消耗计划中的Azure函数执行会相互干扰

Question

I have a serious issue with Azure Functions. Let me sketch my scenario.

I have a workload for processing incoming data files in a blob container. Using a BlobTrigger my processing function picks up the file, processes it and removes it from the container. Everything for one single file within 2 minutes of processing on the consumption plan.

Everything ok there, so I'm happy. Now I want to scale things up and offer +/- 10 of these batches in the blob container. The runtime starts executing them in parallel, so still works as expected. But then: the parallel executions of these functions slow down apparently, so the processing time of a single workload exceeds the max. execution time of 10 minutes! That's (more than) a factor 5 slowing things down, dependent on the amount of jobs offered.

Am I missing the point here? This is what the functions were built for or is it just some toy or something? I resorted to annotating my function with [Singleton] for now, which completely discards any scaling benefits here? How on earth could it be that 'serverless' execution units interfere with one another?

I am very puzzled, any insights would be greatly appreciated.

Answer 1

You should look into Azure function scaling algorithm

First-time Azure function allocates small instance (1.5 GB) to process workload, It would take some time to understand scaling requirement then only Azure ScaleController would add/remove the instance. For single blob 1.5 GB instance takes 2 mins, with 10 blob same instance (1.5 GB) would share resources and it would take time.

I don't see batch size setting for blob trigger in host.josn but I tried small batch size and solve a similar issue with ServiceBus.

You can send more workload on blob and with the help of application Insight, you can check Azure function scale out time.

I hope you already checked blob trigger issues.