Monitoring a Complex and Elastically Scaling Cloud Infrastructure to Avoid Performance Issues
Company Size
200-1,000
Region
- America
Country
- United States
Product
- Datadog
- GameChanger
- Amazon Web Services (AWS)
- MongoDB
- StatsD
Tech Stack
- AWS
- MongoDB
- StatsD
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
- Infrastructure as a Service (IaaS) - Cloud Computing
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Software
Applicable Functions
- Discrete Manufacturing
- Quality Assurance
Use Cases
- Predictive Maintenance
- Process Control & Optimization
- Real-Time Location System (RTLS)
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
GameChanger ( www.gamechanger.io ) produces a popular Android and iOS application used to record scores, statistics and more for amateur basketball, baseball and softball teams. GameChanger keeps score for tens of thousands of sports games per weekend, pushing real-time updates to fans online through texts, emails and its mobile application. The company runs a complex and elastically scaling cloud infrastructure hosted on Amazon Web Services (AWS) to support its mobile and web-based applications. This environment includes multiple databases and services, each of which requires monitoring.
The Challenge
GameChanger runs a complex and elastically scaling cloud infrastructure hosted on Amazon Web Services (AWS) to support its mobile and web-based applications. This environment includes multiple databases and services, each of which requires monitoring. Taking data from tens of thousands of sources, transforming it into reader-friendly snippets, and then pushing it to fans in real-time means GameChanger has to be ready to handle high traffic, heavy I/O and to troubleshoot issues at a moment’s notice. GameChanger first built its own infrastructure monitoring tools in-house from the open-source components Graphite and StatsD. These homegrown monitoring tools got the job done but at a steep price: they required an extra $1,000 of AWS resources and more than half an FTE’s hours each month just to keep GameChanger running.
The Solution
Engineers from GameChanger’s infrastructure group were the first to suggest Datadog. Savino found that Datadog’s monitoring solutions did exactly what GameChanger was trying to do in-house, but in an easy-to-use turnkey solution, at a lower cost and with no dedicated FTE time required. Datadog integrated seamlessly with AWS, MongoDB, StatsD and the many other services and databases that made up GameChanger’s infrastructure. This immediate integration made the company’s switch to Datadog quick and easy. Setting up essential monitoring displays and custom alerts was similarly straightforward. GameChanger no longer had to rely on costly and time-consuming in-house solutions; it instead could monitor its entire infrastructure with Datadog.
Operational Impact
Quantitative Benefit
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