Employment Hero, which was founded in 2014, originally deployed a software stack composed of monolithic applications. It started refactoring those applications to fit a microservices architecture around 2017. At the same time, it made the move toward a Kubernetes-centric environment for hosting its applications.The company’s engineers quickly discovered, however, that the logging and monitoring solution they had in place at the time was not sufficient for managing microservices applications. The platform did not offer an easy way to collect logs within a distributed environment where each service stores logs in a different place, let alone analyze the logs efficiently. Tracing user requests across the logs of multiple services was difficult, and there was no support for live tailing logs to track the latest activity.

As Luong Vo, Platform Engineering Manager atEmployment Hero, explained, “We needed the logging system to be scalable, easy to search, accurate in time, and support live tailing,” and the existing logging solution didn’t do that. At first, Luong and his team experimented with using self-hosted Elasticsearch, Logstash and Kibana—theELK stack—to meet their need for microservices friendly log aggregation and analytics. However, “we found that we were spending too much time scaling Elasticsearch and maintaining the whole stack,” he said, prompting them to search for a more user friendly alternative.

After evaluating other logging platforms, theEmployment Hero team settled on LogDNA.