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If your use-cases requires multiple instances, you should try using the smallest possible flavor before moving up to a larger flavor. For example, given a scenario where you wanted to develop a web application, you could first try installing everything on a single m1.small instance. If you find your application is unable to effectively run in this flavor, you can do one of two things:
- Create a larger instance.
- Create another m1.small instance and move a portion of the web application to that new instance. For example, move the database service to a dedicated instance.
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We highly recommend using a DevOps methodology when using the Rapid Access Cloud. This includes using tools such as Terraform and Ansible. These tools will allow you to codify your configurations and provide the ability to automatically rebuild your deployments. |
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It's possible that the application reading your dataset can efficiently read it without exhausting all available memory. For example, if your dataset is 32 gigabytes in size but your instance only has 16 8 gigabytes of memory, the application might recognize this and automatically read only a small portion of data at a time.
However, if your application doesn't do this, we recommend breaking your dataset up into smaller pieces, sized appropriately for the amount of memory in available to your instance.
If your dataset cannot be broken up into smaller pieces, a final one other option is to add more swap space to your instance. Instructions on how to do this can be found here.
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