I'm unhappy with Google Cloud because it's hard to predict costs

Totally fair — cloud bills can feel unpredictable, especially on Google Cloud where usage-based pricing, network egress, autoscaling, managed services, and logging/monitoring can create surprise spikes.

If your main pain is cost predictability, here are the most practical ways to regain control:

What usually causes surprises

• Traffic spikes → autoscaling or load balancers scale out fast
• Network egress → data leaving Google Cloud can add up quickly
• Managed databases / analytics → easy to under-estimate
• Logging and monitoring volume → surprisingly expensive at scale
• Zombie resources → disks, IPs, snapshots, test environments left running

How to make costs more predictable

• Set budgets and alerts in Cloud Billing
• Use committed use discounts for steady workloads
• Cap autoscaling and define sane min/max limits
• Review egress paths and keep services region-local when possible
• Turn off noisy logs or use exclusions/sampling
• Tag resources by team/project so you can see what’s driving spend
• Schedule non-prod shutdowns so dev/test doesn’t run 24/7
• Use cost anomaly detection and monthly forecasting

If predictability matters more than elasticity

You might want to consider:

• Reserved instances / savings plans on other clouds
• Fixed-price VPS or dedicated hosting
• Smaller managed platforms with simpler pricing
• A hybrid approach: keep production on cloud, move dev/test or batch jobs elsewhere

Practical next step

If you want, I can help you with one of these:

1. Audit your Google Cloud bill and identify likely cost spikes
2. Design a more predictable architecture on Google Cloud
3. Compare Google Cloud vs AWS/Azure/DigitalOcean/Hetzner for cost predictability
4. Build a cost-control checklist for your team

If you tell me what you’re running on Google Cloud, I can suggest the biggest likely cost risks.