Maks: Server Health Monitoring using Kafka
Big Data Analytics has immense potential to change the way Server Health Monitoring is being done. Use of Big
data analytics can help Network Administrators to become more proactive and well informed. This paper proposes a design
for Big Data Platform based Server Health Monitoring system MAKS (Monitoring and Alerting system using Kafka and
Spark). Big Data can not only provide high server availability and hence low down time, it can also help in achieving more
secured cyber space. Hadoop is deployed for numerous real world problem, but since Hadoop has its own technical
limitations in handling real-time streaming data, a much faster application is required to deal with requirements of fast event
driven based approach of companies. Hadoop fulfills the requirement to store data in HDFS and to execute analysis, whereas
Kafka is the one that delivers high speed in terms of transportation and data distribution to several locations. Spark streaming
integrated with Kafka provides a very efficient solution to this problem. The motive of this paper is to propose a design
model, using Spark and Kafka for Serve health Monitoring.
Keywords - Server Health Monitoring, Alerting, Kafka, Big Data, Spark.