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Risk Management Python

Risk Management Tutorials in the Python Stack.

Bad Ship Happens

We get it—bad ship happens. However, disruptions don't have to be. With LaunchDarkly, you can manage your risk and mitigate disruptions.

In this repo, you will find different ways that LaunchDarkly helps you mitigate risk and instructions for implementing them in your projects.

Progressive Rollouts

Introduce new features gradually within your application, which allows for controlled exposure and real-time impact assessment. Instead of deploying new features to all users simultaneously, start with a small segment—perhaps 1%—then increase to 5% and 10%—moving to the next group only when you're confident in the stability of your code. This phased approach helps contain potential disruptions, ensuring small updates don’t become big problems.

🔗 How to mitigate risk by implementing progressive rollout of new features in a Python application using LaunchDarkly.

Automated Monitoring and Rollbacks

Detect issues early by continuously monitoring feature performance. Add this to the capability to revert to previous states to ensure your services and applications remain reliable.

🔗 How to implement kill switch feature flags in a Python application using LaunchDarkly.

Runtime Configuration Management

Sometimes, swift adjustments are necessary inside a production environment, even for minor changes. Quickly toggle features on or off by incorporating clear demarcations using flags in your code. This ability to modify settings without deploying new code provides the flexibility needed to respond rapidly to unforeseen challenges or shifts in a live environment while maintaining the reliability your customers need.

Targeted Segments.

Tailor features based on various parameters to create a more personalized approach. This enhances the user experience while simultaneously reducing broader risks. With strategic targeting, you can ensure that updates are rolled out in a controlled and secure manner, optimizing functionality and security for different user segments.

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