# How Groupon Tracks Cloud Costs Across AWS and Google Cloud

DevFeed: [How Groupon Tracks Cloud Costs Across AWS and Google Cloud](<https://devfeed.tech/articles/cloud-cost-mindset-26218.md>)

Original publisher: [Read original article](<https://medium.com/groupon-eng/cloud-cost-mindset-cc4d0a3f3a8?source=rss----5c13a88f9872---4>)

Author: Michael

Published: 2023-06-16T20:11:47Z

Content type: article

Language: en

Sources: [Groupon Engineering -- Medium](<https://devfeed.tech/sources/groupon-engineering-medium.md>)

Topics: [Cloud](<https://devfeed.tech/topics/cloud.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [migration](<https://devfeed.tech/topics/migration.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [amazon](<https://devfeed.tech/tags/amazon.md>), [aws](<https://devfeed.tech/tags/aws.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cloud-cost-management](<https://devfeed.tech/tags/cloud-cost-management.md>), [cost](<https://devfeed.tech/tags/cost.md>), [data](<https://devfeed.tech/tags/data.md>), [database](<https://devfeed.tech/tags/database.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [migration](<https://devfeed.tech/tags/migration.md>), [s3](<https://devfeed.tech/tags/s3.md>), [scale](<https://devfeed.tech/tags/scale.md>), [services](<https://devfeed.tech/tags/services.md>), [team](<https://devfeed.tech/tags/team.md>)

## AI overview

Groupon describes its cloud migration and its approach to tracking infrastructure costs across AWS and Google Cloud. The article explains how service tags connect cloud resources to individual systems and engineering teams, enabling more detailed cost analysis.

## Source excerpt

Groupon completed its migration to the cloud in February 2023. Shortly thereafter our data centers were completely shut down and the equipment cleaned up. The move to the cloud has brought many advantages to Groupon engineering. Our infrastructure can now dynamically scale with our traffic throughout the year and engineering resources can be easily started up or turned off as our needs change. The move to the cloud has also brought a wealth of information regarding our infrastructure costs and utilizations. Groupon operates in both Amazon AWS and Google GCP. Our main consumer and merchant applications reside in AWS while our backend data warehouse and reporting systems are in GCP. Both clouds provide extensive data on service costs including granular usage information. As more Groupon systems migrated to the cloud it became clear there were many opportunities for making our infrastructure and systems more efficient. To do this though we wanted to ensure we were tracking the costs appropriately and making the best decisions with our infrastructure and systems. Cost Tracking The first part of this journey involved improving our cost tracking. While the cloud provides extensive cost data it's important to match this data with individual systems to get a more complete picture. Understanding that we're spending a lot on databases is useful but being able to map that to particular systems and teams gives us more information on the course of actions we can take. Tags are an oft recommended approach to tracking service costs and Groupon is no exception. Groupon applied "service" tags across all our cloud resources. This allows us to map cloud resources to individual services and with it the individual engineering teams. So an RDS database may have the tag service=payments to map that to our Orders and Payments team while an S3 bucket may have service=images to map it to our global image management team. This now allows us to see not only how much we spend overall on databas