咨询Google Cloud高并发应用托管定价：18个microservices、7万日用户场景

Great question—figuring out cloud costs for a large microservices app can feel overwhelming at first, but Google Cloud has some solid tools and approaches to help you narrow this down. Let’s break this down step by step based on your setup (18 microservices, ~70k daily users):

This is your go-to tool for building a custom cost estimate tailored exactly to your app’s needs:

• First, map out each microservice’s expected resource usage. For App Engine, you’ll need to estimate details like instance type (standard vs. flexible), average request latency, daily request volume per service, and memory/CPU needs per instance. For other services (like Cloud Run, which is ideal for microservices), note CPU time, memory allocation, request counts, and network egress.
• Add each service you plan to use to the calculator—for your 18 microservices, you can create separate entries for each, adjusting parameters to match their specific load.
• Don’t forget supporting services: Include things like Cloud Storage for static assets, Cloud SQL/Firestore for databases, Cloud Load Balancing, and VPC networking—these all contribute to your total cost.

App Engine has two environments, each with distinct pricing models:

• Standard Environment: Costs are based on instance hours, memory allocation, and request counts. There’s a free tier for testing, but for your scale, focus on estimating peak vs. average instance counts (thanks to auto-scaling, you only pay for what you actually use).
• Flexible Environment: Pricing is tied to VM instance hours, CPU/memory per instance, and network traffic. This is a good fit if your microservices require custom runtimes or more consistent resource access.

If you’re open to alternatives, Cloud Run is a fantastic choice for microservices:

• It’s fully serverless, so you pay only for CPU-seconds and memory used during request execution, plus request counts. Auto-scaling handles traffic spikes seamlessly, which is perfect for a 70k-user app with variable load.
• Use the pricing calculator to input per-service details: average execution time, resource allocation per container, and daily request volume to get a precise estimate.

Once you have a rough number, these tools will help you stay on track:

• Cost Explorer: Once you’re in development, use this to track real-time spending. You can set budgets and alerts to avoid unexpected overages.
• Cloud Console Recommendations: This tab will suggest optimizations like right-sizing instances or cutting unused resources, helping you reduce costs without sacrificing performance.

Nothing beats real-world data:

• Deploy a handful of your microservices to App Engine or Cloud Run, route a small portion of your traffic to them, then use Cost Explorer to gather actual cost data. You can extrapolate this to your full 70k user base for a much more accurate total cost.

内容的提问来源于stack exchange，提问作者Eduardo Beckford