We detected 72 companies using AWS CodeBuild. The most common industry is Software Development (31%) and the most common company size is 2-10 employees (32%). We find new customers by discovering URLs with known URL patterns through web crawling or modifications to subprocessor lists.
Note: This tracks companies that added a AWS CodeBuild config file to their public Github repo. We also track companies that use AWS here
Source: Analysis of Linkedin bios of 72 companies that use AWS CodeBuild
Company Characteristics
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Shows how much more likely AWS CodeBuild customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Industry: Software Development
20.7x
Industry: IT Services and IT Consulting
17.0x
Company Size: 51-200
6.5x
Country: United States
3.7x
Company Size: 11-50
2.2x
I noticed that AWS CodeBuild users span an incredibly diverse range of activities, but they share a common thread: they're building software infrastructure that other people depend on. These aren't just app developers. They include companies creating payment processing platforms (Finix), cloud-native infrastructure tools (OpenObserve, Arpio), observability platforms, and developer tooling. Many are building B2B software solutions or platforms that enable other businesses to operate, like ProductPlan for product management or vcita for small business operations. There's also a surprising contingency of mission-driven organizations like Faith Comes By Hearing and Seed Company, suggesting that even nonprofits tackling complex software challenges need robust CI/CD capabilities.
The stage distribution is weighted toward growth-phase companies rather than early startups. While there are seed-stage companies like Comp AI and Shuttle, I see many more established players: mid-size companies with 50-200 employees, several Series A through C funded companies, and even massive enterprises like Intuit with over 18,000 employees. The funding data shows companies that have proven their models and are scaling, not just experimenting. Employee counts cluster in the 11-200 range, suggesting teams large enough to need sophisticated development infrastructure but small enough to stay agile.
🔧 What other technologies do AWS CodeBuild customers also use?
Source: Analysis of tech stacks from 72 companies that use AWS CodeBuild
Commonly Paired Technologies
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Shows how much more likely AWS CodeBuild customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that AWS CodeBuild users are infrastructure-focused engineering teams running sophisticated cloud-native operations. The extremely high correlation with Terraform tells me these companies treat infrastructure as code and automate everything they can. They're not just using AWS services casually. They're building serious, reproducible deployment pipelines where every component is version controlled and automated.
The pairing of CodeBuild with GitHub Actions and CircleCI is particularly revealing. These companies are running multiple CI/CD tools simultaneously, which suggests they either have complex multi-environment setups or they're transitioning between tools while maintaining legacy pipelines. The strong presence of Dependabot and GitHub Advanced Security shows they're serious about security and maintenance at scale. They can't afford manual dependency updates when managing dozens or hundreds of services. The Helm correlation confirms they're deploying containerized applications to Kubernetes, completing the picture of a modern, cloud-native infrastructure stack.
My analysis shows these are product-led companies in growth or mature stages. The tool combination screams engineering-first culture where developers ship frequently and infrastructure scales automatically. These aren't early startups cobbling together MVP deployments. They're past the scrappy phase and into systematic operations. They likely have dedicated DevOps or platform engineering teams whose job is maintaining the deployment machinery. They're probably B2B SaaS companies or technical infrastructure providers where uptime and deployment velocity directly impact revenue.
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