Arpan Sharma

Led engineering teams in observability strategy, aligning with business goals; mentored 15+ engineers on Dynatrace best practices, Leverage AIOps & MLOps in DevOps lifecycle. Established shift-left reliability culture early in the DevOps lifecycle, enabling proactive reliability and building strong observability foundations for Tier-1 applications to achieve superior system resilience. Developed FinOps prototype using Python, Boto3, and OpenAI APIs for real-time AWS cost insights closely integrated with Dynatrace alerting, enabling intelligent optimization. Collaborated on hybrid cloud governance with focus on observability-driven incident response.

Led 11-member SRE team to achieve 99.9% uptime for 70+ microservices via Dynatrace full-stack observability across AWS, Azure, GCP, and VMware—implementing AI-based alerting to reduce MTTR by 40% and false alerts by 40%. Integrated Dynatrace with CloudWatch, Azure Monitor, and GCP Operations for proactive monitoring, SLO governance, and incident orchestration via PagerDuty, ServiceNow/Slack, cutting detection time by 40%. Migrated 250+ applications to multi-cloud, optimizing observability for cost savings (20-30%) using Dynatrace, AWS Budgets, and Azure Cost Management, automated non-prod shutdowns. Implemented IaC practices using Terraform, CloudFormation, and ARM/Bicep, automating provisioning and environment consistency, cutting manual configuration efforts by 40%. Built CI/CD pipelines with observability gates using Jenkins, Spinnaker, and Chaos Engineering (Litmus & FIS Chaos), improving reliability by 25% and deployment frequency by 50%. Supported data platforms (AWS EMR/Redshift, Azure Synapse) with Dynatrace-monitored ETL pipelines; ensured DevSecOps compliance for global services. Drove Agile & Scrum ceremonies (stand-ups, sprint planning, retrospectives) as Scrum Master, ensuring continuous delivery excellence and team accountability.

Managed 3300 Linux servers with focus on monitoring and incident reduction; implemented SIPs using Bash/Python scripting, reducing incidents by 20% and manual effort by 50%. Enhanced environment stability through early observability practices, stabilizing production escalations.

Provided L3 DevOps support for infrastructure and applications; set up environments (Dev/QA/UAT) with monitoring for high availability and disaster recovery. Automated deployments via Jenkins and shell scripts, reducing times by 30%; collaborated on scalable observability for application performance.