Datadog Case Studies Glovo scales on-demand delivery app and eliminates downtime with Datadog Database Monitoring

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	Glovo scales on-demand delivery app and eliminates downtime with Datadog Database Monitoring Datadog

Glovo scales on-demand delivery app and eliminates downtime with Datadog Database Monitoring

Datadog

Technology Category	Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	Food & Beverage Pharmaceuticals Retail
Applicable Functions	Logistics & Transportation Sales & Marketing
Use Cases	Predictive Maintenance Real-Time Location System (RTLS) Supply Chain Visibility
Services	Cloud Planning, Design & Implementation Services Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

Food & Beverage

Pharmaceuticals

Retail

Applicable Functions

Logistics & Transportation

Sales & Marketing

Use Cases

Predictive Maintenance

Real-Time Location System (RTLS)

Supply Chain Visibility

Services

Cloud Planning, Design & Implementation Services

Data Science Services

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.

About 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.

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.

Impact #1	Glovo engineers now have full visibility into their databases and can quickly identify and optimize inefficient queries to reduce computational load.
Impact #2	Glovo is using DBM for capacity planning and to enable resource optimization across the organization.
Impact #3	The infrastructure team supports other teams across the business in provisioning and maintaining their own infrastructure.

Impact #1

Glovo engineers now have full visibility into their databases and can quickly identify and optimize inefficient queries to reduce computational load.

Impact #2

Glovo is using DBM for capacity planning and to enable resource optimization across the organization.

Impact #3

The infrastructure team supports other teams across the business in provisioning and maintaining their own infrastructure.

Benefit #1	Reduced downtime from 3 hours to 0
Benefit #2	Reduced CPU usage from 65% to 60%
Benefit #3	Increased number of databases from 1 to 90 while improving performance

Benefit #1

Reduced downtime from 3 hours to 0

Benefit #2

Reduced CPU usage from 65% to 60%

Benefit #3

Increased number of databases from 1 to 90 while improving performance

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Overview

Glovo scales on-demand delivery app and eliminates downtime with Datadog Database Monitoring

Operational Impact

Quantitative Benefit