Sushmith Kumar Email & Phone Number

Nashville Metropolitan Area

• Developed a comprehensive migration plan, ensuring a smooth transition from Splunk to the ELK stack while preserving data integrity and functionality.• Engineered efficient Logstash configurations to ingest and transform data from diverse sources, ensuring seamless integration into Elasticsearch.• Successfully migrated Splunk dashboards and alerts to Kibana, optimizing visualization and alerting capabilities to match and enhance the previous monitoring system.• Translated existing Splunk queries to Elasticsearch DSL, optimizing queries for efficient and accurate data retrieval from Elasticsearch indices.• Utilized Kibana to design and develop custom dashboards and visualizations, tailored to specific monitoring needs and user requirements.• Implemented performance monitoring solutions within ELK to identify bottlenecks and optimize Elasticsearch clusters for improved query response times.• Leveraged knowledge of Splunk search language and capabilities to enhance and optimize Elasticsearch queries and data analysis.• Implemented data normalization and standardization processes during migration to ensure consistency in log formats and improve search and analysis capabilities.• Developed custom Logstash filters to parse and enrich log data, extracting valuable information for more accurate analysis and alerting.• Demonstrated substantial cost savings by migrating from Splunk to ELK, achieving similar or better monitoring capabilities while optimizing resource utilization.• Enhanced real-time alerting by fine-tuning alerting rules and leveraging Elasticsearch's native alerting features to ensure timely notification of critical events.• Employed custom scripts and automation tools to streamline data ingestion processes, reducing manual intervention and ensuring data consistency.• Designed ELK infrastructure for scalability and high availability, allowing for seamless scaling as data volume increased and minimizing downtime.

• Implemented Logstash pipelines for efficient ingestion, parsing, and enrichment of diverse data sources, ensuring seamless integration with Elasticsearch.• Developed tailored Logstash filters to preprocess and transform raw data into structured formats, enabling easier querying and analysis in Elasticsearch.• Configured Kibana alerts to notify the operations team in real-time of critical events, enhancing proactive issue resolution and minimizing system downtimes.• Successfully centralized logs from various applications and systems into Elasticsearch, simplifying log management and accelerating troubleshooting processes.• Designed intuitive Kibana visualizations to track key performance metrics, enabling quick identification of performance bottlenecks and trends.• Optimized Elasticsearch cluster configurations and indices to handle increased data volume while maintaining optimal performance.• Implemented data retention policies to manage data lifecycle effectively, balancing storage costs with the need for historical data analysis.• Integrated Elasticsearch with external tools and platforms to enhance monitoring capabilities and centralize monitoring efforts.• Implemented security features to control access to Elasticsearch data and maintain data privacy, following industry best practices and compliance standards.• Prepared comprehensive documentation and conducted training sessions to ensure the operations team could effectively utilize and manage the ELK stack.• Automated the generation and distribution of regular performance and usage reports, providing insights to stakeholders for informed decision-making.• Integrated geo-spatial analysis capabilities into Kibana, allowing visualization and analysis of data with geographic components for enhanced insights.• Managed Amazon Web Services (AWS) infrastructure, including EC2 instances, S3 buckets, and VPCs.

• Lead the optimization of a large-scale Elasticsearch cluster to improve search performance and efficiency.• Configured and managed a multi-node Elasticsearch cluster, including index settings, shard allocation, and node monitoring.• Designed and implemented efficient data models for storing and querying large volumes of structured and unstructured data in Elasticsearch.• Developed custom Java applications to integrate with Elasticsearch for data indexing, search functionality, and real-time data processing.• Optimized Elasticsearch cluster performance by fine-tuning JVM settings, shard allocation strategies, and query optimizations.• Utilized Elasticsearch REST APIs for performing CRUD operations, executing complex search queries, and managing cluster settings.• Implemented Logstash pipelines for data ingestion, transformation, and enrichment before indexing into Elasticsearch.• Created custom visualizations and dashboards in Kibana to analyze and monitor Elasticsearch cluster performance and data trends.• Implemented security measures for Elasticsearch cluster, including user authentication, role-based access control, and SSL/TLS encryption.• Designed and implemented a scalable data ingestion pipeline using Beats and Logstash for streaming data into Elasticsearch.• Set up monitoring and alerting for Elasticsearch cluster using Elasticsearch monitoring features and external monitoring tools.• Integrated Elasticsearch with other systems and applications using APIs and libraries for seamless data exchange.• Identified and resolved performance bottlenecks, data consistency issues, and other challenges in Elasticsearch cluster operation.• Worked in an Agile development environment, collaborating with cross-functional teams to deliver features and enhancements.• Managed codebase changes using Git version control and implemented CI/CD pipelines for automated testing and deployment.

• Developed code for user interface by utilizing OOPS concepts like multithreading, inheritance, polymorphism, and collection API. • Worked with Microservice architecture using Spring Boot to modularize code and implemented Rest API’s using Spring Rest and integrated Swagger API for documentation. • Worked on implementation of Spring Security with JWT Token which is used across the web application for the authentication and authorization of the users. • Implemented all the functionality using Spring IO / Spring Boot, Microservices and Hibernate ORM.• Written PL/SQL code for Analysis, Design, and Implementation of Business Applications using the Oracle Relational Database Management System (RDBMS). • Created DB Links to interact with other Oracle databases on the distributed database system. • Managed and maintained Oracle and NoSQL (MongoDB) databases in production domain. • Used Lift and Shift mechanism to migrate on premise PostgreSQL to Google Cloud Platform.• Implemented CI/CD pipeline for the Azure cloud-based analytical data ecosystem using Azure DevOps (VSTS), GIT as versioning controlling and hosted pipelines for build and release. • Designed and implemented highly available and fault-tolerant solutions using GCP technologies such as Load Balancing, Cloud CDN, and Cloud DNS. • Configured GCP Virtual Private Cloud (VPC) to establish secure connections between on-premises and cloud environments. • Tested components using Junit framework during development. • Configured and automated Jenkins tool for continuous integration and deployment. • Used Log4J to capture the log that included runtime exceptions for technical support. • Developed UI for interaction with the system using jQuery, JavaScript, Angular, JSON, and Bootstrap.