GO-JEK is a startup that specializes in ride-hailing, logistics and digital payments in Indonesia with recent expansion into Vietnam, Singapore and Thailand. Established in 2010 as a motorcycle ride-hailing phone service, GO-JEK has evolved into an on-demand mobile platform and a cutting-edge app, providing a wide range of services that includes transportation, logistics, mobile payments, food delivery and many other on-demand services.
They use InfluxDB for storing and collecting metrics from systems and applications. They use these infrastructure and business metrics for monitoring and alerting, gathering 55,153 points per second during peak times, all written into an InfluxDB instance. With such a heavy load, they faced the issue of high memory and disk space utilization, and instead of scaling the InfluxDB cluster horizontally, they solved the disk space problem by downsampling their metrics data.
GO-JEK used InfluxDB and Grafana to build their monitoring solution – a solution that saved them from downtimes, rising machine costs and countless pages buzzing in the night forcing them to burn the midnight oil to address performance issues. They automated this solution using Chef and Terraform for all the InfluxDB and Grafana instances.
They use InfluxDB every team, each of which has 2 InfluxDB instances with relay in between. GO-JEK uses InfluxDB to:
- Store application and infrastructure metrics
- Dashboard with Grafana
- Downsample the data to help with storage
- Use the Ruby client
- Use Terraform
190 million +
Number of customers using ride-hailing, logistics and digital payment platform
55,000 +
System and app data points collected during peak times per second
Reduced downtime
Better observability resulting in less operational costs and performance issues
“We had used Grafana, Kapacitor and InfluxDB, but after we started facing the issues of high memory and disk utilization, that’s when we explored the solution of data downsampling.”