Timberlake is a Go server paired with a React.js frontend. It improves on existing Hadoop job trackers by providing a lightweight realtime view of your running and finished MapReduce jobs. Timberlake exposes the counters and configuration that are the most useful, allowing you to get a quick overview of the whole cluster or dig into the performance and behavior of a single job.It also provides waterfall and boxplot visualizations for jobs. We've found that these visualizations can be really helpful for figuring out why a job is slow. Is it launching too many mappers and overloading the cluster? Are reducers launching early and starving the mappers? Does the job have reducer skew? You can use the counters of bytes written, shuffled, and read to understand the network and I/O behavior of your jobs. And when there's a crash, Timberlake will show you tracebacks from the logs to help you debug the job.