Which of the following would speed up this process?
Create a pipeline to build a custom AMI with the framework installed and use this AMI as a baseline for application deployments.
Employ a user data script to install the framework but compress the installation files to make them smaller.
Create a pipeline to parallelize the installation tasks and call this pipeline from a user data script.
Configure an AWS OpsWorks cookbook that installs the framework instead of employing user data. Use this cookbook as a base for all deployments.
Explanations:
Creating a custom AMI (Amazon Machine Image) with the framework pre-installed eliminates the need for repeated installations during application deployments, significantly reducing deployment time. Each deployment can simply launch a new instance from this AMI, making the process much faster.
While compressing the installation files might reduce the time taken to transfer files, the actual installation process remains unchanged. Since the installation takes a fixed amount of time (30 minutes), this option does not effectively address the bottleneck in deployment speed.
Parallelizing installation tasks might seem like a viable option, but since the framework installation is likely a sequential process that takes 30 minutes, parallelizing tasks would not significantly reduce the overall installation time. Additionally, if the framework installation depends on previous steps, it might introduce complexity without providing a real speedup.
Although using AWS OpsWorks with cookbooks can automate the installation process, it still relies on the same underlying installation mechanism. If the cookbook does not streamline the installation significantly compared to the current user data script, it won’t solve the bottleneck issue effectively. Moreover, it may require additional setup and management overhead.
In my opinion, the answer is:
Create a pipeline to build a custom AMI with the framework installed and use this AMI as a baseline for application deployments.