Server Monitoring Tools: Nagios Core, Ganglia, CollectD, Spiceworks, Cacti, Zabbix, Icinga, OpenNMS, WhatsUp Gold

This article provides an overview of the top server monitoring tools including Nagios Core, Ganglia, CollectD, Spiceworks, Cacti, Zabbix, Icinga, OpenNMS, and WhatsUp Gold. It discusses their features, benefits, and how they help in reducing risks and threats to servers. The article also explains the monitoring architecture and data vulnerability solutions. It concludes by emphasizing the importance of server monitoring for evaluating performance and ensuring the security of vital data.

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Introduction:
Server is considered to be the system responsible for the supplying of different kind of
resources, services and data to the system from the network channels. After receiving of request
the server is associated with the responding to the request. The requests are mainly associated
with involving a user identity verification request or request for permission [1]. Different kind of
tools are used which helps in monitoring of the servers. This tools are mainly used so as to
monitor and administer the entire network. The automated checking systems helps in the
generation of the checks in a scheduled manner which is also responsible for the providing of a
pre-emptive warnings for the servers.
IT Infrastructure monitoring tools:
Some of the major IT infrastructure monitoring tools have been provided below:
NagiosCore:
NagiosCore is a monitoring tool which is customizable along with being cost-effective. The open
source monitoring tool helps in measuring along with the monitoring of the servers [2]. This tool
is also responsible for the providing of reports as well as remediate services.
Ganglia:
Ganglia is an open source tool which is used by the high speed computer systems. This
tool is having an architecture which along with being scalable is also distributed in nature and is
seen to be dependent upon the hierarchical design. Data is represented by XML whereas the
transportation is represented by the XDR. The efficiency of this tool is maximized by means of
the algorithms and data structures which helps is putting an overhead upon the individual nodes.

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CollectD:
CollectD is an open source monitoring tool responsible for the collection of the performance
statistics along with being responsible for storage of the collected data in various kind of formats
[4]. This tool is used by various OS and is associated with searching and identification of
different bottlenecks. This type of tool is mainly seen to be integrated with the graphing tool.
Spicework:
Spicework is responsible for proving of server insights along with the insights of the
SNMP devices, the services and the switches. Responsible for the finding out of IP address
devices along with helping in the supplying of knowledge base as well as different functions of
the help desk.
Cacti:
This is a front end tool or a graphing tool used by the data systems which is having the
capacity of managing the process of collecting the data. External scripts are used for gathering
the data which in turn is responsible for feeding the metrics [3]. Graphs are generated by this tool
by usage of the infrastructure elements such as the load balancers and servers.
Zabbix:
Zabbix is an enterprise solution which is having different characteristics and is
responsible for the providing of support commercially. The tool is also responsible for the
checking of the response time for different servers such as the HTTP. The uptime is also checked
by this software.

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Icinga:
This tool is an extension of the Nagios which is responsible for the providing of the
REST API as well as connectors for the database [5]. The new API attribute helps in easy
integration of different extensions where there is no need of direct modification of the core.
OpenNMS:
OpenNMS is the software associated with allowing the connection of maximum ten
devices which is associated with allowing a login to a single user only. The serving functionality
of this software is very simple [6].
WhatsUP Gold:
This tool is associated with the monitoring of the application performance along with the
server and the network device performance. The tool is associated with monitoring in the on
premises as well in the clouds. An interactive as well as comprehensive map is provided by this
tool which is related to the complete network architecture. The servers along with the traffic
flow, the applications and the wireless controllers are also monitored.
Comparison
CollectD
Disk usage

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Figure 1: Disk Usage)
Source: (Created By Author)
CPU Monitoring

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Figure 2: CPU Monitoring
Source: (Created by Author)
Process Monitoring

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Figure 3: Process Monitoring
Source: (Created By Author)
Resource Monitoring
Figure 4: Resource Monitoring
Source: (Created by Author)

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Bandwidth Measuring
Figure 5: Bandwidth Measuring
Source: (Created By Author)

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Ganglia
Disk usage
Figure 6: Disk Usage

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Source: (Created by Author)
CPU Monitoring
Figure 7: CPU Monitoring
Source: (Created by Author)
Resource Monitoring

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Figure 8: Resource Monitoring
Source: (Created by Author)
Bandwidth Monitoring
Figure 9: Bandwidth Monitoring
Source: (Created by Author)

