Best practices for cloud spring cleaning

In the cloud, there are some insidious and barely visible new sources that contribute to software entropy.

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Even the cloud needs spring cleaning. And the cleanup isn’t the refactoring and data quality work that you already know about. Those “big animals” are hard to miss, and now we need to pay attention to the mites and dust-bunnies that we noticed only when they become overwhelming.

These new micro-debts appear quickly and continuously because cloud systems are easy to configure. Add a new field, edit a formula, modify a report, change a picklist value – each of these takes just seconds. But the repercussions of those little changes can lead to big consequences. Aside from the fact there’s no comprehensive way to inventory all the changes, the knock-on effects of new or changed items are hard to assess.

So undoing a change (either to retire something that’s obsolete or to correct a new symptom) is way more work than making the change in the first place. Thanks to compound-interest effects, the collection starts to become as obnoxious as an ant-hill.

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