Awesome and Dark Tactics
Homepage Catalog Tag Selection Contributions
All Tags AWS algorithm-design architecture cloud-principles cost-reduction data-centric data-compression data-processing deployment design edge-computing energy-footprint hardware libraries locality machine-learning management measured migration model-optimization model-training performance queries rebuilding scaling services strategies template workloads

<- Back to category

Tactic: Choose fitting deployment paradigm

Tactic sort: Awesome Tactic
Type: Architectural Tactic
Category: resource-adaptation
Tags: cloud-principles  measured 

Title

Choose fitting deployment paradigm

Description

The currently most prominent deployment paradigms are VM, container, and serverless architectures. Choosing the fitting paradigm for the workload will optimize the performance. There is no one-size-fits-all solution regarding choosing the fitting deployment paradigm. A serverless architecture ensures that services are automatically shut off when they are finished. Moreover, when using a serverless architecture the service utilization is much lower compared to using a VM as the overhead is much smaller. This is expected to have a positive effect on the energy consumption. A possible negative effect of a serverless architecture on energy efficiency occurs in the scenario where the service is frequently called but not constantly on. Starting the service up and down could consume relatively more energy compared to spinning one VM that is constantly on and frequently called. Little research has been conducted on the effect of the deployment paradigms on energy consumption.

Participant

Cloud consumer

Related software artifact

Cloud deployments (abstract)

Context

VM versus serverless

Software feature

Deployment paradigm

Tactic intent

Selecting the best-fitting deployment paradigm to optimize performance and cost

Target quality attribute

Performance

Other related quality attributes

Cost-efficiency, energy-efficiency

Measured impact

When organizations decide to migrate their software to the public cloud, cloud consumers need to decide upfront which deployment paradigm to embed as it is costly and time-consuming to change the deployment paradigm after launching the application. Hence, with this analysis, we aim to support cloud consumers in choosing the fitting deployment paradigm. We designed an experiment to measure the impact of the deployment paradigm on the energy consumption. Due to time constraints, the experiment could not be executed successfully. We refer the reader to section 7.2.3 and 7.2.4 of the source for further reading.

Source

Master Thesis “Architectural Tactics to Optimize Software for Energy Efficiency in the Public Cloud” by Sophie Vos


Graphical representation

  • Contact person
  • Patricia Lago (VU Amsterdam)
  •  disc at vu.nl
  •  patricialago.nl

The Archive of Awesome and Dark Tactics (AADT) is an initiative of the Digital Sustainability Center (DiSC). It received funding from the VU Amsterdam Sustainability Institute, and is maintained by the S2 Group of the Vrije Universiteit Amsterdam.

Initial development of the Archive of Awesome and Dark Tactics by Robin van der Wiel