The very first cold start happens when the very first request comes in after deployment.

After that request is processed, the instance stays alive for the time being to be reused for subsequent requests. But for how long?

The first cold start happens when the very first request comes in after deployment.

After that request is processed, the instance stays alive for the time being to be reused for subsequent requests. But for how long?

The first cold start happens when the very first request comes in.

After that request is processed, the instance stays alive for the time being to be reused for subsequent requests. But for how long?

The following chart shows the typical range of cold starts in Google Cloud Functions, broken down per language. The darker ranges are the most common 67% of durations, and lighter ranges include 95%.

Google Cloud Functions have a setting to define the memory size that gets allocated to a single instance of a function. The CPU resources are allocated proportionally to the memory. So, in theory, larger instances could start faster.

The following chart shows the typical range of cold starts in Azure Functions, broken down per language. The darker ranges are the most common 67% of durations, and lighter ranges include 95%.

The following chart shows the typical range of cold starts in AWS Lambda, broken down per language. The darker ranges are the most common 67% of durations, and lighter ranges include 95%.

AWS Lambda has a setting to define the memory size that gets allocated to a single instance of a function. The CPU resources are allocated proportionally to the memory. So, in theory, larger instances could start faster.

AWS Lambda might need to access resources inside Amazon Virtual Private Cloud (Amazon VPC). In the past, configuring VPC access slowed down the cold starts significantly.

We are testing cold starts on cloud functions responding to HTTP requests because that’s where the increased latency matters the most.

Each cloud function responds with a simple 200 OK with the following custom response headers:

Auto-provisioning and auto-scalability are the killer features of Function-as-a-Service cloud offerings, and Azure Functions in particular.

One drawback of such dynamic provisioning is a phenomenon called “Cold Start”. Basically, applications that haven’t been used for a while take longer to startup and to handle the first request.