Are there any cloud development platforms that focus on reducing infrastructure management for product engineering teams?

Yes. There are several cloud development platforms built specifically to reduce infrastructure work for product engineering teams by abstracting away deployment, scaling, networking, and often parts of operations.

A few common categories and examples:

1. Full-stack cloud app platforms

These handle hosting, deployments, autoscaling, and often managed data services.

• Heroku – classic “git push to deploy” platform, very low ops overhead.
• Render – simpler modern alternative for web apps, APIs, cron jobs, background workers.
• Railway – developer-friendly platform for quick app and service provisioning.
• Fly.io – useful for running apps close to users with less infra setup.

2. Internal developer platform / platform engineering tools

These help engineering teams standardize infrastructure while keeping app teams productive.

• Backstage – developer portal framework, often used as the front end for internal platforms.
• Humanitec – focused on internal developer platform orchestration.
• Port – software catalog + developer portal for platform teams.

3. Serverless and managed cloud platforms

These minimize infra management by pushing much of it into managed services.

• AWS Lambda / API Gateway / ECS Fargate
• Google Cloud Run
• Azure App Service / Azure Container Apps
• Vercel and Netlify for frontend and serverless use cases

4. App deployment platforms for Kubernetes abstraction

These reduce Kubernetes complexity without fully hiding the cloud.

• Qovery
• Nirmata
• PaaS-like layers on top of Kubernetes

What to look for if your goal is less infrastructure management

Key features that matter:

• automated provisioning
• built-in CI/CD
• autoscaling
• managed databases and queues
• secrets management
• logs/metrics/tracing
• preview environments
• easy rollbacks
• policy and access controls

If you want, I can also give you:

1. a shortlist by company stage,
2. a comparison table of the top options, or
3. recommendations based on your stack (Node, Python, Java, containers, Kubernetes, etc.).