We just released our 22.5 Release to Forward Enterprise and boy what a surprise to have our NQE external data sources finally ready to show the world.

Very simply, this allows you to pull in data from external HTTP sources (currently we support HTTP GET) and automagically model the data in our data model explorer and our integrated development environment.

To enable this you simply need to add the resource endpoints for the HTTP API of the data you are interested in. i.e. /api/dcim/sites, configure the authentication if required and you are ready to collect.

Once you run our collection framework we will pull all of this information into our already extensive data model.

All the data available from the external resource definition is modeled in our platform and can be used to build custom evaluations across external/internal resources and unify multiple data sources into a representation that can be consumed from external systems.

Our import includes a type inference capability to determine if values can be elevated from String, Number to more specific types such as IPAddress.

Once we have added our external resource endpoints. We can run our collection to pull the external data into our platform as a JSON encoded file.

Building out our custom integration layer

Now that we have the data, we compose queries using our rich IDE capabilities. Below you can see our code completion displays all the available collections under the NetBox external source.

Because NQE is an extensible query language we can join two or more collections together by simply binding common fields leveraging the where clause.

The two where clauses in lines 8 and 9 below join the existing Forward Enterprise device collection with the NetBox devices inventory as well as joining the NetBox devices collection with sites collection allowing us to create a composite output of three independent data sources.

The final query below combines data from these three sources allowing us to take the device name, site name and manufacturer from the NetBox devices collection, Site address from the sites collection, and interface IP addresses from Forward Enterprise Data model to produce an aggregate report.

Below is the output from our IDE but you can also export this data to an Excel spreadsheet for offline review.

Hold on to your hat!, Now that we have our query committed in the NQE Library, it automatically becomes available as a custom API endpoint. Now any external systems can make a simple REST call providing just the unique queryId, (think of this like a SQL Stored Procedure) to the /api/nqe endpoint and you get back the data in JSON!

In the below example, we create an Ansible module to call the NQE API interface as a task so it can be combined with additional workflows.

Summary

With about 20 lines of code you can build an API aggregation layer for network information combining external data sources with the rich database of network configuration and state available in the Forward Enterprise platform.

Thanks to Andreas Voellmy and his team for building NQE and continuously adding these great features for our customers to leverage.

Here at Forward Networks our mission is to "Transform networks to be agile, predictable and secure" and now with external data sources we have another arrow in our quiver to accomplish that.

Way more to come.

Come check us out.

Today's enterprise IT teams are well acquainted with the pressures of ensuring network security, while also managing the time it takes to do so. The recent experience of one multinational technology company perfectly illustrates how Networks Query Engine (NQE) can be used to quickly and effectively bolster network security.

As with most companies, this company's IT team was asked on a regular basis to locate IP addresses in the network. While some of these queries are more general in nature, others stem directly from concerns over network security.

For instance, IT might learn that a particular host isn't supposed to be on the network. Or someone might raise a red flag after seeing a tablet logged into another machine. Regardless of the cause, however, it's imperative that IT quickly locate and isolate potentially dangerous IP addresses.

Traditionally, the process of doing so has taken anywhere from a few minutes up to as long as 20 minutes. And if there's anything that enterprise IT teams agree upon, it's the need to reduce time-intensive projects.

According to one recent study, 72 percent of technology professionals say the shift to support remote work – whether fully remote or hybrid – has created additional work for IT departments, as they struggle to support employees in multiple locations. Furthermore, a quarter of the IT workforce is either looking for a new role, changing jobs or switching careers in 2022.

Not surprisingly, 97 percent of IT professionals cite feeling burned out as the primary driver for leaving the field and/or finding a new company. That burnout is driven by increasing demands from employers and other stakeholders – and many of those demands stem from unplanned interruptions like the need to locate an IP address.

In this particular case, the enterprise IT team found that by utilizing NQE to locate an IP address, they were also able to find the associated advertised subnet. Likewise, they quickly found the upstream layer 3 distribution switch and its associated media access control (MAC) address, enabling them to pull the associated virtual LAN and access the specific switch that's being used by a specific device.

Moreover, using NQE to locate the IP address reduced the amount of time needed to do so to just a matter of seconds vs hours or days of manual work. This frees the IT team to work on more strategic projects and eliminates a mind-numbing task that contributes to burnout.

Learn more about how you can use NQE to solve common IT tasks by scheduling a demo today. Be sure to read our other blogs in this series about how Forward Networks is impacting enterprise networks around the world, including The Show Must Go On: NQE Helps Entertainment Venue Avoid 'Spectacular Customer Service Fail.'

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