Feature Detailed Plots

The Feature Detailed Plots page is an aggregation of several graphical depictions of availability and utilization statistics. These graphs show usage at any given point over a year and provide visual cues for determining license usage.

Feature Detailed graphs show availability and utilization statistics. They are controlled using the options box on the left-hand side of the page. Specifically, they show three graphs:
  • Checkout Count and Duration: This shows a breakdown of the utilization of the specified feature(s) per user, host, project or custom group.
  • Detailed: This shows the capacity of the specified feature, usage details and the usage average.
  • Denials: If denials exist for the specified feature, they will be shown in the denial plot.

Figure 1. Feature Detailed Plots Page

Checkout Count and Duration Graphs

This pie chart provides a visual cue for the number of checkouts and the duration.

Figure 2. Feature Detailed Pie Charts – Checkout Count & Checkout Duration
  • Checkout count: This shows the percent of checkouts per user or per host for the group.
  • Checkout duration: This shows the duration of checkouts per user or per host for the group.
  • Denial count: This shows the percent of the denials per user or per host for the group.

In this example, the pie charts show that “Christopher” used most of these two features, and he is responsible for most of the duration and the denial count. Christopher might be a super user, or he might represent a generic account that is used by many people. This presents an opportunity for further investigation.

Feature Detailed Plot

This graph provides a visual cue for determining whether you need more or fewer licenses.

Figure 3. Detailed Plot – Tokens Used

Tokens Used are transposed with your maximum capacity and the average capacity daily.

This shows the usage for the give time frame for each breakdown.
  • Dark blue is utilized
  • Light blue is how much is exactly used, capacity.

This example shows a proper balance of tokens used and tokens queued.

Denials Plot

If denials exist for the specified feature(s), they will be shown at the bottom of the page in the denial plot. The plot shows a thin red bar that indicates the number of denials detected for each second throughout the specified time period.

Figure 4. Denials Plot

You can limit the scope of the reports on the page to specific tags, features, users, hosts, and projects.

In this example, each vertical bar represents five minutes, (this can be set to a different time parameter). This plot covers the second quarter. It shows 7 to 8 denials as the maximum, which is not too many. If there were no denials, you might be wasting money. But in this case, there is neither too many more too few denials; this is a sweet spot.

Usage Comparison Plot

This graph simplifies the complex reports generated by checkout statistics page.

Figure 5.

This graph accompanies the checkout statistics page, which has complex report-by and filter options. This plot compares the utilization average over time, broken down by the selected option. You can choose different teams, departments, tags, users or groups. It shows which is used the most and which is used the least, and this gives you an idea of how to distribute resources and when to distribute them.

This example plot specifically shows the overall usage of the two features – MATLAB and Calibre – MATLAB gets more use than Calibre, during the second quarter of the year.

As a general rule, the stacked view option can be used when a graphical view of the total usage is desired. For example, in an environment where there are two different synthesis tools available and a report is needed that shows the total synthesis usage while also showing how each tool's usage varies over time, the stacked view would be useful. If a simple comparison of the usage of each tool is desired, the default unstacked view should be used. When using the stacked view, the total usage statistics are also shown at the bottom of the legend.

The report defaults to showing the top five objects that are reported by a group - in this example, reported by users. All other objects, if applicable, are combined into an "others" group.

The report uses a dynamically calculated averaging interval (referred to as the "binning" interval), based on the specified report period. For example, a 1-week report would result in a 4-hour interval, whereas a 1-month report period would result in a 1-day averaging interval.

The options box on the left side of the page provides controls to setup any desired filters, the report-by option, the smoothing basis, and plot customization parameters.

The report can be driven by usage data that has been smoothed according to the peak usage (default) or the average usage. If using the peak, the plot will visualize the usage considering the peak usage, and the statistics in the legend will contain both the peak and average of all peaks found across all of the binned intervals. If using the average usage, the plot will visualize the average usage over time, and the legend statistics will include the peak and average of all averages found across all of the binned intervals. Note that when using the average usage, peaks will be obscured based on the averaging interval. For example, a peak of 30 minutes will not show up in a 1-week report because that usage will be factored into the average.

Custom Groups

If custom groups have been configured in Monitor, they will be available in the filter and pie chart report by sections of the options box. This is not only where "filter by" options are specified, but also where the specific custom group is selected for Reservation Overdraft Analysis.

Reservation Overdraft Analysis

Reservation Overdraft Analysis is a way of visualizing how FlexNet Publisher license reservation pools are utilized, and how much excess member usage is hitting the general pool. Paired with the "include reservations" capability, this is an effective tool for identifying waste and tuning how tokens are used. In order for this plot to function correctly, some preparation is required:
  • You must be utilizing the license reservation mechanism in FlexNet Publisher options file, otherwise Overdraft Analysis is irrelevant.
  • Reservation tracking must be enabled in the FLEXlm monitor page of the tag for which Overdraft Analysis will be done ( or if you are using a manual configuration, it will require the -trackreservations option).
  • The specific license options file for the tag must be manually parsed at the command line to create a custom group and group types that correspond to your reservation pools. This custom group type will then show up as a checkbox in the left margin in the options box. The user must generate Custom Group Types/Custom Groups using the desired FlexNet Publisher options file as input. This is the options file that should contain reservations you are interested in analyzing. The groups are generated at a vovproject-enabled shell with the following command:
    ftlm_accounts loadfromoptions /path/to/options/file   GROUP_TYPE   all
    For example:
    ftlm_accounts loadfromoptions /path/to/options/smpsd.opt Synopsys_Reservations  all
  • When the Detailed Plots report is refreshed, a new Synopsys_Reservations checkbox will be available. A new "overdraft analysis" plot will also show up, which can be disabled with a checkbox.
  • Overdraft analysis may be enabled by selecting the checkbox on the left margin in the options area (below "include reservations").