Today’s business leaders are laser-focused on accelerating AIOps, including speeding time to comfort for users, and also on speeding bottom-line business value that can be realized from AIOps. That’s where Juniper’s AI-Native Networking Platform is gaining traction. Juniper’s AI-Native Networking Platform is purpose-built to help organizations harness the power of AI, accelerate AIOps, and speed time to comfort AI users within the organization while also helping deliver the bottom-line value businesses seek.
This is important, as in today’s rapidly evolving and complex IT and application landscapes, operations teams are tasked with monitoring and managing infrastructure deployed across private data centers, public clouds, and edge locations. As a result, the network is essential to delivering positive experiences and achieving business objectives. However, the sheer volume of data collected in these environments makes it virtually impossible to correlate the data and determine the root cause of a problem in real-time.
The Role of AIOps in Speeding Time to Value with AI
In a recent research study we conducted, The Impact of AI on the Network, a whopping 80% of respondents stated the network environment is more complex than it was two years ago. This is where AIOps in general, and a focus on accelerating AIOps in particular, can play a significant role in assisting operations teams.
However, given the current amount of AI washing and AI hype that we’re currently experiencing, it can be challenging for organizations to differentiate between what’s real and what is not. Spending on AI technologies is happening at a fairly rapid pace. In fact, data from our research partner, Enterprise Technology Research, indicates that more than half of respondents (58%) have increased their net sentiment and spending for AI technologies. This represents a growing recognition of the potential benefits of AIOps solutions, yet we know that adopting a new technology can be a time-consuming process.
Evaluating an AI Solution for Networking: What to Consider
Network operations teams, like most IT operations teams, tend to be more conservative when deploying new technology, especially in environments where high availability and consistently positive experiences are expected. As such, it’s important to know going in that evaluating AI technology will require a deliberate approach, which will require time to validate. In addition to time to validate, users will need to become comfortable with the new technology, which, of course, will vary from individual to individual, as well as from organization to organization based on their culture and leadership. Traditionally, validating the accuracy and effectiveness of any new IT technology tools involved creating a test bed that represented the production environment. However, this process is expensive and can be protracted, taking six months or more to vet a solution thoroughly.
As the technology innovation cycle continues to accelerate and organizations are required to move faster, this validation window or time to comfort must be shortened for AI technologies. One of the best ways to do that is to choose a mature, proven solution combined with a rigorous adoption program or blueprint for organizations to follow, which could dramatically reduce the time required to become comfortable. When evaluating an AI solution for networking, organizations should carefully consider several critical criteria to determine its maturity, including:
- Extensibility: how many network domains are covered?
- Trusted, high-quality, and relevant data to build the model
- Efficacy: Proof of the model’s accuracy (i.e. can it demonstrate continuous improvement)
- Secure: Eliminate the potential for data leakage
- Explainability: Provide context or link for the answers
- Simple to use: Single AI assistant using natural language processing
- Closed-loop system: Enable operations to provide feedback
- Digital Twin: Proactively test digital representation without impacting the actual environment
- AI Blueprints: Standardized program to accelerate adoption and validate technology
Juniper’s AI-Native Networking Platform Checks All the Boxes
Fortunately, mature AI solutions exist today — keep in mind that Watson competed and won on Jeopardy in 2011. As I see it, Juniper’s AI-Native Networking Platform, which the company spent nearly a decade developing, checks all the boxes for critical evaluation criteria.
As a result, most Juniper AI users I have spoken with report that operations teams have shortened the time to comfort, knocking off four to five months from legacy evaluation cycles. This also means the Juniper solution is already deployed in production environments and is delivering real customer value.
This value included a shift to users being more proactive and having more time to work on strategic initiatives, with trouble tickets dropping from hundreds to just a few over the same period after being deployed. Juniper AI users also noticed that many issues were being automatically resolved before they were even detected by users or the operations teams.
So, the real question is, what are you waiting for? Now is the time to get started — check out Juniper’s AI-Native Networking Platform combined with its Blueprint for AI-Native Acceleration, which can expedite the time to comfort and provide real value to your business.
We are excited to be broadcasting on Thursday, August 22nd from our new studio at the New York Stock Exchange. Join me, John Furrier, and executives from Juniper to discuss the latest tech innovations driven by Mist AI, as well as how Juniper Networks is revolutionizing network management and operations with AI-native innovation. Key technology areas discussed will include Wi-Fi, wired switching, AIOps, network access control, SD-WAN, and location-based services. Don’t miss this opportunity to see how AI is transforming the future of networking.
For more information on these solutions, register for this upcoming webinar using this link, and we’ll see you there!
See more related coverage here:
HPE Juniper Highlights the Trend in Network Vendor Consolidation
HPE Fortifies AI-Powered Networking Portfolio with Advanced Security Features
HPE and Juniper Networks and a $14B Price Tag: Smart Move or Not So Much?
