George Kousiouris, Chris Giannakos, K. Tserpes, Teta Stamati
{"title":"在大型FaaS工作流的不同编排机制中测量基线开销","authors":"George Kousiouris, Chris Giannakos, K. Tserpes, Teta Stamati","doi":"10.1145/3491204.3527467","DOIUrl":null,"url":null,"abstract":"Serverless environments have attracted significant attention in recent years as a result of their agility in execution as well as inherent scaling capabilities as a cloud-native execution model. While extensive analysis has been performed in various critical performance aspects of these environments, such as cold start times, the aspect of workflow orchestration delays has been neglected. Given that this paradigm has become more mature in recent years and application complexity has started to rise from a few functions to more complex application structures, the issue of delays in orchestrating these functions may become severe. In this work, one of the main open source FaaS platforms, Openwhisk, is utilized in order to measure and investigate its orchestration delays for the main sequence operator of the platform. These are compared to delays included in orchestration of functions through two alternative means, including the execution of orchestrator logic functions in supporting runtimes based on Node-RED. The delays inserted by each different orchestration mode are measured and modeled, while boundary points of selection between each mode are presented, based on the number and expected delay of the functions that constitute the workflow. It is indicative that in certain cases, the orchestration overheads might range from 0.29% to 235% compared to the beneficial computational time needed for the workflow functions. The results can extend simulation and estimation mechanisms with information on the orchestration overheads.","PeriodicalId":129216,"journal":{"name":"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering","volume":"143 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows\",\"authors\":\"George Kousiouris, Chris Giannakos, K. Tserpes, Teta Stamati\",\"doi\":\"10.1145/3491204.3527467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Serverless environments have attracted significant attention in recent years as a result of their agility in execution as well as inherent scaling capabilities as a cloud-native execution model. While extensive analysis has been performed in various critical performance aspects of these environments, such as cold start times, the aspect of workflow orchestration delays has been neglected. Given that this paradigm has become more mature in recent years and application complexity has started to rise from a few functions to more complex application structures, the issue of delays in orchestrating these functions may become severe. In this work, one of the main open source FaaS platforms, Openwhisk, is utilized in order to measure and investigate its orchestration delays for the main sequence operator of the platform. These are compared to delays included in orchestration of functions through two alternative means, including the execution of orchestrator logic functions in supporting runtimes based on Node-RED. The delays inserted by each different orchestration mode are measured and modeled, while boundary points of selection between each mode are presented, based on the number and expected delay of the functions that constitute the workflow. It is indicative that in certain cases, the orchestration overheads might range from 0.29% to 235% compared to the beneficial computational time needed for the workflow functions. The results can extend simulation and estimation mechanisms with information on the orchestration overheads.\",\"PeriodicalId\":129216,\"journal\":{\"name\":\"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering\",\"volume\":\"143 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3491204.3527467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Companion of the 2022 ACM/SPEC International Conference on Performance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3491204.3527467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows
Serverless environments have attracted significant attention in recent years as a result of their agility in execution as well as inherent scaling capabilities as a cloud-native execution model. While extensive analysis has been performed in various critical performance aspects of these environments, such as cold start times, the aspect of workflow orchestration delays has been neglected. Given that this paradigm has become more mature in recent years and application complexity has started to rise from a few functions to more complex application structures, the issue of delays in orchestrating these functions may become severe. In this work, one of the main open source FaaS platforms, Openwhisk, is utilized in order to measure and investigate its orchestration delays for the main sequence operator of the platform. These are compared to delays included in orchestration of functions through two alternative means, including the execution of orchestrator logic functions in supporting runtimes based on Node-RED. The delays inserted by each different orchestration mode are measured and modeled, while boundary points of selection between each mode are presented, based on the number and expected delay of the functions that constitute the workflow. It is indicative that in certain cases, the orchestration overheads might range from 0.29% to 235% compared to the beneficial computational time needed for the workflow functions. The results can extend simulation and estimation mechanisms with information on the orchestration overheads.