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The goal of this project is to design and implement a scalable multi-cloud cost optimizer capable of calculating the best scheme for deploying a given arbitrary complex workload over a public (hybrid) cloud, thus reducing the involved monetary costs

Python 100.00%
aws optimizer cloud azure hybrid-cloud

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adiy10 avatar gilwer avatar octocat avatar ofekz1997 avatar yosefgoren avatar

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cloudcostoptimizer's Issues

Filter results by instance type or region (lists).

Feature request: allow the results to be filtered by instance type and region

For some workloads, only specific instance types or regions are required. An example would be an application running on OSD, where only some instance types and regions are supported. From https://docs.openshift.com/dedicated/osd_policy/osd-service-definition.html, the instance types must be M5, R5 or C5 and the supported regions (21) are also noted.

Note, that we can specify a specific region or "all" now, so it is possible to filter by region by running the optimiser multiple times and comparing the results, although this isn't ideal.

Filter results by hardware architecture

Feature request: allow the results to be filtered based on hardware architecture (e.g. x86_64, arm, mac).

AWS now offers x86_64- and Arm-based instances (see https://aws.amazon.com/ec2/instance-types/ for the list). Running pre-built containers means choosing an instance type with a matching hardware architecture. However, the current results do not distinguish hardware architecture, so results that cannot be used may be returned. For example, the a1.* (Arm) instances are currently cheaper than x86_64 (Xeon or EPYC) instances but cannot be used for x86_64 containers.

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