What's New in Capacity Planner

Overview

This page contains the list of all highlights that have been introduced for each Geneos release.

For detailed release notes for all versions of Capacity Planner, see Release Notes.

Capacity Planner v101

Released: August 2019

For detailed release notes, see Capacity Planner Release Notes 101.

Groupings Manager

The Groupings Manager allows you to create, delete, and modify any grouping values directly from the sunburst avoiding the need to provide a CSV file.

Note: It is often the case that grouping values are provided via a regular data upload. If a grouping that is provided in such a way is modified or deleted using the grouping manager, it will be reinstated to the original value upon the next successful data processing.

For more information, see Groupings Manager documentation.

Capacity Planner v100

Released: May 2019

For detailed release notes, see Capacity Planner Release Notes 100.

Highlights

These are the highlights in this release:

  • Cluster headroom — drive time series information can now be viewed from the headroom dialog window.
  • Residuals — the residuals can now be visualized using reports.
  • Reports — improvements were introduced in the following advanced reports:
    • Metric analysis — multi-chart
    • Metric analysis — single-chart
Click here to view more information about the highlights for Capacity Planner v100
Cluster headroom

Drive time series information can now be viewed from the headroom dialog window. A new tab is displayed in the lower half of the dialog window. The menu options for each drive allow you to view the time series data for that drive utilisation.

For more information, see Headroom.

Residuals

A residual workload is one that represents work that the server is doing that is not captured by a monitoring tool and not reflected in the sunburst visualization. It is particularly important when modelling purely physical environments and multi-process applications. In this case, the sunburst will show servers and workloads representing processes running on that server. However, there may be a difference between the perceived activity of the server and the combined activity of the processes. This difference is known as the residual. The residual is not shown or accessible directly via the sunburst but can be visualized using reports.

High values of residual activity indicate that monitoring is not necessarily sufficient to capture workload on a server.

Reports

Metric analysis — multi-chart report has been enhanced to allow for further visualisations with a single chart presented per selected entity type (for example VM, cluster, host or drive). Two of these (Linear Trend and Scatter Plots) calculate linear regression lines and associated intercept, gradient and R2 values.

For more information, see Metric analysis — multi-chart in Available Reports.

Bar chart and treemap visualisation were added to the Metric analysis — single-chart.

For more information, see Metric analysis — single-chart in Available Reports.

Capacity Planner v99

Released: December 2018

For detailed release notes, see Capacity Planner Release Notes 99.

Highlights

These are the highlights in this release:

  • Single Sign On — SSO support using SAML 2.0 was added.
  • Reports — a number of enhancements were introduced to the reports. The reports were also redesigned.
  • Benchmarking — a more automated process has been put in place to apply benchmarking scores to servers as they are discovered.
Click here to view more information about the highlights for Capacity Planner v99
Single Sign On Single Sign On allows the user authentication to be validated within your organisation using SAML 2.0. When used, allows you to log in to Capacity Planner using your existing SSO credentials that are used for other applications across your organisation. There is no need to register with Capacity Planner to make use of this option. When you successfully authenticate, you can start using Capacity Planner straight away
Reports

Prior to this release, there were a number of reports, many of which performed the same reporting activity, but simply on a different type of device or managed entity. Also, the configuration of input parameters for some reports were not as flexible as others. For example, some reports may allow you to run over a chose time frame as identified by a user defined baseline, while others would not.

Several changes have been made to the standard set of reports to firstly reduce the amount of reports available but make those reports more flexible and powerful.

   

Capacity Planner v95

Released: May 2018

For detailed release notes, see Capacity Planner Release Notes 95.

Highlights

These are the highlights in this release:

Click here to view more information about the highlights for Capacity Planner v95
Viewing different models The models tab has been enhanced to allow the user to select from multiple available models. A model is a summary of a given time frame. For example, a summary of a particular week, day or month, or perhaps a summary of working hours only.
Workload summary

On the right click menu, under the ‘workloads’ sub-menu, a new ‘Workload summary’ option is available. This will present a summary of all metrics on all workloads from the segment that was selected in the hierarchy. It will present each metric, the number of VMs from that point of the hierarchy downwards, the measure being used for that metric in the current model, the number of workloads that have that metric and then the sum and average for that metric. The following is an example where a small subset of workloads in an estate have specific application metrics configured.

Excluding metrics from migrations You can now exclude metrics from any scenario operation that involves the movement of workloads (for example, cluster redistribution or migration). This is particularly useful when memory.consumed.average is used in a VMWare environment. This metric can often over-state the use of memory for particular applications and the user may wish to optimise a cluster estate while ignoring the aggregate consumed memory. The following in an example of a redistribution operation using minimum number of hosts within a cluster and ignoring the memory.consumed.average metric.
Setting demand

Until now, users have had the facilty to ‘add demand’ to workloads that will effectively ‘inflate’ the demand of a metric by a chosen absolute value or percentage. This release introduces the facility to specifically set demand for a workload. This can be particularly useful when modelling a greenfield site where hardware configuration and average VM configuration is known, but no demand profile information is available. Another area where this can be useful is in the modelling of scenario when all provisioned VMs use the resources they have been provisioned, and demonstrating that capacity in a cluster may not be sufficient to support this demand.

