COCOA: Cold Start Aware Capacity Planning for Function-as-a-Service Platforms

Imperial College London researchers released this dataset to support the paper 'COCOA: Cold Start Aware Capacity Planning for Function-as-a-Service Platforms'. The paper was accepted at the IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) in 2020. The dataset likely contains performance metrics or simulation results related to cold starts and capacity planning in serverless computing environments.

Use Cases

• Benchmarking cold start mitigation strategies based on the described performance modeling framework
• Training models for capacity planning based on the described function-as-a-service platform dynamics
• Simulating serverless platform behavior under varying loads based on the described cold start scenarios

Strengths

• Dataset is directly linked to a peer-reviewed academic paper published at a major conference.
• The associated paper provides a clear methodological context for the data's intended use.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Alim Ul Gias, Imperial College London