Ankit Anand

Ankit Anand, associated with the SigNoz Team, has played a pivotal role in benchmarking SigNoz against popular logging solutions such as the ELK (Elasticsearch, Logstash, and Kibana) stack and the PLG (Promtail, Loki, and Grafana) stack. Through his research, Anand found that SigNoz is approximately 2.5 times faster than ELK and uses about 50% less resources for data ingestion. Additionally, he discovered that SigNoz is roughly 13 times faster than ELK in executing aggregate queries and requires only half the storage for the same volume of logs. Anand’s methodology included the use of four virtual machines, where three were dedicated to generating logs using flog, a fake log generator, and one for deploying the logging solution. He implemented a SigNoz cluster architecture to assess performance metrics such as CPU, memory, and disk usage during data ingestion and evaluated the query performance across various commonly used queries. His findings also emphasized the critical role of high disk utilization in preventing data loss due to backpressure, a key consideration for systems handling large volumes of data.