<p>I'm new to devops .</p>
<p>I created a converter and want to deploy it . The converter converts a 3D model from a format to another and then you'll be able to visualize the outpout file on the platform and then you can download the file if you want to.</p>
<p>when bench-marking the process , i found out that for now it runs up to 1 minute when the files are really big , I'm using azure just moved to aws this week . For now the converter converts one file at a time and uses blender's python library and a c++ library ( when trying to use docker i built these inside the container )</p>
<p>I started by creating a docker container that will read a heavy blob and then output the converted file but figured out that docker is not designed to read local files .</p>
<p>I'm searching for the right model to host this . Is docker a good solution ? If not , is there other ways to do this ?</p>

CC BY-SA 4.0
2020-08-24T10:52:27.907Z
Seems like a job for AWS batch, ECS or Lambda? Can you provide some idea of how long the process lasts, what constraints on operations are?
Bruce Becker
CC BY-SA 4.0
2020-08-24T11:00:42.753Z
Hi Bruce , when bench-marking the process , i found out that for now it runs up to 1 minute when the files are really big , I'm using azure just moved to aws this week . For now the converter converts one file at a time and uses blender's python library and a c++ library ( when trying to use docker i built these inside the container )
tawfikboujeh
<docker><performance><scalability>
What is the best way to deploy a short living process when you have no machine?
tawfikboujeh
# What is the best way to deploy a short living process when you have no machine?

(Asked by: username_0 on 2020-08-24)

I'm new to devops .

I created a converter and want to deploy it . The converter converts a 3D model from a format to another and then you'll be able to visualize the outpout file on the platform and then you can download the file if you want to.

when bench-marking the process , i found out that for now it runs up to 1 minute when the files are really big , I'm using azure just moved to aws this week . For now the converter converts one file at a time and uses blender's python library and a c++ library ( when trying to use docker i built these inside the container )

I started by creating a docker container that will read a heavy blob and then output the converted file but figured out that docker is not designed to read local files .

I'm searching for the right model to host this . Is docker a good solution ? If not , is there other ways to do this ?

**Tags:** docker, performance, scalability

> **Comments:**
> **username_1**: Seems like a job for AWS batch, ECS or Lambda? Can you provide some idea of how long the process lasts, what constraints on operations are?  
> **username_0**: Hi Bruce , when bench-marking the process , i found out that for now it runs up to 1 minute when the files are really big , I'm using azure just moved to aws this week . For now the converter converts one file at a time and uses blender's python library and a c++ library ( when trying to use docker i built these inside the container )  

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## 0 answers

