Eficiency of REST and gRPC realizing communication tasks in microservice-based ecosystems

Andrzej Paszkiewicz; Carlos E. Palau; Ignacio Lacalle; Kamil \.Zak; Marcin Paprzycki; Marek Bolanowski; Maria Ganzha; Piotr Sowi\'nski

Eficiency of REST and gRPC realizing communication tasks in microservice-based ecosystems

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2208.00682 v1 pith:RMD677HM submitted 2022-08-01 cs.PF cs.DCcs.NI

Marek Bolanowski , Kamil Żak , Andrzej Paszkiewicz , Maria Ganzha , Marcin Paprzycki , Piotr Sowiński , Ignacio Lacalle , Carlos E. Palau This is my paper · ORCID

classification cs.PFcs.DCcs.NI

keywords communicationtasksecosystemsgrpcmicroservice-basedperformedrestallows

verification ladder T0 review T1 audit T2 compute T3 formal

0 comments

read the original abstract

The aim of this contribution is to analyse practical aspects of the use of REST APIs and gRPC to realize communication tasks in applications in microservice-based ecosystems. On the basis of performed experiments, classes of communication tasks, for which given technology performs data transfer more efficiently, have been established. This, in turn, allows formulation of criteria for the selection of appropriate communication methods for communication tasks to be performed in an application using microservices-based architecture.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

From Monolith to Microservices: A Comparative Evaluation of Decomposition Frameworks
cs.SE 2026-01 conditional novelty 4.0 of 10

Across four benchmark monoliths, hierarchical DBSCAN-based decomposition scores highest under the authors' hand-weighted aggregate metric, but most comparison data comes from prior papers.

Pith tools