78.2K
RUServerless != No Servers, It just means "Not Your Servers."
Most developers think "Serverless" just means saving money. That’s only half the truth. The real benefit is shifting the responsibility of "uptime" to the cloud provider.
Here is the technical breakdown of what actually changes in your architecture:
1. Compute: EC2 vs. Lambda
The Old Way (EC2): You pay for "Capacity." If you rent a server for 24 hours but only get traffic for 2 hours, you wasted money on the other 22 hours. You also have to patch the OS.
The Serverless Way (Lambda): You pay for "Execution." If your code runs for 200ms, you pay for exactly 200ms.
⚠️ The Catch: Cold Starts. If your function hasn’t run in a while, AWS needs to spin up a container. This adds latency (sometimes 100ms - 2s). For super low-latency apps, this can be a problem.
2. Storage: EBS vs. S3
The Old Way (EBS): This is Block Storage. It's like a hard drive attached to your computer. You pay for the size of the disk (e.g., 500GB), even if it's empty.
The Serverless Way (S3): This is Object Storage. You pay only for the storage used and the API requests (GET/PUT) to access it.
3. Database: RDS vs. DynamoDB
The Old Way (RDS): Even when idle, the database instance is running. You pay an hourly rate for the CPU and RAM.
The Serverless Way (DynamoDB On-Demand): You pay per Read/Write unit.
⚠️ The Catch: Cost at Scale. Serverless databases are cheap for low to medium traffic. But if you have massive, constant throughput (millions of requests per hour), a provisioned server (like RDS or DynamoDB Provisioned Mode) is often mathematically cheaper than Serverless On-Demand.
The Verdict? Go Serverless for variable traffic, startups, and background tasks. Stick to provisioned servers for sustained, predictable high loads.
#softwareengineering #aws #serverless #lambda #cloudcomputing
@rushi.says
