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Monitoring IaaS using various cloud monitors

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Abstract

In cloud computing, the performance of infrastructure as a service is critical because of its divergence in area. The cloud providers guarantee that the resources will be available around the clock. The providers assure that the period of unavailability of resources is very less. Recently the cloud users have increased rapidly; therefore the providers also have increased, basically increasing the complexity of the infrastructure. This complex infrastructure should be allocated properly to the users and the availability of resources should be notified to the users. So monitoring of these resources constantly is critical. In this analysis, comparison of various monitoring tools in terms of SLA parameters are measured and tabulated. For the comparison, the Amazon cloud instances are monitored with three different monitoring tools like CloudWatch monitoring, IDERA uptime cloud monitor and ManageEngine applications manager. The SLA parameters of IaaS are CPU utilization, network in, network out, disk read, disk write, response time and memory usage. In addition with Amazon instances, servers like Tomcat and data base like PostgreSQL are also monitored and their performance parameters are also analyzed. The instances monitored by cloudwatch monitoring gives twice the range of CPU Utilization than the others. The network data transfer is also high using cloudwatch.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, St.Xavier’s Catholic College of Engineering, Anna University, Nagercoil, 629003, India

    Absa Stephen

  2. Indian Institute of Information Technology Kottayam, Kottayam, India

    Shajulin Benedict

  3. Department of Computer Science and Engineering, St.Xavier’s Catholic College of Engineering, Anna University, Nagercoil, 629003, India

    R. P. Anto Kumar

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  1. Absa Stephen
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Correspondence to Absa Stephen.

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Stephen, A., Benedict, S. & Kumar, R.P.A. Monitoring IaaS using various cloud monitors. Cluster Comput 22 (Suppl 5), 12459–12471 (2019). https://doi.org/10.1007/s10586-017-1657-y

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  • DOI: https://doi.org/10.1007/s10586-017-1657-y

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