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The size of the docker image you're referring to seems to be the file size, which wouldn't be impacted by memory limitations. The term memory refers to the component within your computer that allows for short-term data access and is typically used in computing to store working data for a system[1]. [1] https://en.wikipedia.org/wiki/Random-access_memory
When you have a file and save it in a file system it isn't normally stored in memory unless it's been recently accessed, and memory is able to cycle out old cached content as new content is requested[2]. [2] https://www.oreilly.com/library/view/understanding-the-linux/0596002130/ch14s02.html
Now onto the differences between task size and container size. When you register a task definition, you can specify the total CPU and memory used for the task. This is separate from the cpu and memory values at the container definition level. A single ECS task may have many containers running to complete, and in these cases the "Container Size" parameter would limit each container's resource consumption, while the "Task Size" parameter would limit how many total resources your Task may use[3]. [3] https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task_definition_parameters.html
In regards to performance issues or launch failures, unless you load too much into RAM at once your task should still run fine, even with your image file being 8 GB. Something good to note though, Task-level CPU and memory parameters are ignored for Windows containers. We recommend specifying container-level resources for Windows containers.
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