Jaisudhan Selvaraj


Jaisudhan Selvaraj

Jaisudhan has about 9+ years of work experience in IT Industry focusing on Performance testing & Engineering with excellent working experience of End-to-End process and it’s methodology , Operational Acceptance Testing & Management, Service Virtualization process/concepts, CI/CD Automation for NFT jobs and Selenium Automation test in JAVA, He also manages performance project/program of large mission critical applications and handling defect management process within in NFT space. He has worked on various domains such as IME, Healthcare, Insurance, Retails, Telecommunications & BFS for the customers in APAC, USA & UK regions. He is part of Cognizant NFT team with successful NFT career and manages various performance testing projects successfully for a well reputed Banking customer in UK. He is always keen to thrive things different and invent new solutions in technology aspects which benefits the organization and customers.

Topic: The Splunk Integration for Futuristic NFT in DevOps Culture

The advent of DevOps has produced innovative dependencies across project teams (waterfall, Agile/POD). Software product/code can be delivered to production through CI/CD model quickly in which Splunk aids project team to quickly isolate issues in development, build and QA phases for faster time to market. The evolution of DevOps culture across SDLC/STLC, Splunk enables various integration techniques for efficient tracking of test, build, infrastructures and deliver software products with its powerful machine learning and analyzing capabilities.

Integration of APM tools/Search engines with any software systems becomes nightmares when it comes to cost, technical challenges, CI/CD implementation approach and real-time monitoring of infrastructures/systems.

Splunk gives seamless enablement for CI/CD model with various integration for real-time application developments, infrastructure monitoring and provides business intelligence insights into vast I/O data operations. The Machine generated data is a log which comes from any computer Process/Application during their execution(e.g. system event & live application logs, network feeds, message queues, etc.) which is difficult to interpret.

Splunk is one of most powerful tools to analyze any raw data from modern Infrastructures/Systems/CI Build logs, etc Splunk evolving in various continuous integration approach in the way how it’s being utilized across Projects/NFT lifecycles. This paper will highlight following areas for futuristic NFT & various monitoring integration techniques with CI/CD approach,

Implementation Approach:
·Loading data into Splunk across all the systems involved in the infrastructure estate by integrating through Splunk directory/ file monitoring concepts or Splunk forwarder monitoring to Splunk Indexer
·Key Performance Indicator monitoring for Business Critical Transactions and Business Intelligence operational decision with Splunk Alerting & Email systems with CI/CD Model.
· Generate a centralised dashboard from the raw test results of Loadrunner, Neoload, Jmeter tools etc by pulling data a from common test data repository.
· Real-time monitoring of Infrastructures/Operating systems from Perfmon, Nmon, vmstat logs etc via Splunk forwarder monitoring approach.
·APM tools integration such as DynaTrace etc using Splunk add-on/Dynatrace App for Splunk plug-in.
· Virtualization tool Integration such as CA Dev Test etc by monitoring virtual service environment server logs via Splunk forwarder monitoring approach.
·Real-time monitoring of centralised Jenkins infrastructure using Jenkins Splunk plug-in.

·Real-time KPI monitoring from the centralised Splunk dashboard & reports
·Visualize performance test results from a centralised dashboard with trend analysis across test results
·Live monitoring and analysis of performance bottleneck from multiple infrastructures/ Operating systems
·Live Monitoring of errors, response time of critical web traffics/ API calls and user session trend analysis
·Live Monitoring of virtual services and its invocation count, trend of processing time during performance tests
·Centralised dashboard of Jenkins infrastructure health analysis, build & test analysis etc.
·Business benefits such as faster time to market, reduced performance risks, quick business decisions etc.

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