Scientific Papers
ISSI Research PapersPaper information
Title
Models@runtime for Monitoring Cloud Services in Google App Engine
Models@runtime for Monitoring Cloud Services in Google App Engine
Published in
13th IEEE World Congress on Services (IEEE SERVICES 2017), June 25-30, 2017, Honolulu, Hawaii, USA, IEEE Computer Society. - 2017
13th IEEE World Congress on Services (IEEE SERVICES 2017), June 25-30, 2017, Honolulu, Hawaii, USA, IEEE Computer Society. - 2017
Abstract
Over the last years a number of monitoring approaches for cloud services have been proposed. They suffer, however, from several limitations when changes to monitoring requirements must be made or because of the complexity involved in capturing raw data from services at runtime. To address these problems, in a previous work, we proposed a platform-independent monitoring middleware for cloud services that exploits models@runtime for monitoring the quality of cloud services and providing a report containing SLA violations. The middleware has been implemented in Microsoft Azure. To provide further evidence about the generalizability of our approach, in this work, we present the implementation of the platform-independent middleware in Google App Engine. The middleware is capable of extracting raw data from the services deployed in this platform based on the quality requirements established in an SLA and structured in a model at runtime that is exploited to perform the measurements established in the model, so that users can assess the compliance of quality requirements established in the SLA. The use of models@runtime allowed to raise the level of abstraction by providing a high-level of flexibility and maintainability required to monitor cloud services.
Over the last years a number of monitoring approaches for cloud services have been proposed. They suffer, however, from several limitations when changes to monitoring requirements must be made or because of the complexity involved in capturing raw data from services at runtime. To address these problems, in a previous work, we proposed a platform-independent monitoring middleware for cloud services that exploits models@runtime for monitoring the quality of cloud services and providing a report containing SLA violations. The middleware has been implemented in Microsoft Azure. To provide further evidence about the generalizability of our approach, in this work, we present the implementation of the platform-independent middleware in Google App Engine. The middleware is capable of extracting raw data from the services deployed in this platform based on the quality requirements established in an SLA and structured in a model at runtime that is exploited to perform the measurements established in the model, so that users can assess the compliance of quality requirements established in the SLA. The use of models@runtime allowed to raise the level of abstraction by providing a high-level of flexibility and maintainability required to monitor cloud services.
BibTeX
@misc{issi_web:id:486,
title = "Models@runtime for Monitoring Cloud Services in Google App Engine",
author = "Silvia Abrahao and Emilio Insfrán Pelozo",
booktitle = "13th IEEE World Congress on Services (IEEE SERVICES 2017), June 25-30, 2017, Honolulu, Hawaii, USA, IEEE Computer Society.",
year = "2017",
eprint = "http://issi.dsic.upv.es/publications/archives/",
url = "",
abstract = "Over the last years a number of monitoring approaches for cloud services have been proposed. They suffer, however, from several limitations when changes to monitoring requirements must be made or because of the complexity involved in capturing raw data from services at runtime. To address these problems, in a previous work, we proposed a platform-independent monitoring middleware for cloud services that exploits models@runtime for monitoring the quality of cloud services and providing a report containing SLA violations. The middleware has been implemented in Microsoft Azure. To provide further evidence about the generalizability of our approach, in this work, we present the implementation of the platform-independent middleware in Google App Engine. The middleware is capable of extracting raw data from the services deployed in this platform based on the quality requirements established in an SLA and structured in a model at runtime that is exploited to perform the measurements established in the model, so that users can assess the compliance of quality requirements established in the SLA. The use of models@runtime allowed to raise the level of abstraction by providing a high-level of flexibility and maintainability required to monitor cloud services. "
}