Question 1

What cloud platforms do hyper-growth companies most commonly use?

Accepted Answer

AWS remains the dominant cloud platform at most hyper-growth companies, particularly those that started before 2020. GCP is common at AI-native companies and those with large-scale data workloads. Azure is more prevalent at enterprise-focused B2B companies. Many scale-ups use a multi-cloud approach for specific workloads (e.g., GCP for ML training, AWS for production services). Kubernetes is nearly universal for container orchestration at Series B and beyond.

Question 2

What is the difference between a cloud engineer and a site reliability engineer (SRE) at a hyper-growth company?

Accepted Answer

A cloud engineer typically focuses on provisioning and managing cloud infrastructure — designing architectures, writing Terraform, managing networking and security. An SRE focuses on the reliability and operational health of production systems — on-call rotations, incident response, defining SLOs, and reducing toil through automation. At smaller hyper-growth companies, these roles often overlap significantly, with a single platform or infrastructure team covering both responsibilities.

Question 3

How much Kubernetes experience is needed for infrastructure roles at hyper-growth companies?

Accepted Answer

For senior infrastructure and platform engineering roles at Series B+ companies, hands-on Kubernetes experience is typically expected rather than optional. This includes deploying and managing clusters (EKS, GKE, or self-managed), writing Helm charts, configuring networking (Ingress, service meshes), and managing resource limits and autoscaling. For junior roles, familiarity with containers and Docker is the baseline, with Kubernetes experience treated as a strong advantage.