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Evaluating the Overhead of the Performance Profiler Cloudprofiler With MooBench

dc.contributor.authorYang, Shinhyung
dc.contributor.authorReichelt, David Georg
dc.contributor.authorHasselbring, Wilhelm
dc.contributor.editorHerrmann, Andrea
dc.date.accessioned2025-01-08T13:31:08Z
dc.date.available2025-01-08T13:31:08Z
dc.date.issued2024
dc.description.abstractPerformance engineering has become crucial for the cloud-native architecture. This architecture deploys multiple services, with each service representing an orchestration of containerized processes. OpenTelemetry is growing popular in the cloud-native industry for observing the software’s behaviour, and Kieker provides the necessary tools to monitor and analyze the performance of target architectures. Observability overhead is an important aspect of performance engineering and MooBench is designed to compare different observability frameworks, including OpenTelemetry and Kieker. In this work, we measure the overhead of Cloudprofiler, a performance profiler implemented in C++ to measure native and JVM processes. It minimizes the profiling overhead by locating the profiler process outside the target process and moving the disk writing overhead off the critical path with buffer blocks and compression threads. Using MooBench, Cloudprofiler’s buffered ID handler with the Zstandard lossless data compression ZSTD showed an average execution time of 2.28 microseconds. It is 6.15 times faster than the non-buffered and non-compression handler.en
dc.identifier.issn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45557
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 44, Heft 4
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectperformance
dc.subjectperformance engineering
dc.subjectcloud
dc.subjectbenchmark
dc.subjectMooBench
dc.subjectoverhead
dc.subjectCloudprofiler
dc.titleEvaluating the Overhead of the Performance Profiler Cloudprofiler With MooBenchen
dc.typeText/Conference Paper
mci.conference.dateNovember 6-7, 2024
mci.conference.locationLinz, Austria
mci.conference.sessiontitle15th Symposium on Software Performance 2024
mci.reference.pages15-17

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