data. Note, it is advised that this option is used only for small time period as it can significantly increase the query reponse and browser rendering times.|
|Chart Type||The type of plot to draw, either boxplots or time series or a combination of both if available.|
|Percentile/Value||The measure to use for thresholding using summary data.|
|Display data from||The start date for the query.|
|Display data to||The end date for the query.|
|X Axis Scale||Scale to fit, or show 0-100. The later option being useful when comparing percentage metrics.|
For example, the following query will show report on the drives of all powered on SQL VMs and indicate red for any drive that has been above 90% and amber for any drive that has been above 70% between 20th July 2017 and 11th Octoer 2017.
Please note, depending on the size of the estate that the query is being run against the the volume of data in the query, reports of this nature can take a significant time to generate.
This report filter will find all JBoss VMs of the Mobile application and indicate an amber status if memory utilisation was >50% between 17th August and 19th September.
The following image gives an example output from the previous query.
Click the links below to view other versions of Capacity Planner release notes.
|Capacity Planner Release Notes 105||Released: June 2020|
|Capacity Planner Release Notes 104||Released: February 2020|
|Capacity Planner Release Notes 103||Released: December 2019|
|Capacity Planner Release Notes 102||Released: October 2019|
|Capacity Planner Release Notes 101||Released: August 2019|
|Capacity Planner Release Notes 100||Released: May 2019|
|Capacity Planner Release Notes 99.2||Released: March 2019|
|Capacity Planner Release Notes 99||Released: December 2018|
|Capacity Planner Release Notes 95||Released: May 2018|
|Capacity Planner Release Notes 94||Released: March 2018|
|Capacity Planner Release Notes 93||Released: January 2018|
|Capacity Planner Release Notes 92||Released: December 2017|
|Capacity Planner Release Notes 91||Released: October 2017|
|Capacity Planner Release Notes 90||Released: September 2017|