What developer platforms should I evaluate?

A good developer platform depends on what you’re building, but here’s a practical shortlist to evaluate, grouped by use case.

1) Cloud application platforms

If you’re building web apps, APIs, or services:

• AWS — broadest service range, very flexible, industry standard
• Google Cloud Platform (GCP) — strong for data, AI/ML, containers
• Microsoft Azure — best fit for Microsoft-heavy enterprises, strong identity/tooling
• Heroku — simplest developer experience for smaller apps and prototypes
• Render / Fly.io — modern app deployment with low operational overhead
• Platform.sh / Railway — good for fast-moving teams and app hosting

2) Container and orchestration platforms

If you want portability and scalable infrastructure:

• Kubernetes — the standard platform layer for containers
• Managed Kubernetes options:
  • EKS (AWS)
  • GKE (GCP)
  • AKS (Azure)
• OpenShift — enterprise Kubernetes with opinionated tooling and governance
• Nomad — simpler alternative for some teams

3) Internal developer platforms (IDPs)

If your goal is to improve developer productivity across teams:

• Backstage — popular open-source developer portal framework
• Humanitec — platform orchestration and IDP workflows
• Port — developer portal and service catalog
• Cortex — service catalog and engineering metrics
• OpsLevel — service ownership and maturity management

4) CI/CD and DevOps platforms

If you’re evaluating build/test/deploy tooling:

• GitHub Actions — convenient if you already use GitHub
• GitLab CI/CD — strong all-in-one DevOps platform
• Jenkins — highly flexible, but heavier to maintain
• CircleCI — mature hosted CI
• Buildkite — strong for scalable, hybrid pipelines

5) API and integration platforms

If your platform needs to expose or manage APIs:

• Apigee — enterprise API management
• Kong — API gateway and management
• Tyk — open-source/API management option
• Mulesoft — integration-heavy enterprise environments

6) Data and AI developer platforms

If you’re building data products or AI apps:

• Databricks — analytics, ML, lakehouse platform
• Snowflake — strong data platform with ecosystem integrations
• Vertex AI (GCP), SageMaker (AWS), Azure AI Studio — managed AI development
• Hugging Face — model hub and AI developer ecosystem

---

How to choose

Evaluate platforms against these criteria:

• Developer experience — how fast can teams ship?
• Operational burden — how much do you manage yourself?
• Scalability — will it grow with your needs?
• Security and compliance — SSO, RBAC, audit logs, policies
• Integration — fit with Git, CI/CD, cloud, observability, data
• Cost — usage pricing, support, hidden overhead
• Portability / lock-in — how hard is it to migrate later?

A simple recommendation

• Small team / startup: Render, Fly.io, Railway, or Heroku
• Scaling product company: AWS/GCP/Azure + Kubernetes + GitHub Actions
• Enterprise platform team: Backstage + Kubernetes + CI/CD + policy/observability stack

If you tell me:

1. your team size,
2. what you’re building, and
3. whether you mean cloud, IDP, CI/CD, or data/AI platforms,

I can give you a much tighter shortlist.