This menu item is available in the scenario modelling right click menu and will apply to all workloads. It is currently restricted to CPU, Memory and shared and local storage. The following is an example of setting all metrics of VMs to 50%.

Capacity Planner v94

Released: March 2018

For detailed release notes, see Capacity Planner Release Notes 94.

Highlights

These are the highlights in this release:

Click here to view more information about the highlights for Capacity Planner v94
Models panel 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.
Clusters panel 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.
Time series available from headroom charts 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.
5 minute average data in metrics explorer

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.

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Entity baseline report 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.

Capacity Planner v93

Released: January 2018

For detailed release notes, see Capacity Planner Release Notes 93.

Highlights

These are the highlights in this release:

  • Capacity events — a new event processing algorithm has been introduced to provide more accuracy and mine further different trends from utilisation patterns.
Click here to view more information about the highlights for Capacity Planner v93
Capacity events A new event processing algorithm has been introduced to provide more accuracy and mine further different trends from utilisation patterns. This algorithm is applied across all metrics that are ingested by Capacity Planner.

Capacity Planner v92

Released: December 2017

For detailed release notes, see Capacity Planner Release Notes 92.

Highlights

These are the highlights in this release:

  • Cluster trends report — a new report was added to the advanced reporting.
  • VMs on the watch list — VMs that currently, as of the latest processing of the model, do not have enough capacity to meet their 95th percentile are indicated on the sunburst with the red circle.
Click here to view more information about the highlights for Capacity Planner v92
Cluster trends report Cluster trends report was added. The report provides information on how often this cluster event has been raised and at which severity. In the above example, the first cluster event has been raised 22 times in the last 30 days for each level of redundancy threshold crossing.
VMs on the watch list When you next open the baseline, you may see some VMs with a red circle around them. These are VMs that currently, as of the latest processing of the model, do not have enough capacity to meet their 95th percentile demand value over the last 3 months. In other words, in the last 3 months, the CPU demand of these VMs has been higher than what the VM is currently capable of supporting. This can also be seen within the metrics explorer.

Capacity Planner v91

Released: October 2017

For detailed release notes, see Capacity Planner Release Notes 91.

Highlights

These are the highlights in this release:

Click here to view more information about the highlights for Capacity Planner v91
Right-sizing with measures Different workloads must be optimised and right-sized based on different measures depending on the behaviour profile of that workload. The approach so far in Capacity Planner has been to use the 95th percentile for CPU right-sizing and the 99th percentile for memory right-sizing. Allocating enough resources to accommodate that demand while leaving a 20% growth buffer for unexpected peaks. For some VMs, this is not sufficient. There are machines that lie dormant for long periods of time and have very short high CPU spikes. As a result, it may be more appropriate to base the right-sizing of this on CPU peak rather than 95th percentile
VM storage summary report A VM storage summary report has been added to the default list of standard reports. This report is aimed at identifying potential wastage in environment particularly when thick provisioning is used. It will compare the total allocated VMDK storage or virtual disk storage for a VM with the total drive utilisation and determine the difference in allocation vs demand. It will order, by default, on free VMDK space, from largest to smallest.

Capacity Planner v90

Released: September 2017

For detailed release notes, see Capacity Planner Release Notes 90.

Highlights

These are the highlights in this release:

Click here to view more information about the highlights for Capacity Planner v90
Cluster high availability policies It is often desirable, depending on the appetite for risk within the environment, to ensure that a number of devices within a cluster are redundant. That is, should these devices fail, there is still capacity in a cluster to ensure continued operation of the machines in that cluster. Redundancy is normally expressed in the form of N+x, where ‘x’ is the number of backup components required. In the case of virtualisation clusters, N is the number of devices needed to support the demand within the cluster adequately, and ‘x’ refers to the number of additional hosts. Therefore, when a cluster has a ‘high availability’ policy of ‘N+2’, it can withstand the failure of 2 hosts and still have sufficient capacity to support the aggregate workload of all the virtual machines in that cluster.
Number of redundant servers

A new feature has been added to the Headroom Summary available from the right click menu at any point of the sunburst.

For each metric being used in headroom calculations, Capacity Planner will determine the cut-over points for server redundancy. The following is an example of a cluster level headroom summary for CPU utilisation.

Long term cluster trends

A new event type has been introduced showing long term trends towards cluster capacity. They are available in a new tab in the events dialog window.

As with all events, they are ordered chronologically by default. Each event will indicate when a cluster will have less than 2 redundant servers (<N+2), less than 1 redundant server (<N+1) or cluster saturation. This is when the demand in the cluster will reach the current operational capacity of the cluster (total capacity – reserve headroom %age).

As with all events, the time-series will show the current demand and the forecast trend to the point where the threshold is crossed