--- title: How Checkout.com tallies data with Cloud Composer 3 description: Checkout.com migrated its data orchestration from a self-managed Apache Airflow setup on another cloud provider to Google Cloud's Managed Service for Apache... canonical: https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How Checkout.com tallies data with Cloud Composer 3 | daily.dev og:description: Checkout.com migrated its data orchestration from a self-managed Apache Airflow setup on another cloud provider to Google Cloud's Managed Service for Apache... og:url: https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt og:image: https://api.daily.dev/og/posts/UvXIzhsQT.png og:image:alt: How Checkout.com tallies data with Cloud Composer 3 og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # How Checkout.com tallies data with Cloud Composer 3 **[Google Cloud](https://daily.dev/sources/gcp)** · 5 min read · 3 upvotes · 0 comments ## Summary Checkout.com migrated its data orchestration from a self-managed Apache Airflow setup on another cloud provider to Google Cloud's Managed Service for Apache Airflow (Cloud Composer 3). The move addressed key pain points: DAG sync times of ~6 minutes dropped to near-instant, dynamic auto-scaling reduced monthly infrastructure costs by ~30%, and DAG isolation prevented single failures from cascading across the environment. Containerized dbt execution eliminated manual virtual environment management, and Gemini Cloud Assist integration enables AI-powered troubleshooting directly from the Airflow UI, reducing mean time to recovery. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How much did Checkout.com reduce costs by switching from fixed worker provisioning to dynamic scaling in Managed Airflow? Checkout.com reduced monthly costs by an estimated 30% after moving from fixed provisioning, where workers were sized for peak load around the clock, to Managed Service for Apache Airflow's built-in dynamic scaling, which automatically adjusts worker count based on actual workload demand, scaling up during spikes and down when demand drops. _Teams weighing Airflow cost optimizations can compare real migration outcomes like this one on daily.dev._ ### How long did DAG syncing take in a self-managed Airflow setup using S3 compared to Managed Service for Apache Airflow with Cloud Storage? DAG syncing to the scheduler took approximately six minutes after deployment to S3 in a self-managed Airflow environment. After migrating to Managed Service for Apache Airflow (Gen 3) and using Cloud Storage for DAGs, syncing became near-instant, which improved iteration speed for data engineers deploying pipeline changes. _Engineers debugging slow deployment pipelines can track orchestration tooling changes like this on daily.dev._ ### How does Managed Service for Apache Airflow Gen 3 isolate dbt execution to avoid dependency conflicts across different dbt versions? Managed Airflow Gen 3 uses containerized dbt runs to eliminate dependency bottlenecks, giving each dbt model complete dependency isolation. This removes the need for engineers to manually install and manage separate virtual environments for every supported dbt version, letting teams run any required dbt model with minimal setup and no manual infrastructure overhead. _Data teams choosing between manual dbt environments and containerized execution can follow real-world approaches on daily.dev._ ## Similar posts on daily.dev - [Managed Apache Airflow: Scaling Data & AI Workloads](https://daily.dev/posts/managed-apache-airflow-scaling-data-ai-workloads-1s4kat53h) · Google Cloud · 0 upvotes · 0 comments - [Cloud Composer supports Apache Airflow 3.1](https://daily.dev/posts/cloud-composer-supports-apache-airflow-3-1-tfxltyyoe) · Google Cloud · 1 upvotes · 0 comments - [Snowflake Cortex Code CLI adds dbt and Apache Airflow support for AI-powered data pipelines](https://daily.dev/posts/snowflake-cortex-code-cli-adds-dbt-and-apache-airflow-support-for-ai-powered-data-pipelines-yrixxu8v0) · The New Stack · 1 upvotes · 0 comments - [GitLab on Google Cloud: Fully managed, compliant, and AI-ready](https://daily.dev/posts/gitlab-on-google-cloud-fully-managed-compliant-and-ai-ready-wsd2okrw4) · GitLab · 0 upvotes · 0 comments - [Leveraging Data Assets features in Airflow 3.0 to optimise resource utilization by more than 30%](https://daily.dev/posts/leveraging-data-assets-features-in-airflow-3-0-to-optimise-resource-utilization-by-more-than-30--daarqlw33) · Halodoc · 1 upvotes · 0 comments --- Tags: [#gcp](https://daily.dev/tags/gcp), [#apache-airflow](https://daily.dev/tags/apache-airflow) [View this post on daily.dev](https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"How Checkout.com tallies data with Cloud Composer 3","url":"https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt"},"datePublished":"2026-07-22T14:04:28.528Z","dateModified":"2026-09-14T08:33:16.084Z","description":"Checkout.com migrated its data orchestration from a self-managed Apache Airflow setup on another cloud provider to Google Cloud's Managed Service for Apache...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/faf229593c690bb3fe80ffab7f55f125?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/faf229593c690bb3fe80ffab7f55f125?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Google Cloud","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Google Cloud","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/gcp","url":"https://daily.dev/sources/gcp"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":3},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"gcp,apache-airflow","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Google Cloud","item":"https://daily.dev/sources/gcp"},{"@type":"ListItem","position":3,"name":"How Checkout.com tallies data with Cloud Composer 3"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/how-checkout-com-tallies-data-with-cloud-composer-3-uvxizhsqt#faq","mainEntity":[{"@type":"Question","name":"How much did Checkout.com reduce costs by switching from fixed worker provisioning to dynamic scaling in Managed Airflow?","acceptedAnswer":{"@type":"Answer","text":"Checkout.com reduced monthly costs by an estimated 30% after moving from fixed provisioning, where workers were sized for peak load around the clock, to Managed Service for Apache Airflow's built-in dynamic scaling, which automatically adjusts worker count based on actual workload demand, scaling up during spikes and down when demand drops. Teams weighing Airflow cost optimizations can compare real migration outcomes like this one on daily.dev."}},{"@type":"Question","name":"How long did DAG syncing take in a self-managed Airflow setup using S3 compared to Managed Service for Apache Airflow with Cloud Storage?","acceptedAnswer":{"@type":"Answer","text":"DAG syncing to the scheduler took approximately six minutes after deployment to S3 in a self-managed Airflow environment. After migrating to Managed Service for Apache Airflow (Gen 3) and using Cloud Storage for DAGs, syncing became near-instant, which improved iteration speed for data engineers deploying pipeline changes. Engineers debugging slow deployment pipelines can track orchestration tooling changes like this on daily.dev."}},{"@type":"Question","name":"How does Managed Service for Apache Airflow Gen 3 isolate dbt execution to avoid dependency conflicts across different dbt versions?","acceptedAnswer":{"@type":"Answer","text":"Managed Airflow Gen 3 uses containerized dbt runs to eliminate dependency bottlenecks, giving each dbt model complete dependency isolation. This removes the need for engineers to manually install and manage separate virtual environments for every supported dbt version, letting teams run any required dbt model with minimal setup and no manual infrastructure overhead. Data teams choosing between manual dbt environments and containerized execution can follow real-world approaches on daily.dev."}}]} ```