CODEWITHSUNDEEP
azureoptimizationazure-functionsazure-cosmosdb
MolteNolte
MolteNolte

Reputation: 183

CosmosDB: Optimizing RUs with a time triggered FunctionApp?

We have a FunctionApp which inserts every 6 minutes around 8k documents in a CosmosDb. Currently we set Cosmos to autoscale, but since our RUs are very predictable I have the feeling we could save some money because it's quite expensive. I found out it's possible to set the througput to manually and according to this article I could decrease/increase the RUs with a timer. But now I'm wondering if its a good idea because we have small time interval and even if I time the FunctionApp correctly (error prone?) there are maybe 3 minutes where I can decrease the throughput. Another thing is that manual throughput costs 50% RUs less.

What do you think, is it worth implementing a time-triggered FunctionApp which increase/decrease the throuhput or its not a good idea in terms of error prone etc? Do you have any experience with it?

Upvotes: 0

Views: 48

Answers (1)

Mark Brown
Mark Brown

Reputation: 8763

The timer with manual throughput will likely save you money because throughput is billed as the highest amount of RU/s per hour. Since your workload needs to scale up every 6 minutes your cost is the highest RU/s during that hour. Given that autoscale is 50% more expensive, you'd save by manually scaling up and down.

However, if you were able to stream this data to Cosmos rather than batch it you would save even more. Throughput is measured per second. The more you are able to amortize your usage over a greater period of time, the less throughput you need at any given point in time. So if you were able to use say a message queue and do load-leveling in front of Cosmos and stream the changes in, you will have better throughput utilization overall and thus lower total cost. Of course you'd need to evaluate the cost for utilizing a message queue to do this but in general, streaming is the more cost effective than batching.

Upvotes: 2

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