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Hudl Enhances Performance Monitoring with Sumo Logic's Real-Time Analytics
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Software
- Professional Service
Applicable Functions
- Business Operation
- Product Research & Development
Use Cases
- Machine Condition Monitoring
- Predictive Maintenance
- Remote Asset Management
Services
- System Integration
- Software Design & Engineering Services
The Challenge
Hudl needed a way to collect and centralize massive amounts of data generated by its modern applications, cloud platforms, servers, network devices, and endpoints to rapidly identify and remedy performance issues. The company realized that its vast data requirements and the fast-moving, distributed nature of its services called for a move from a monolithic application and development architecture to a microservices architecture. Hudl was conducting an average of 10 deployments a day, which has since risen to roughly 25 deployments a day. The team needed to know quickly the cause of any availability or performance issues and how to rapidly remedy the situation. Hudl’s customers generate an enormous amount of customer analytics data, with events created every time someone plays a video or loads a new screen, either online or within the app. With every event, new data is generated to capture what the user is doing at the time, as well as which aspects of the new feature are popular – and which are not. Hudl’s development and operations teams needed a better way to collect massive amounts of data from applications, cloud platforms, servers, network devices, and endpoints.
About The Customer
Hudl is revolutionizing the way coaches and athletes prepare for and stay ahead of the competition. Their mission is to help teams and athletes win by providing the tools to create, edit, and share game video, study associated play diagrams, and create high-quality highlight reels both for entertainment and recruiting. Hudl provides everything coaches and athletes need to analyze and improve performance through video and stats. The entire experience is available online, giving coaches and athletes secure access at home and on the go. Nearly 3.5 million unique users from 114,000 teams, including 28 NBA teams, 19 English Premiere soccer teams, and 18 World Cup rugby teams, actively use the Hudl platform, making it the preferred game film service for all programs, from the smallest youth and high school organizations to professional franchises across six continents. Hudl built the technical foundation of its services on a public cloud with a large team of about 200 developers, quality assurance professionals, designers, and product managers who are all dedicated to making sure the Hudl IT playbook is executed smoothly.
The Solution
Hudl chose Sumo Logic’s cloud-native machine data analytics platform because it provided easy-to-deploy, full-stack visibility and real-time insights into the status of its service. Sumo Logic is the secure, cloud-native, data analytics service that delivers real-time, continuous intelligence across the entire infrastructure and application stack. With Sumo Logic, Hudl gains a service model to help automatically generate audit-ready compliance reports from both its on-premises and AWS event logs, and gains the insight to quickly diagnose and fix system errors and service disruptions. The first thing Hudl appreciated about Sumo Logic was how easy it proved to deploy, with Sumo Logic’s APIs being very straightforward to use. Sumo Logic provided Hudl the ability to quickly identify and rectify performance-related incidents as they arose. For example, using Sumo Logic, Hudl has created a dashboard that notifies support teams whenever there is an outage or performance issue. With Sumo Logic, Hudl has the ability to filter down to only the data relevant to what is happening in real time, or recall specific dates to see the overall availability minute-by-minute during that time period. This enables Hudl to see exactly what went wrong and understand how to prevent that issue in the future.
Operational Impact
Quantitative Benefit
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