Data Logging is the main activity to be considered in maintaining a server or database in working condition without any errors or failures. Data collection can be automatic, so, no human presence is necessary. To store the data of logs for many days and visualizing became a huge problem in recent days. Coming to node SGSN-MME, which is the main component of the GPRS network, which handles all packet switched data within the mobile operator's network. A lot of log data is generated and stored in file systems on the redundant File Server Boards in SGSN-MME node. The evolution of the SGSN-MME is taking it from dedicated, purpose-built, hardware into virtual machines in the Cloud, where virtual file server boards fit very badly. The purpose of this thesis is to give a better way to store the log data and add visualization using the ELK stack concept. Fetching useful information from logs is one of the most important part of this stack and is being done in Logstash using its grok filters and a set of input, filter and output plug-ins which helps to scale this functionality for taking various kinds of inputs ( file,TCP, UDP, gemfire, stdin, UNIX, web sockets and even IRC and twitter and many more) , filter them using (groks,grep,date filters etc.)and finally write output to ElasticSearch. The Research Methodology involved in carrying out this thesis work is a Qualitative approach. A study is carried using the ELK concept with respect to Legacy approach in Ericsson company. A suitable approach and the better possible solution is given to the vSGSN-MME node to store the log data. Also to provide the performance and uses multiple users of input providers and provides the analysis of the graphs from the results and analysis. To perform the tests accurately, readings are taken in defined failure scenarios. From the test cases, a plot is provided on the CPU load in vSGSN-MME which easily gives the suitable and best promising way.