Redis Enterprise on AWS: A Scalable Solution for HackerRank's Data Layer Needs
Technology Category
- Analytics & Modeling - Real Time Analytics
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Cement
Applicable Functions
- Maintenance
- Product Research & Development
Use Cases
- Real-Time Location System (RTLS)
- Time Sensitive Networking
Services
- Cloud Planning, Design & Implementation Services
About The Customer
HackerRank is the industry leader in pre-screening, technical assessments, and remote interview solutions for hiring developers. The platform is used by more than 11 million developers to practice coding skills, prepare for job interviews, and get hired. HackerRank’s overarching goal is to become the single source of truth for every engineer’s technical ability. Every day, more than 70,000 candidates compete in code competitions and are subsequently ranked on the company’s public, global leaderboard. The leaderboard is one of the most heavily used components in HackerRank’s system, and must perform under significant stress during peak times, from large coding events to surges in company recruiting.
The Challenge
HackerRank, a leading platform in pre-screening, technical assessments, and remote interview solutions for hiring developers, was faced with the challenge of needing a fast, scalable, and reliable data platform that required minimal maintenance and configuration. This was crucial for the company to focus on innovation and to fulfill its mission of becoming the single source of truth for every engineer’s technical ability. Additionally, HackerRank needed a real-time leaderboard to showcase top developers. The company was using multiple solutions to cobble together a data layer, which was not efficient or sustainable for its growing needs.
The Solution
HackerRank adopted Redis Cloud as a unified data platform to handle all its use cases. Redis Cloud was able to handle large-scale recruiting events where over 20,000 developers take coding tests simultaneously with ease. It also provided in-memory performance to keep real-time standings, regardless of the number of developers taking tests at the same time. HackerRank used Redis Cloud to build not only its caching layer but also its database for all of its real-time use cases. For code compilation and execution, HackerRank leveraged the RedisJSON module to provide live execution status, reducing latency and providing real-time updates to users. The RedisBloom module was used to implement key aspects of its global leaderboard.
Operational Impact
Quantitative Benefit
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