Companies that use Amazon EKS

Source: Analysis of job postings that mention Amazon EKS (using the Bloomberry Jobs API)

I analyzed the hiring patterns and found that Amazon EKS purchasing decisions sit squarely with engineering leadership. Directors of Engineering (20%), VPs of Engineering (15%), Directors of DevOps (12%), Directors of Cloud Engineering (10%), and Heads of Platform Engineering (8%) dominate the buyer landscape. These leaders are focused on platform standardization, cost optimization through FinOps practices, and enabling developer velocity while maintaining security and compliance. Their strategic priorities center on modernizing legacy systems, establishing multi-account landing zones, and creating self-service infrastructure that scales with business growth.

The daily users of Amazon EKS are DevOps engineers, SREs, platform engineers, and cloud infrastructure specialists. I noticed they're managing cluster upgrades, implementing observability and monitoring, building CI/CD pipelines integrated with GitHub Actions or GitLab, writing Terraform for infrastructure as code, and supporting production workloads at massive scale. Several postings mentioned managing tens of thousands of containers or operating some of the largest Kubernetes deployments globally. These practitioners focus on automation, security guardrails, and reducing operational toil through policy enforcement.

The pain points reveal a clear pattern around migration complexity and operational maturity. Companies repeatedly mention "migrating approximately 4,200 servers from three Tennessee data centers to AWS" and seeking "resilient, scalable, secure cloud-native workloads." I saw phrases like "reduce customer adoption friction, dramatically shorten software iteration cycles" and "paved-road, self-service experience that gets application teams to production safely and quickly." Organizations want EKS to solve the dual challenge of accelerating developer productivity while maintaining enterprise-grade reliability and security for mission-critical financial and healthcare systems.

Source: Analysis of Linkedin bios of 484 companies that use Amazon EKS

I noticed that Amazon EKS users span a remarkably diverse range of sectors, but they share a common thread: they're building digital-first products that require scale and reliability. These aren't companies dabbling in tech, they're companies where software is the core business. I see fintech platforms processing billions in payments, healthcare companies serving millions of patients, SaaS providers managing massive data operations, and marketplaces connecting buyers and sellers. Whether it's Remitly moving money across borders, Verkada streaming security video, or Property Finder powering real estate searches across MENA, these companies depend on their infrastructure staying up and performing under pressure.

The funding and size data reveals a growth-stage sweet spot. While I see some mature companies like Constellation Brands and established unicorns like Ripple, the majority are Series A through Series D companies with 50 to 500 employees. They've proven product-market fit and are now scaling rapidly. They're past the scrappy startup phase but not yet enterprise behemoths. They're in that crucial window where infrastructure choices either enable or constrain growth.

Source: Analysis of tech stacks from 484 companies that use Amazon EKS

I noticed that Amazon EKS users are primarily fast-growing B2B SaaS companies with sophisticated technical operations and aggressive sales motions. The presence of Kubernetes External DNS alongside EKS tells me these companies are running complex, production-grade Kubernetes environments where they need automated DNS management for their services. This isn't hobbyist infrastructure. These are serious engineering organizations managing multiple environments and services at scale.

The pairing of Monte Carlo Data with EKS is particularly revealing. Companies using both are running data-intensive operations on Kubernetes and care deeply about data quality and observability. They're likely serving enterprise customers who demand reliable data pipelines. Similarly, Statsig's presence suggests these companies are running extensive experimentation programs, using their Kubernetes infrastructure to A/B test features rapidly. The combination points to product-led growth tactics backed by solid engineering infrastructure.

What's most interesting is the sales and marketing stack. Chili Piper and Impact appearing so frequently tells me these aren't purely product-led companies. They're running outbound sales motions with sophisticated meeting scheduling and partner/affiliate programs. CyberHaven's presence suggests they're security-conscious, likely because they're selling to enterprises with strict compliance requirements. The full picture is of growth-stage companies (Series B to D) that have proven product-market fit and are now scaling go-to-market aggressively while maintaining technical sophistication.