Companies that use Pulumi

Source: Analysis of 100 job postings that mention Pulumi

My analysis shows that Pulumi is primarily purchased by infrastructure and platform engineering leaders, with Directors of Platform Engineering (18%), Directors of DevOps (12%), and Heads of Cloud Infrastructure (10%) representing the core buyer personas. These leaders are focused on strategic priorities like cloud migration, developer productivity, and building internal developer platforms. They consistently mention goals around enabling self-service infrastructure, reducing cognitive load on developers, and standardizing infrastructure as code practices across their organizations.

The day-to-day users are DevOps engineers, platform engineers, site reliability engineers, and cloud architects who use Pulumi to provision multi-cloud infrastructure, build CI/CD pipelines, and create reusable infrastructure modules. These practitioners leverage Pulumi alongside Kubernetes, Terraform, and various cloud platforms to automate deployment workflows and manage infrastructure at scale. Many postings emphasize hands-on work with container orchestration, service mesh configurations, and building golden paths for development teams.

The pain points reveal organizations struggling with complexity and scale. Companies describe needing to "abstract away complexity" and provide "paved roads that make delivery fast, secure, observable, and cost-efficient." Multiple postings mention building platforms that are "secure, scalable, automated, and cost-efficient" while enabling "developer self-service" capabilities. The recurring theme is reducing operational toil through automation, as one posting explicitly states the role is "ideal for a developer who understands the toil of infrastructure and is passionate about removing barriers with automation."

Source: Analysis of tech stacks from 2,974 companies that use Pulumi

I noticed that Pulumi users are distinctly product-led, engineering-first companies that have moved beyond startup chaos into a more mature operational phase. The combination of Linear for issue tracking, Spacelift for infrastructure orchestration, and SonarQube Cloud for code quality shows these companies care deeply about developer experience and engineering excellence. They're building serious technical products and want their internal tools to match that ambition.

The pairing of Pulumi with Spacelift is particularly revealing. These companies aren't just managing infrastructure as code, they're treating it as a first-class engineering discipline with proper CI/CD, policy enforcement, and collaboration workflows. The strong correlation with Sentry tells me they're running production systems at scale and need real-time error tracking. Meanwhile, Retool's presence suggests they've reached a stage where internal tools matter. They're building custom dashboards and admin panels rather than making engineers hand-code everything or forcing ops teams into clunky database interfaces.

My analysis shows these are product-led growth companies in their scale-up phase, likely Series A through C. They've proven product-market fit and are now investing in operational maturity. The Vercel Pro correlation indicates they're shipping frequently and care about developer velocity. Linear's overwhelming presence tells me they've rejected heavyweight project management tools like Jira in favor of something built for how modern engineering teams actually work. These companies prioritize shipping speed and developer happiness as competitive advantages.

Source: Analysis of Linkedin bios of 2,974 companies that use Pulumi

I noticed that Pulumi users span a remarkably diverse range of industries, but they share a common thread: they're building technology products that require sophisticated cloud infrastructure. These aren't companies that just use software. They're companies that build it, whether that's SaaS platforms for insurance claims, AI-powered legal prediction engines, blockchain infrastructure, or developer tools. Many are creating customer-facing applications with complex backend requirements, real-time data processing, or AI/ML capabilities that demand scalable, programmable infrastructure.

The funding and size data reveals these are predominantly growth-stage companies. Most employ between 11-200 people, with a sweet spot around 50- employees. When funding information is available, I see mostly Seed and Series A rounds, typically in the $3-10M range. A few larger enterprises appear in the mix, but the majority are scaling startups that have found product-market fit and are now building out their infrastructure to support growth.