Bharghava Varun Ayada

I joined Walmart's observability team to help build and scale the log search and tracing infrastructure. Currently working on a dynamic throttling mechanism in fluent-bit by writing a custom Go output plugin to throttle sudden and sustained burst of log volume. I'm also working on a new log ingestion pipeline for the next generation in-house logging infrastructure using Go, Kafka, Clickhouse, etc

Built micro services using Go, gRPC, protocol buffers that handle up to 15k rps. Architect view counts service that handles 30k rps using Go, RDS and Redis. Built upload service to handle media uploads and image processing using pub/sub pattern. Built defender service to rate limit users by analysing millions of log lines per minute. Built search service that indexes 1k docs/min into Elasticsearch

I joined Twilio Segment's observability team in the Personas vertical to help integrate observability into the Personas microservices. During this period, I worked on BCR compliance which involved automated cleanup of terabytes of churned customers data from all our data stores. Built deletion managers in Go to delete data from data stores like BigQuery, BigTable, DynamoDB, S3, MySQL and Redis.

Implemented hybrid transcoding that automatically switched to AWS when in-house transcoding service ran out of compute resources. Built analytics dashboards with infra performance and capacity data for the video transcoding service. Built infra to handle 8x increase in transcoding requests when Flickr increased storage per user to 1 TB. Setup Splunk to aggregate logs from hundreds of servers.