You can implement your backend using raw VMs, or use higher-level abstractions like serverless. If you choose the former, you’re talking on a lot of DevOps work: • VM instance types are bound to a specific hardware version. One company I work with is running m4 instances from years ago, paying more to run on older hardware with lower performance. We need to manually migrate to newer hardware. On the other hand, with serverless platforms like Lambda, you specify a minimum set of requirements, like 10 GB memory and 6 vCPUs. You don’t specify the hardware generation like m4 or m5. This way, your code can automatically benefit from newer hardware generations.
VMs Create a Lot of DevOps Work
VMs Create a Lot of DevOps Work
VMs Create a Lot of DevOps Work
You can implement your backend using raw VMs, or use higher-level abstractions like serverless. If you choose the former, you’re talking on a lot of DevOps work: • VM instance types are bound to a specific hardware version. One company I work with is running m4 instances from years ago, paying more to run on older hardware with lower performance. We need to manually migrate to newer hardware. On the other hand, with serverless platforms like Lambda, you specify a minimum set of requirements, like 10 GB memory and 6 vCPUs. You don’t specify the hardware generation like m4 or m5. This way, your code can automatically benefit from newer hardware generations.