Introducing the Forward Enterprise and NetBox Integration

NetBox Labs, is the open-source startup behind NetBox, a tool designed specifically for network engineers and operators. It combines the functionalities of IP Address Management (IPAM) and Data Center Infrastructure Management (DCIM) into a unified solution. With this relationship, Forward Enterprise and NetBox Cloud customers:

• Eliminate manual discovery and data entry: Leverage Forward Networks to automate “Day 1” discovery of networks and populate NetBox Cloud’s network data model, accelerating time to value.
• Easily implement ongoing network assurance and validation: Integrate solutions from Forward Networks with NetBox Cloud as the Network Source of Truth.
• Gain new insight for compliance checks: Leverage data from NetBox Cloud’s model to augment data in partner platforms, addressing key network observability and operations use cases such as compliance validation.

The relationship includes a joint effort to build a bi-directional integration between Forward Enterprise and NetBox. I’m thrilled to announce that the initial release of this integration has been published in this GitHub repository!!!

It enables customers to:

• Onboard a NetBox instance by importing data discovered and collected by Forward Enterprise from the network using a provided Python script. In this initial integration, customers can export devices and interfaces from Forward into NetBox DCIM.
• Import device data from NetBox such as role, tenant, and racks. Customers can then display this data in Forward applications (e.g., device cards) or use it to create verification and compliance checks.

Onboard a NetBox instance

Onboarding a NetBox instance can be achieved by utilizing the data discovered and collected from the network through the Forward platform. This process involves running the provided Python script available in the mentioned GitHub repository.

The scripts performs the following actions:

1. Retrieves Forward Devices and Interfaces using Forward NQE REST APIs
2. Gathers information such as Sites, Device Types, Device Roles, Interface type, etc. from NetBox via REST APIs
3. Translates the data from Forward into the NetBox schema
4. Pushes Devices and Interfaces to NetBox via NetBox REST APIs

Here are two screenshots that display devices and interfaces imported into NetBox by the script:

Import device data from NetBox

This integration is designed for users who would like to import data stored in NetBox into Forward, either to display them in the Forward application or to create verification and compliance checks.

This integration did not require any development! It relies on features like External Sources import, NQE Queries, NQE Verifications, and NQE Decorators, which are available to all Forward customers. With Forward External Sources, customers can import data from any HTTP-based external application each time it collects information from the network infrastructure. Forward automatically infers the data schema from the imported data and stores it in NQE. Once in NQE, it can be used like any other data collected from the network.

The following screenshot shows a device card displaying data imported from NetBox:

What’s next?

This is just the beginning of the collaboration between Forward Networks and NetBox Labs. Stay tuned for more exciting updates!

Meanwhile, check out the GitHub repository and feel free to provide any feedback or, better yet, contribute with any enhancement!! Reach out to Forward Networks or NetBox Labs for more information. This marks just the beginning of the collaboration between Forward Networks and NetBox Labs. Stay tuned for more exciting updates!

Cisco Live Amsterdam is kicking off in less than a week! We hope you'll stop by our stand (C13), grab a coffee from our barista, and learn about our new AI-supported feature, AI Assist, which was recently featured in Network World.

We're giving away three electric bikes! Attend a theater demo or talk to one of our onsite technical experts for a chance to win.

Theater presentations are every half-hour in the booth. Learn about:

• Simplifying data access with AI
• Enhancing security and proving compliance with a digital twin
• Enabling end-to-end visibility in hybrid, multi-cloud environments
• Reducing outages and ensuring the network behaves as intended

Join our live sessions:

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Natural language prompts put the power of NQE into the hands of every networking engineer

As featured in Network World, Forward Networks has raised the bar for network digital twin technology with AI Assist. This groundbreaking addition empowers NetOps, SecOps, and CloudOps professionals to harness the comprehensive insights of NQE through natural language prompts to quickly resolve complex network issues.

See the feature in action.

AI Assist: Transforming Network Operations:

Recognizing the persistent challenges faced by engineers in accessing hybrid, multi-cloud network data amid vendor diversity and network complexity, Forward Networks introduced AI Assist, available today as part of release 24.1. The new feature facilitates Network Query Engine (NQE) searches using natural language prompts, allowing engineers of varying skill levels to conduct sophisticated network queries with a minimal learning curve. The feature also generates natural language explanations for queries, fostering improved collaboration and understanding within teams.

