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Several tools can be utilized at various hierarchical levels to track and analyze system needs and performance.
At the cluster level, performance parameters are leveraged to track compute, latency, and more, down to the physical disk.
The vSphere client portal is part of the VMware suite. It provides out-of-the-box charts to view real-time and historical VM performance of:
There are several ways to collect analytics for overall equipment efficiency, predictive maintenance, and identifying faults. ThingWorx provides graphical Mashups and DPM-based dashboards to define the desired analytics for factory performance evaluation.
Using a rich set of REST API, Python, and Java Scripting capability, and database-level analytics tools like PowerBI, Tableau, and others, more complex analytics can be developed.
The following sections cover the Mashups capability of ThingWorx and show the DPM dashboard. Other options listed here are out of scope for this guide, but mentioned here for general guidance.
In ThingWorx, a Mashup is a web page to visualize data and to interact with a Thing model through a graphical interface. Mashup Builder is the tool to create visualization web pages in ThingWorx. It is a 100% configuration, zero-code content development environment.
Visualization of IoT data can be created quickly and easily with Mashup Builder. The tool allows users to combine the data services available within ThingWorx with a set of widgets to create unique web pages.
The Mashup Builder workspace consists of the following default sections when in design time:
To view the Mashup, click View Mashup. When you view a Mashup, a new tab opens, and the Mashup is rendered in a runtime environment. During runtime, you can execute services, trigger events, and interact with your Thing models.
You can also view Mashups directly using the REST API service. To view a Mashup directly, use the following syntax:
<protocol>://<server>:<port>/Thingworx/Mashups/<MashupName>
<protocol>
—protocol used to connect to the server (HTTP or HTTPS) <server>
—name or IP address of your ThingWorx server <port>
—port number <MashupName>
—name of the Mashup entity in ThingWorx The following figure illustrates how the Factory1 data is visualized using Mashup Builder. The upper pane shows the current values from variables such as sensor live values, and the lower pane shows the historical values stored in SQL Server, PostgreSQL, or InfluxDB databases in a separate server.
Various alerts can be created for events, including if the value of a property changes beyond certain limits.
Mashup templates can be created as custom Mashup templates. Other users can then choose these custom templates as starting points to design their own Mashup.
The following figure shows where to find the Mashup templates section in the Browse menu.
Bulk editing of the Mashup can be done by exporting it to .xml format, as shown in the following figure. For example, if a user wants to replicate ‘baseMashupFactory1’ for Factory2, Mashups can be edited in .xml to replace bindings. Edited Mashups can then be imported back.
Digital Performance Management (DPM) is an add-on for the PTC ThingWorx platform. Using the separate Microsoft SQL Server database, it can collect factory production operation data to provide information about job status, material movement, production quantities, and other insights into overall equipment and production effectiveness.
The following figure shows the DPM dashboard that uses PTC Kepware base-connected data ingested into PTC ThingWorx and a separate DPM SQL Server database for real-time production monitoring.
Key metrics exist to help monitor ThingWorx applications. Select tools can be deployed to collect and analyze the following performance indicators:
Each log file corresponds to some of the same content that you can see in the Monitoring drop-down in ThingWorx Composer.
Windows PowerShell with VMware PowerCLI integration can be used to collect performance metrics including the SCSI controller, CPU and memory consumption of individual VMs, disk latencies, and throughput information.
At the OS level, many tools are available to track performance metrics. These tools and metrics vary based on OS.
In a Windows systems, the built-in Performance Monitor application provides an easy-to-use graphical user interface (GUI) to configure jobs that can collect specified data on demand. These metrics track compute performance, memory use, and storage use, broken down by disk. These jobs can also be exported as a template to quickly configure multiple machines.
Linux systems offer comparable statistics with select packages. The sysstat package offers system performance tools that are comparable to those in Performance Monitor on Windows, including CPU utilization and disk I/O statistics. This package can be installed on both Debian and CentOS Linux systems, though the installation varies between them.
After installing the sysstat package, execute the iostat
command to output a set of real-time system statistics including CPU use, memory use, and disk use.
Several options can customize the statistics displayed. Details on command options and the collected metrics are available on the iostat man page. Execute the iostat -xtk 1 1800 command to:
These metrics can be easily output to a file for simple tracking.