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Added documentation guidance
Lines 34-52, added guidance for documenting chaos experiments and underlining the importance of hypothesis
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articles/chaos-studio/chaos-studio-chaos-experiments.md

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@@ -31,6 +31,25 @@ A chaos experiment is an Azure resource deployed to a subscription, resource gro
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Chaos experiments can target resources in a different subscription than the experiment if the subscription is within the same Azure tenant. Chaos experiments can target resources in a different region than the experiment if the region is a supported region for Chaos Studio.
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## Documenting chaos experiments
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There are several methods for documenting chaos engineering. One approach is to use work items in Azure DevOps Boards or in GitHub Projects. By creating dedicated work items for each experiment, you can track the details, progress, and outcomes of your experiments in a structured manner. This documentation can include information such as the purpose of the experiment, the expected outcomes, the steps followed, the resources involved, and any observations or learnings from the experiment.
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| Aspect | Details | Description |
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|----------------|-------------------------------------------------------------------------------------------|-----------------|
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| Hypothesis | Define the objective and expected outcomes of the experiment | |
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| Attack Layer | Identify which part of the system will be subjected to chaos experiments (e.g., network, database, application layer). | |
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| Duration | Specify the time frame for the chaos experiment. | |
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| Target | Determine the specific targets or components within the system. | |
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| Environment | Define whether the experiment will be conducted in a production, staging, or development environment. | |
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| Observations | Record any data or behavior observed during the experiment. | |
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| Results | Summarize the findings and outcomes of the experiment. | |
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| Action Items | List any action items or steps to be taken based on the results. | |
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The hypothesis is a crucial aspect of a chaos experiment as it defines the objective and expected outcomes of the experiment. It helps in testing the system's ability to handle unexpected disruptions effectively. By formulating a clear hypothesis, you can focus your experiment on specific areas of the system and gather meaningful data to evaluate its resilience.
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By leveraging the features of Azure DevOps Boards or GitHub Projects, you can collaborate with your team, assign tasks, set due dates, and track the overall progress of your chaos engineering initiatives. This documentation serves as a reference for future analysis, sharing knowledge, and improving the resilience of your systems.
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## Next steps
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Now that you understand what a chaos experiment is you're ready to:
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