Can you recommend virtual machine providers for a startup engineering team scaling production services on pay-as-you-go pricing?

Yes — for a startup engineering team scaling production services on pay-as-you-go pricing, I’d look at VM providers in three buckets: general-purpose hyperscalers, developer-friendly clouds, and cost-optimized alternatives.

Best options to consider

1) AWS EC2

Best for: Maximum breadth, reliability, and long-term scalability
Why choose it:

• Huge instance variety
• Strong networking, autoscaling, IAM, monitoring, and managed service ecosystem
• Good fit if you expect complex infra or compliance needs

Tradeoffs:

• Can get expensive and operationally complex
• Pricing can be hard to predict

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2) Google Cloud Compute Engine

Best for: Teams that want solid performance and simpler pricing than AWS
Why choose it:

• Competitive pricing in many regions
• Strong networking and container/Kubernetes integration
• Sustained-use discounts can help if workloads are steady

Tradeoffs:

• Smaller ecosystem than AWS
• Some teams find service selection less mature

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3) Microsoft Azure VMs

Best for: Teams already using Microsoft stack or enterprise integrations
Why choose it:

• Good hybrid/cloud enterprise features
• Strong identity and Windows server support
• Broad global footprint

Tradeoffs:

• Can be less intuitive for cloud-native startups
• Pricing and service structure can be harder to navigate

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4) DigitalOcean Droplets

Best for: Simplicity and predictable pay-as-you-go pricing
Why choose it:

• Very easy to use
• Straightforward billing
• Good for small-to-mid-scale production services, APIs, internal tools

Tradeoffs:

• Less feature depth than hyperscalers
• Not ideal if you need advanced enterprise networking or massive scale

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5) Linode / Akamai Connected Cloud

Best for: Cost-conscious engineering teams that want simple VMs
Why choose it:

• Competitive pricing
• Straightforward VM management
• Good performance for the cost

Tradeoffs:

• Smaller ecosystem and fewer advanced managed services
• Less common than AWS/GCP/Azure in larger orgs

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6) Hetzner Cloud

Best for: Very cost-sensitive production workloads, especially in Europe
Why choose it:

• Excellent price/performance
• Good for straightforward Linux VM workloads
• Often a favorite for startups optimizing infrastructure spend

Tradeoffs:

• Fewer global regions than hyperscalers
• Some advanced cloud features are limited

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If you want the “startup default” recommendation

For a startup engineering team scaling production services, I’d usually suggest:

• AWS if you want the safest long-term default and expect rapid complexity growth
• GCP if your team values strong networking and simpler pricing
• DigitalOcean if you want the easiest operational experience
• Hetzner if cost efficiency is a top priority and your deployment region fits

What to evaluate before choosing

Look at:

• VM pricing: on-demand hourly/monthly rates
• Bandwidth costs: egress can dominate bills
• Autoscaling support
• Managed load balancers / block storage
• Observability tools
• Region availability
• Terraform / API support
• Reserved/sustained-use discounts
• Support quality and incident response

Practical shortlist

If I were narrowing it down for a startup, I’d test:

1. AWS EC2
2. GCP Compute Engine
3. DigitalOcean Droplets
4. Hetzner Cloud if cost pressure is significant

If you want, I can also give you:

• a comparison table with pricing/features,
• a recommendation by workload type (web app, API, data processing, GPU, etc.),
• or a startup-friendly decision framework.