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Estimate the environmental impacts of live apps on premise

10 January, 2023

This article is the second part of a serie. See Intro here.

⚠ DRAFT ⚠

Possible plan of article :

Context

This article presents tools we use to estimate environmental impacts of Backend applications.

Assumptions:

All the tools presented, require that we have low level access to the hardware and to the first layer of software (OS or Virtualization layer).

This excludes the scenario where we are using virtualized infrastructure as a service (IAAS). However theses approaches will work in the case where we use bare metal instances, even if provided as a service.

Measure based approaches

We can adopt a measure-based approach. In practice we are often limited to measure the Energy consumed by our IT. We can measure it globally (top-down) or locally (bottom-up).

In both case we need to find a way to attribute the energy consumption to a specific device or application. This implies a precise inventory of our physical assets and services.

Power meters

A first possibility is to use physical power meters. They can be attached to a DataCenter, a rack or even a physical server.

Pros:

Cons:

Software meters

Recent hardware come with meters that monitor power usage and can be queried by software.

Research paper show for example that the global electrical consumption of servers is closely linked to the consumption of CPU and RAM. So theses figures are sufficient to estimate the server consumption.

Pros:

Cons:

Main tools:

Hybrid with model-based approaches

Mixed approach where we measure what we can (genrally workload) from the OS and the remaining impacts from a model. This brings the added value of having a multicriteria approach (like in Boavizta dataset).