ServiceNow Achieves 90% Fewer Network Incidents with HPE Mist AI
After overhauling its networking infrastructure, ServiceNow slashed network incidents by 90% and aims for total network autonomy by 2028. The transition to HPE's Mist AI has revolutionized their operations and set a benchmark for automated network management.
Key Facts
- ServiceNow's network incidents dropped 90%, showcasing AI's impact on operational efficiency.
- Network patching hours reduced from 2,000-3,000 to <60, revealing significant cost savings potential.
- Same team managed network post-AI, indicating improved productivity without increased headcount.
- ServiceNow's goal for a 100% autonomous network by 2028 suggests a strategic shift towards full automation.
- HPE's self-driving network model shows competitive advantage, resolving 70-80% of issues autonomously.
Summary
Summary
ServiceNow achieved a 90% reduction in network incident volume after transitioning its network operations to HPE's Mist AI platform. The deployment significantly decreased network patching time from 2,000-3,000 hours per year to fewer than 60 hours, all while maintaining the same team size. ServiceNow aims for a fully autonomous network by 2028.
Background
ServiceNow, a leader in digital workflows and IT service management, faced a chaotic network environment prior to the deployment of HPE's Mist AI. The company had been using various point products to address specific issues, which resulted in fragmented network telemetry and manual data correlation by engineers.
Challenge
The primary challenge was the overwhelming volume of network incidents and the extensive time required for network patching. ServiceNow needed a solution that would streamline operations, reduce incident resolution times, and improve overall network management efficiency.
Solution
ServiceNow began its transformation by implementing Mist AI in 2018, starting with a small deployment focused on measuring end-user experience and applying AI across the wireless network. Following Juniper Networks' acquisition of Mist in 2019, ServiceNow undertook a comprehensive network overhaul during the COVID-19 pandemic, migrating to a unified platform that integrated Wi-Fi, wired, and WAN networking. This included the use of Juniper access points, EX switches, and Session Smart SD-WAN routers, all managed by Mist's AI engine, Marvis.
Results
The results were substantial: network incidents fell by 90%, and troubleshooting that previously took hours was reduced to minutes. Network patching time decreased from 2,000-3,000 hours annually to fewer than 60 hours. ServiceNow maintained the same network team size despite significant growth in the company.
Key Insights
One key takeaway is the importance of gradual autonomy in AI deployment. ServiceNow's approach allowed the network team to build confidence in the technology over time, leading to greater acceptance and a shift towards higher-level tasks. This method can be applied to other organizations looking to integrate AI solutions.
Customer Testimonial
"ServiceNow has grown immensely over the last several years, but their IT team has not," said Rami Rahim, EVP, president and GM of HPE Networking.
Entities Mentioned
Companies
Products
Technologies
People
Organizations
Key Concepts
Definitions
- autonomous network
- A network that can manage and optimize itself without human intervention.
- Mist AI
- An AI platform developed by Mist Systems for managing wireless networks.
- Marvis
- The AI engine used by Mist to provide insights and automate network management.
- graduated autonomy
- A phased approach to transferring control to AI, allowing for incremental confidence building.
- self-driving network
- A network that autonomously resolves issues and optimizes performance using AI technologies.
Use Cases
- →reducing network incidents by 90%
- →automating network patching
- →integrating AI with IT service management software
- →providing managed services for enterprise networking
- →improving end-user experience in networking
- →enabling incremental autonomous actions in networks
Frequently Asked Questions
How did ServiceNow achieve a 90% reduction in network incidents?
ServiceNow moved its network operations to HPE's Mist AI platform, which automates many network management tasks. This shift allowed the system to resolve 70-80% of potential issues autonomously.
What is the goal of ServiceNow's network strategy by 2028?
ServiceNow aims to achieve a fully autonomous network by 2028. This involves gradually handing over control to AI systems to enhance efficiency and reliability.
What role does Marvis play in ServiceNow's network operations?
Marvis is the AI engine that powers Mist's capabilities, providing insights and automating network management tasks. It helps in quickly identifying and resolving network issues.
What challenges did ServiceNow face during the transition to AI-driven networking?
Initially, the network team was skeptical about AI control, fearing it could worsen issues. ServiceNow addressed this through a graduated autonomy approach, building confidence over time.
How does HPE's self-driving network benefit its customers?
HPE's self-driving network allows customers to automate network actions incrementally, leading to significant reductions in service desk tickets and improved operational efficiency.