Amazon SageMaker vs. Amazon SageMaker Debugger vs. VisualVM vs. jscoverage Comparison Chart

Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values.

jscoverage tool, both node.js and JavaScript support. Enhance the coverage range. Use mocha to load the jscoverage module, then it works. jscoverage will append coverage info when you select list or spec or tap reporter in mocha. You can use covout to specify the reporter, like HTML, and detail. The detail reporter will print the uncovered code in the console directly. Mocha runs test case with jscoverage module. jscoverage will ignore files while listing in covignore file. jscoverage will output a report in HTML format. jscoverage will inject a group of functions into your module exports. default jscoverage will search covignore in the project root. jscoverage will copy exclude files from the source directory to the destination directory.