Observability SRE adept at designing and managing observability solutions:- Logging: Built and maintaining ELK stack (Elasticsearch, Logstash, Kibana) for efficient centralized logging, enabling seamless troubleshooting and analysis of application logs.- Monitoring: Implemented and maintaining VictoriaMetrics stack, providing real-time monitoring and alerting capabilities for comprehensive visibility into key performance metrics and system health indicators.- Tracing: Integrated Jaeger distributed tracing into complex application stacks, offering end-to-end visibility into latency bottlenecks and facilitating performance optimizations.- Incident Management: Maintaining and leveraging the Opsgenie for incident management, ensuring timely and effective response to critical system incidents.

- Designed and implemented Spark on Kubernetes to efficiently run and manage large-scale Spark applications, improving the organization's big data processing and analysis capabilities.- Designed and deployed Apache Airflow on Kubernetes for large-scale data processing pipeline, ensuring high scalability and reliability. Enabled efficient submission of Spark jobs, leading to improved data processing speed and efficiency.

- Designed and build a highly available and cost-effective observability Platform - Thanos to manage a heterogeneous workload environment(AKS + GKE + EKS). The platform provided a single pane of view, offers cheap data access, enables better insights, and reduced downtime.- Planned and executed a global co-location merger, optimizing our cloud footprint and costs, resulting in a significant monthly savings of over $500K in AWS invoices alone, and further savings were achieved from reduced administration and maintenance overhead. It enabled us to achieve our cost optimization goals without compromising user experience or performance.- Migrated our Big Data infrastructure from MapR to AWS EFS, resulting in savings of over $150k per month on infrastructure and $400k+ on MapR licenses without impacting user experience or performance. It allowed us to achieve our cost optimization goals while maintaining the same level of data processing capabilities- Successfully onboarded AWS, Azure, & Google Cloud and also migrated specific microservices of Bixby. The migration was executed with a focus on cost optimization, scalability, and high availability. It also enabled us to leverage the strengths of each cloud provider.- Designed and built 20+ scalable and highly available MapR - Big Data clusters configured to run MapReduce, Hive, Pig, and Drill, enabling efficient and effective Big Data processing and analysis. It improved the organization's ability to handle and analyze large data sets, providing better insights into business operations.- Led a two-phase project for continuous learning on infrastructure as code, developing a repository for reusable Terraform and Ansible code and then building a single-click infrastructure provisioning system, improving consistency and reliability.

Linux/Network Admin

Linux/Unix Admin