Alteryx Machine Learning Cloud Deployment (Single Tenant)

Last modified: September 30, 2022

All non-emergency changes (both infrastructure and application) go through a controlled and defined process. We test the code and deploy it in a staggered fashion across multiple segmented networks before we submit it for consideration to release. We extensively test all code with multiple methodologies that include unit, end-to-end, regression, and manual tests. We leverage predetermined cadences and windows to minimize the disruption of actual deployments. Changes designated as high-risk require additional tests and approvals. This is in addition to the business controls in place that include segregation of duties and independent reviewers as final approvers for inclusion for a release.

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