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Scaled Agile Exam SAFe-DevOps Topic 5 Question 34 Discussion

Actual exam question for Scaled Agile's SAFe-DevOps exam
Question #: 34
Topic #: 5
[All SAFe-DevOps Questions]

Why is hypothesis evaluation important when analyzing data from monitoring systems in the Release on Demand aspect?

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Suggested Answer: D

According to the SAFe DevOps Practitioner 6.0 study guide1, hypothesis evaluation is important when analyzing data from monitoring systems in the Release on Demand aspect because it helps link objective production data to the hypothesis being tested. Hypothesis evaluation is the process of measuring and comparing the actual outcomes of a hypothesis with the expected outcomes based on customer feedback and business value. Hypothesis evaluation helps DevOps teams to validate or invalidate their hypotheses, learn from their mistakes, and improve their solutions. By linking objective production data to the hypothesis being tested, DevOps teams can see how well their solutions are delivering value to customers and achieving their goals.


by Virgie at Jun 11, 2025, 04:51 AM

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Carmen
25 days ago
C. Oh, come on, balanced scorecards? That's so 2005. I prefer to keep my stakeholders informed with a good old-fashioned game of Tetris. Really gets the heart racing, you know?
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Giuseppe
27 days ago
D. Absolutely the right answer. Hypothesis evaluation is the key to making sure our monitoring data is actually telling us something meaningful.
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Renay
2 days ago
D) It helps link objective production data to the hypothesis being tested
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Jimmie
6 days ago
D) Absolutely the right answer. Hypothesis evaluation is the key to making sure our monitoring data is actually telling us something meaningful.
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Lizette
13 days ago
A) It helps define the minimum viable product (MVP)
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Vincent
1 months ago
B. Definitely the best option here. Knowing where to apply those emergency fixes is crucial when you're trying to keep the system running smoothly.
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Yan
13 days ago
D) It helps link objective production data to the hypothesis being tested
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Johanna
16 days ago
B) It helps operations teams know where to apply emergency fixes
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Grover
23 days ago
A) It helps define the minimum viable product (MVP)
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Alexia
1 months ago
D. This helps us connect the data we're collecting to the actual hypothesis we're trying to test. Gotta love a good old-fashioned data-driven approach, am I right?
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Timothy
19 days ago
D
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Sang
20 days ago
A
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Jacqueline
1 months ago
I believe it also helps define the minimum viable product, which is crucial for Release on Demand aspect.
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Kristel
2 months ago
I agree with Pamella. It helps us understand if our assumptions are correct based on real data.
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Pamella
2 months ago
I think hypothesis evaluation is important to link objective production data to the hypothesis being tested.
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