Glovo scales on-demand delivery app and eliminates downtime with Datadog Database Monitoring
Customer Company Size
Large Corporate
Region
- Europe
- Asia
- Middle East
Country
- Spain
Product
- Datadog Database Monitoring
- Datadog Application Performance Monitoring
- Datadog Infrastructure Monitoring
- Datadog Log Management
Tech Stack
- Microservices
- Database Management
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Retail
- Food & Beverage
- Pharmaceuticals
Applicable Functions
- Logistics & Transportation
- Sales & Marketing
Use Cases
- Real-Time Location System (RTLS)
- Predictive Maintenance
- Supply Chain Visibility
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Glovo is an on-demand courier service that purchases, picks up, and delivers products ordered through its mobile app. The company connects users with businesses and couriers offering on-demand services from local restaurants, grocers and supermarkets, pharmacies and retail stores. Operating in 25 countries across Europe, the Middle East and Asia, Glovo is a rapidly growing organization. The company initially designed its application using a monolithic architecture but to keep pace with rapid growth, Glovo engineers recently began migrating their application to a microservice-based architecture.
The Challenge
Glovo, an on-demand courier service operating in 25 countries, was facing a significant challenge as its database resource consumption couldn't keep pace with its projected growth. As the company launched a migration to microservices, it needed better visibility into its databases to reduce CPU usage and prevent costly downtime. With an increased number of databases and queries running, they found databases were provisioned incorrectly and would often reach CPU capacity. This resulted in outages adding up to three or four hours of downtime in 2022. The existing monitoring products Glovo used didn’t provide the insight they needed. Limited access to real-time monitoring and alerting hindered the team’s response to issues. They also lacked the ability to track and compare current and historical performance data, making investigations manual and tedious.
The Solution
Glovo was already using Datadog Application Performance Monitoring (APM), Infrastructure Monitoring, and Log Management. They decided to extend their existing observability tooling to Datadog Database Monitoring (DBM) as it had the same easy-to-use interface they were already familiar with as well as features like granular data of the queries, explain plans, query costs, wait times, etc. With Datadog DBM, Glovo engineers now have full visibility into their databases and can quickly identify and optimize inefficient queries to reduce computational load. Glovo is also using DBM for capacity planning and to enable resource optimization across the organization. For example, the infrastructure team supports other teams across the business in provisioning and maintaining their own infrastructure. DBM helps the infrastructure team work with other business areas to ensure their workloads run efficiently and resources are allocated appropriately, thereby reducing costs.
Operational Impact
Quantitative Benefit
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