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scikit-learn

scikit-learn

Use the New Relic scikit-learn quickstart to improve the performance of your scikit-learn.

What's included?

alerts
3
scikit-learn observability quickstart contains 3 alerts. These alerts detect changes in key performance metrics. Integrate these alerts with your favorite tools (like Slack, PagerDuty, etc.) and New Relic will let you know when something needs your attention.
Predictions
This alert is triggered if prediction exceeds 1000 for 5 minutes.
Data Drift
This alert is triggered if data drift exceeds 1 for 5 minutes.
Model Drift
This alert is triggered if model drift exceeds 1 for 5 minutes.
dashboards
0
This quickstart doesn't include any dashboards. Do you think it should?
You can edit this quickstart to add helpful components. View the repository and open a pull request.
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The Importance of Monitoring scikit-learn Models in Production

scikit-learn is a widely-used machine learning library in the Python ecosystem. When deploying these models in production environments, continuous monitoring during inference becomes essential for several key reasons:

Performance optimization:

By keeping an eye on your models, you can detect and rectify performance bottlenecks, ensuring that predictions are made efficiently and promptly.

Early detection of issues:

Through vigilant monitoring, problems such as delayed inference times or unexpected outputs can be identified early on, allowing for swift interventions and minimal service disruption.

Assured Reliability:

Active monitoring guarantees that the scikit-learn models remain dependable, reinforcing user trust in the predictions and insights provided.

Comprehensive monitoring quickstart for scikit-learn

By placing emphasis on real-time monitoring during the inference phase, you not only ensure the efficacy of your training but also guarantee that your scikit-learn models are robust and reliable when serving users.

What’s included in the scikit-learn quickstart?

New Relic scikit-learn monitoring quickstart provides quality out-of-the-box reporting:

  • Obtain insights into how your scikit-learn models are performing in real-time
  • Alerts on model performance: Set up proactive notifications for any unusual behavior or degradation in the performance of your models

How to use this quickstart

  • Sign Up for a free New Relic account or Log In to your existing account.
  • Click the install button.
  • Install the quickstart to get started or improve how you monitor your environment. They're filled with pre-built resources like dashboards, instrumentation, and alerts.
Authors
New Relic
Jyothi Surampudi
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