In the previous part of this series, we saw how to define a basic portlet. Now we will look into making this portlet reference a web page that will enhance our dashboard experience.

In this example, we will be embedding a Developer Community article along side a couple of widgets displaying information related to the number of views on the Developer Community articles. This example is not hosted on the Community Analytics server, but if it was we could see the view counts going up as we interacted with the page.

Why use this?

In a real case, perhaps you have an embedded page from an external web site showing the current Emergency Room wait times for Hospitals in your area. This portlet can be used along side widgets from your Emergency Room showing how many people are waiting, how many doctors are active, and how many people are being treated. As other Emergency Room wait times grow, you can possibly expect your volume to increase as well. This can help you make decisions on how to allocate resources.

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Article
· Dec 12, 2019 2m read
Creating Portlets in DeepSee

What is a portlet?

The simple answer is: a custom widget. A portlet can exist by itself on a DeepSee dashboard, it can be used along side standard DeepSee widgets, or along side other portlets. The rendering of the custom widget is completely user defined. This means you can embed a web page, create a form to perform any sort of action needed based on the data on your dashboard, use third party charting libraries, or simply display data from outside of a DeepSee cube.

How to get started

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Article
· Feb 13, 2017 14m read
Creating custom SNMP OIDs

This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.

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Users of analytical applications often need to generate and send out PDF reports comprised of elements of the analytical panel. In the InterSystems stack, this task is solved using the DSW Reports project that is an extension of DeepSeeWeb. In this article, we will explain how to use DSW Reports for generating PDF reports and emailing them.

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This is the first article of a series diving into visualization tools and analysis of time series data. Obviously we are most interested in looking at performance related data we can gather from the Caché family of products. However, as we'll see down the road, we are absolutely not limited to that. For now we are exploring python and the libraries/tools available within that ecosystem.

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Hi, Community!

This is the 3rd part of DeepSee Web story - Angular base UI for DeepSee Dashboards, see the beginning here.

By design, DSW provides an implementation for every widget in DeepSee library. But there are some extra features in DSW which make solutions built with DSW dashboards more functional. This article describes it.

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Hi, Community!

Please welcome a new session recording from Global Summit 2017:

Data Visualization: The Choice is Yours

https://www.youtube.com/embed/1pdzlCDrabo
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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Article
· Dec 22, 2016 2m read
The Polymetric Dashboard

> Customizable System Monitoring. ## Introduction The Polymetric Dashboard is a stand-alone module that provides enhanced monitoring tools for a Caché environment. Equipped with over one hundred sensors that monitor key system metrics, a robust REST API, and a modular AngularJS user interface, the Polymetric Dashboard is fully functional out of the box. However, the Polymetric Dashboard is designed to be customizable; any system metric can be monitored by creating a new sensor, and the visualization of collected data can be tailored to specific requirements and purposes.

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In last week's discussion we created a simple graph based on the data input from one file. Now, as we all know, sometimes we have multiple different datafiles to parse and correlate. So this week we are going to load additional perfmon data and learn how to plot that into the same graph.
Since we might want to use our generated graphs in reports or on a webpage, we'll also look into ways to export the generated graphs.

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