![]() Splunk/Java: Splunk 6, Splunk Cloud, Splunk Enterprise, Splunk modules, Splunk DB Connect, Splunk Web Framework Splunk, Splunk Hunk, Splunk on Splunk HDFS, Grafana, Java, J2EE, Eclipse, Windows NT 4.0, UNIX, My Eclipse IDE, JSP/Servlets, Design patterns, Struts, Spring, MVC framework, Hibernate, JDBC, XSD, SAX, JAXP, Oracle8, UNIX, Splunk IT Service Intelligenceīig data Analytics: New Relic, Splunk, Tableau, AppDynamics, Service now, Nagios,Grafanaįamiliar reporting tools: Cognos, Crystal reports, SSRSīuild/automation tools: Puppet, chef, ant, mavenĭatabases: Oracle 11g/10g/9i, MySQL, DB2, MS-SQL Server Experienced in automation using Shell Scripting Proficient in working on UNIX and Linux platforms.Expert level skills on jQuery, JavaScript, JSON, HTML, CSS.Monitor the applications and server infrastructure for optimization, performance and Utilization metrics.Excellent experience with major relational databases - Oracle, SQL Server 2000/2005/2008, DB2, My SQL.Creating ITSI Dashboards/Glass Tables, setting up Multi KPI Alerts and generating complex operational reports.Expertise in the implementation of Core concepts of Java, J2EE Technologies.Experience with creating and executing complex SQL queries.Participated in workshops with ServiceNow partner teams to help companies implement Service Now using best practices in ITSM.Strong skill set in the Service Now suite development including SOAP/REST integration.Hands-on experience in technical implementation of Incident Management, Problem Management, Release Management, Change Management and Service Catalog, Demand Management, SCCM.Experience in designing, development and implementation of Service Now Platform.Extensive experience in designing, developing and publishing visually rich and intuitively interactive tableau workbooks and dashboards for executive decision making.Extensive experience in creating UI visualization with tableau desktop, tableau server and tableau reader in various versions of Tableau.Experience in Indexer Clustering and Search Head Clustering architecture in Splunk.Experience in Installation, Configuration, Migration and Administered Splunk Search Head, Indexers, Heavy Forwarders, Deployment Server, Cluster Master, Deployment Server, License Master and Universal Forwarder on Linux and Windows operating systems.Built customized complicated multi panel dashboards with Regex. Extensive knowledge on Splunk knowledge objects, Data inputs and Distributed environment.Experience in customizing Splunk for monitoring in Application Management.Knowledge of Extract keyword, sed, Knowledge objects, Knowledge of various search commands like stats, chart, time chart, transaction, strptime, strftime, eval, where, xyseries, table etc.Managing of Splunk licenses based on the requirement.Installing the Splunk Light Weight Forwarders, Forwarders, Indexers, Search Heads after configuring the files like nf, input.Upgraded to Splunk6.X version in the environment.Experience in using Splunk DB Connect to index the data from various database types.Implemented workflow actions to drive troubleshooting across multiple event types in Splunk.Expertise in Installation, Configuration, Migration, Trouble - Shooting and Maintenance of Splunk Passionate about Machine data and operational Intelligence.Experience in development of dashboards/reports, alerts and Splunk integration.IT professional around 7 years of experience working in various domains such as Splunk Admin / Developer, Splunk Architect, Application security testing, Generating reports, relationship management and coordination skills.Meaning, the REGEX captures the entire event, breaks it up to multiple capturing groups and then reconstructs the event. The "$1" and "$2" refer to the two capturing groups in the "REGEX" field. These last two parts are to be retained when the event data is written back out to the "_raw" field specified by the "DEST_KEY." Note that the “FORMAT” setting specifies how the event will be re-written. The approach here is to match the first part of the event (.*), then the part to be masked (SN=…), then the last 4 digits and the rest of the event. “This is an event with a sensitive number in it. This is the result of the sample event going through the transformation TRANSFORMS-hr_app_logs_mask_data = mask_sn In the example, the goal is to mask the “sensitive number" except for the last 4 digits. In this approach, a TRANSFORMS statement is called in the nf file and is applied to the data in the queues before being indexed.
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