Last month we introduced our Network Query Engine (NQE) at Cisco Live Europe and to a very impressive technical audience as part of Tech Field Day 2019. If you didn’t have the chance to read through our introduction blog, NQE leverages the internal network data model that Forward Networks builds and manages to allow users to query their network infrastructure details like a database. These queries can be quickly built to confirm network health, proper configurations, effects of a change, device or interface status, etc. A few representative queries that customers have described to us and that are now possible include:
- Do all distribution layer access links in my network have redundant paths?
- Are all BGP sessions currently established with configured peers?
- What are the nearest neighbors of a down device?
- Are any device interfaces intended to be operational currently down anywhere in my network?
By viewing all network details as a data source, users are able to query on issues globally across their entire network, looking for any anomalies, in one quick sweep. This has rarely been possible before, without an enormous amount of usually custom effort. The alternative is to check for conditions at each device, one at time, across a large network. Scripts that automated these kinds of custom checks across network devices are very tedious to develop and maintain, especially across different vendors and device types. Forward Networks now makes it easy to build queries in only a few minutes, based on the normalized, vendor-neutral data model in our platform, with a very flexible new query language, GraphQL.
GraphQL was developed by Facebook and turned into an open source project in 2015. It offers enormous flexibility in defining what information is returned, independent of the data model, making it much more efficient for almost every use case than typical interface APIs. GraphQL query statements are natural to embed in programming or scripting languages, like Python, to further compare or analyze the extracted data, or format the results.
Now See the Demos
But, the best way to get a handle on how NQE works is to see a quick video we built that explains how it can be used inside our Forward Enterprise platform, how a sample query is built and how the information can be leveraged. Check out the short demo below:
A lengthier and more technically advanced use case was presented as part of Tech Field Day. Our lead NQE engineer, Andreas Voellmy, shows how we can compare BGP routes in downstream and upstream routers to confirm they were all exported correctly as advertised. This situation actually caused a severe outage at one of our service provider customers, so they wanted to be able to continually check for this scenario. To be able to programmatically verify this across an entire SP network, with many vendors, on a daily basis is a huge time saver and eliminates future errors for them now. Check out Andreas’ demo that replicates their use case here:
“For years organizations have been trying to extract value from the data available to them in large complex network environments. Unfortunately, manual efforts and inefficient collection and normalization procedures have held them back. Fortunately, Forward Networks has unlocked the ability to quickly, easily and programmatically convert network data into knowledge and actionable information leveraging its Network Query Engine feature.” - Bob Laliberte, ESG
Network IT engineers realize that NQE gives them a really accelerated approach to automate almost any of their network analysis and health status checks. Our platform provides many useful ways to analyze the network end-to-end, but NQE allows customers to query the collected and normalized data in thousands of ways and use cases that we didn’t design for.
A few final quick points to know:
- We provide a lot more information and example code on our github repository, where we invite customers to share their code samples and feature requests.
- NQE is currently part of our Forward Enterprise product and available now.
- Our NQE data model takes inspiration from OpenConfig, and we have aligned with that data model where possible, although there is not a strict syntactical mapping. More details on our github repository.
Want to learn more or get a live demo? We’ll show you how NQE can help accelerate your networking tasks and processes in minutes.