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Process Monitoring
Figure 10: Process Monitoring
Source: (Created by Author)

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Zabbix
Disk Usage

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Figure 11: Disk Usage
Source: (Created by Author)
Process Monitoring

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Figure 12: Process Monitoring
Source: (Created By Author)
CPU Monitoring
Figure 13: CPU Monitoring
Source: (Created By Author)

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Bandwidth Monitoring
Figure 14: Bandwidth Monitoring
Source: (Created By Author)
Resource Monitoring

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Figure 15: Resource Monitoring
Source: (Created By Author)
WhatsUp Gold
Disk Usage

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Figure 16: Disk Usage
Source: (Created By Author)
Process Monitoring

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Figure 17: Process Monitoring
Source: (Created By Author)
CPU Monitoring
Figure 18: CPU Monitoring
Source: (Created By Author)
Bandwidth Monitoring

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Figure 19: Bandwidth Monitoring
Source: (Created By Author)

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Resource Monitoring
Figure 20: Resource Monitoring
Source: (Created By Author)
Monitoring architecture:
The monitoring server is classified into four major sections which is associated with including
the application, window agent, linux agent and service. The architecture is associated with
monitoring the servers which is followed by the generation of the reports [7]. If any issues is
detected then warnings are provided. The monitoring architecture has been provided below:

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Figure 21: Server monitoring architecture
Source: ([1])
Data vulnerability and solutions:
There is a need of proper management and it is seen that the monitoring tools are heavily
dependent upon the server’s privileges access. Certain task and overtime are assigned to each
tools and along with this there also exists multiple users who are associated accessing the
servers. The entry points put forward the risk related to data breach and due to the existence of
additional entry data the vulnerability increases which in turn increases the threats to the server
[8]. One of the scanning tool which can be used for detection of the vulnerabilities in the server
is the Comondo HackerProof. The scanning tool is associated with helping by means of the

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regular scanning along with abandonment of the cart and by including the PCI tools and by
prevention of drive by attack.
Conclusion:
Server monitoring are very important and acts as an import metric used for the evaluation of the
performance. The server monitoring tools like Nagios Core, Ganglia, CollectD, Spiceworks,
Cacti, Zabbix, Icinga, OpenNMS and WhatsUp Gold closely monitors the server system. This
tools are associated with following strict protocols so as to monitor the servers. The server
monitoring tools are associated with helping in reduction of risks as well as different kind of
threats and this is very important as huge of data always flows through a server which are very
vital.

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References:
[1.]J. Hernantes, G. Gallardo and N. Serrano, IT infrastructure-monitoring tools. IEEE
Software, 32(4), pp.88-93, 2015.
[2.]H.J. Syed, A. Gani, R.W. Ahmad, M.K. Khan, and A.I.A. Ahmed, Cloud monitoring: A
review, taxonomy, and open research issues. Journal of Network and Computer
Applications, 98, pp.11-26, 2017.
[3.]V. Casola, A. De Benedictis, and M. Rak, Security monitoring in the cloud: an SLA-based
approach. In 2015 10th International Conference on Availability, Reliability and
Security (pp. 749-755), IEEE, 2015, August.G.Q. Peng, G. Xue, and Y.C.Chen, Network
Measurement and Performance Analysis at Server Side. Future Internet, 10(7), p.67, 2018.
[4.]S.S. Kolahi, K. Treseangrat, and B. Sarrafpour, Analysis of UDP DDoS flood cyber attack
and defense mechanisms on web server with Linux Ubuntu 13. In 2015 International
Conference on Communications, Signal Processing, and their Applications (ICCSPA'15) (pp.
1-5). IEEE, 2015, February.
[5.] A. Cardoso, CJV. TEIXEIRA, and JS. PINTO. Architecture for Highly Configurable
Dashboards for Operations Monitoring and Support. Studies in Informatics and
Control, 27(3), pp.319-330, 2018.
[6.] S. Hilt, and P. Lin. Leaking Beeps: A Closer Look at IT Systems That Leak Pages. Trend
Micro, Sept 2016.
[7.] A. Nelson. Performance Tuning best pracitces and performance monitoring with Zabbix,
2015
[8.] M. Adam. Evaluation and implementation of CEP mechanisms to act upon infrastructure
metrics monitored by Ganglia (No. CERN-STUDENTS-Note-2015-172), 2015.

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