Balakrishna V

Architected and maintained scalable multi-cloud infrastructure (AWS, Azure, GCP) supporting performance-intensive AI/ML workloads.

Designed and implemented AI-driven prompts for shell scripts, YAML configurations, and monitoring dashboards, orchestrating scalable automation within CI/CD pipelines using Jenkins, Azure DevOps, and GitHub Actions.

Reduced release activity time by 90% and achieved 99% faster deployments by implementing CI/CD pipelines and Datadog Watchdog anomaly detection.

Enhanced system observability and reduced incidents by implementing Datadog AIOps and anomaly detection, proactively identifying and forecasting bottlenecks.

Optimized database performance, reducing query response time by 90% through Datadog monitoring, performance tuning, and efficient resource allocation.

Accelerated API and service performance by implementing Datadog end-to-end tracing and AI-powered insights, optimizing routing and load balancing.

Automated deployment pipelines using Octopus, reducing deployment times by 50% and minimizing manual intervention.

Boosted application reliability to 99.98% through advanced end-to-end observability and rapid rollback strategies, achieving near zero-downtime releases.

Orchestrated multi-cloud migration (AWS, Azure, GCP) and scaling of servers and databases, driving a 35% system performance increase.

Leveraged Datadog AIOps and predictive analytics to increase reliability and minimize high-priority incidents by 60%.

Implemented Datadog across multiple application servers and Docker containers to enhance monitoring capabilities.

Led the successful migration of on-premise infrastructure and applications to Azure, enhancing cloud adoption.

Automated Azure resource provisioning using Terraform templates and parameterized YAML pipelines in Azure DevOps.

Set up AKS for container orchestration and developed CI/CD pipelines using Azure DevOps, achieving near zero-downtime deployments.

Achieved over 99.9% uptime by automating redundant processes and establishing multi-region failover across Azure.

Streamlined security implementation in Azure cloud environments and introduced best practices for remediation.

Developed AppDynamics-driven incident response playbooks, enabling rapid resolution of critical issues.

Managed end-to-end release cycles, including scheduling, status communication, and rollout plans, ensuring successful software deployments.

Managed multi-region deployments with 99.99% uptime by optimizing server, infrastructure, and database architecture to handle traffic spikes.

Automated database scaling and implemented optimizations, supporting 50% higher workloads without performance degradation.

Automated zero-touch release pipelines using Jenkins and Nexus, implementing Git branching and naming conventions for streamlined deployments.

Designed and implemented a comprehensive CI/CD automation system, enhancing development lifecycle efficiency.

Increased application reliability to 99.98% by automating deployment, monitoring, and scaling routines, proactively adjusting resources to meet demand.

Reduced deployment windows by 70% and scaled infrastructure to accommodate 2x user sessions during peak loads without performance loss.

Led legacy infrastructure migration, optimizing server allocation and database performance for enhanced scalability.

Deployed highly available Azure IaaS VMs and PaaS services, implementing Availability Sets and Site Recovery for business continuity.

Built highly available multi-region Azure application environments using CDN, Traffic Manager, App Services, and various Azure storage and database solutions.

Configured Azure Role-Based Access Control (RBAC) to enforce least privilege principles and segregate duties within the team.

Managed and troubleshot data migrations from on-premises to S3 buckets, configuring VPC networks and ELB in compliance with client policies.

Engineered multi-region, highly available environments, ensuring 99.99% uptime and on-demand scaling of server and database resources.