Building on the Industry’s Most Comprehensive Networking Data Library:

Leveraging its extensive NQE library, the capability will be continuously improved through use. A world-class networking large language model (LLM) combined with the industry’s most comprehensive network digital twin delivers the AI outcomes that users can trust.

Learn more about Forward Networks’ AI implementation at www.forwardnetworks.com/ai

Forward introduces AI Assist to help engineers gain greater insights and reach faster resolutions to their most challenging network issues using natural language

SANTA CLARA, Calif., Jan. 25, 2024 /PRNewswire/ -- Forward Networks has officially launched AI Assist, a groundbreaking generative Artificial Intelligence (AI) feature integrated into its flagship platform, Forward Enterprise. This cutting-edge addition aims to empower NetOps, SecOps, and CloudOps professionals, enabling them to gain comprehensive insights and expedite solutions for their most demanding network challenges through natural language prompts. The announcement coincides with the company's unveiling of its long-term AI strategy.

Recognizing the persistent need for enhanced access to hybrid, multi-cloud network data among engineers, Forward Networks addresses the hurdles posed by vendor diversity and network complexity. AI Assist, available today, facilitates Network Query Engine (NQE) searches using natural language, thus allowing team engineers of varying skill levels to conduct sophisticated network queries with minimal learning curve. Moreover, AI Assist generates natural language explanations for existing queries, fostering improved collaboration and understanding within the team.

Forward Networks is harnessing the collective power of user-generated searches and its extensive NQE library to train its networking large language model (LLM). Because Forward Enterprise collects an unparalleled breadth of cloud and device data, the integration of the networking LLM with Forward's advanced data platform streamlines operations and provides even novice users with advanced insights into network behavior. Leveraging the ease of natural language, AI Assist empowers engineers to quickly assess network behavior and identify potential issues (e.g., non-compliance, troubleshooting). The model's continuous improvement is driven by operator utilization, establishing a solid foundation for upcoming AI features.

"By combining the power of our network digital twin with AI, we make it even easier for engineering and security teams to extract critical insights from their network," said Nikhil Handigol, Co-Founder, Forward Networks. "We are developing the world's leading networking large language model, laying the groundwork for future features that proactively assist engineers, enhance the efficiency and safety of changes, and aid in determining optimal network configurations. Since founding the company just over ten years ago, our passion has continued to grow and drive our commitment to modernize networks. Harnessing the powerful capabilities of AI is integral to achieving our vision."

Forward Networks ensures that the world's most complex and mission-critical networks are secure, agile, and predictable. The platform gathers configuration and L2-L7 state data from network devices and public cloud platforms, creates a mathematical model of the network, and computes all possible traffic paths. Supporting devices from major networking vendors and cloud operators, including AWS, Microsoft Azure, and Google Cloud Platform, Forward Enterprise stands out as the go-to solution for large enterprises managing multi-vendor, hybrid-cloud networks.

"In this hyper-connected digital business environment, networks and networking staff are under tremendous pressure to heighten service integrity and capabilities on a continual basis," said IDC's Mark Leary, Research Director – Network Observability and Automation. "IDC research indicates that those organizations that leverage the power of AI across their network infrastructure are driving greater gains in operational efficiency, digital experience, and key financial measurements. Forward Networks' purpose-built networking LLM, coupled with their comprehensive digital twin platform, represents a promising advancement in bolstering network resiliency and responsiveness."

Read Press Release on PR Newswire

Digital twins are often associated with manufacturing, where a virtual replica mimics the workings of a complex physical system, such as a jet engine or a machine on a production line. But increasingly, there is interest from enterprises, telecom companies, and cloud providers in applying the technology to networks. [READ MORE on NETWORK COMPUTING]

The term “digital twin” technology, initially referenced with industrial use cases, is gaining popularity. An industrial digital twin is a virtual depiction of a physical product, process, or system within an industrial context like manufacturing. According to Accenture, digital twins “support better decision-making by simulating how assets behave given certain inputs.” The benefits of being able to test conditions and eliminate problems before they occur can’t be overstated in a manufacturing environment; the same digital twin technology can also provide virtual representations of complex enterprise networks. [READ MORE ON DIGITAL IT NEWS]