Free SAFe-DevOps Exam Braindumps (page: 8)

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Which steps in the value stream should be the main focus when prioritizing improvement items?

  1. Steps with a high Flow Efficiency
  2. Steps with short Active Time and high %C&A in the future-state map
  3. Steps with low Percent Complete and Accurate (%C&A) and short Active Time in the current-state map
  4. Steps with a long Active Time

Answer(s): B

Explanation:

According to the SAFe DevOps Practitioner 6.0 study guide1, when prioritizing improvement items, the steps with short Active Time and high %C&A in the future-state map should be the main focus. Active Time is the amount of time a step spends on performing work, while %C&A is the percentage of capacity utilization of a step. The future-state map shows how the Value Stream will look like after implementing improvements, based on customer feedback and business value. The improvement items are ranked by their impact on flow efficiency, customer satisfaction, and business agility. The steps with short Active Time and high %C&A in the future-state map indicate that they are bottlenecks or waste sources that need to be eliminated or reduced as soon as possible. Therefore, they should be prioritized for improvement actions.



What should be measured in a CALMR approach to DevOps?

  1. Deployment frequency
  2. Mean time to restore
  3. Everything
  4. Flow, quality, and value

Answer(s): D

Explanation:

The correct answer is D. Flow, quality, and value should be measured in a CALMR approach to DevOps. The CALMR approach to DevOps is a mindset that guides the ARTs toward achieving continuous value delivery by enhancing culture, automation, lean flow, measurement, and recovery. Measurement is one of the key elements of the CALMR approach, as it provides data and feedback to monitor and improve the performance and outcomes of the solution delivery process. Measurement involves collecting and analyzing metrics that reflect the flow, quality, and value of the solution, such as:
Flow metrics ­ Flow metrics measure the efficiency and reliability of the delivery process, such as lead time, cycle time, throughput, work in progress, and flow efficiency. Flow metrics help to identify and eliminate waste and bottlenecks in the value stream, and to optimize the flow of value to the customer.
Quality metrics ­ Quality metrics measure the functionality and stability of the solution, such as defect rate, defect density, defect leakage, mean time to detect, mean time to resolve, and test coverage. Quality metrics help to ensure that the solution meets the functional and nonfunctional requirements and standards, and to detect and resolve any issues or defects as early as possible. Value metrics ­ Value metrics measure the outcomes and benefits of the solution, such as customer satisfaction, retention, engagement, revenue, and net promoter score. Value metrics help to evaluate the validity of the hypotheses and assumptions about the customer value proposition, and to guide the decision making and prioritization of the features12



What is a possible outcome of the Release activity?

  1. A Solution is migrated to the cloud
  2. A Solution is made available to internal users
  3. A Solution infrastructure is provisioned
  4. A Solution is deployed to production

Answer(s): D

Explanation:

According to the SAFe DevOps Practitioner 6.0 study guide1, the Release activity is the final step in the Continuous Delivery Pipeline that deploys the Solution to production. Production is where the Solution is available for end users to operate and consume. The Release activity involves verifying that the Solution meets the quality and security requirements, monitoring its performance and health, and responding to any issues or incidents that may arise. The Release activity also enables continuous improvement by measuring the business value of the Solution and collecting feedback from customers and stakeholders.



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

  1. It helps define the minimum viable product (MVP)
  2. It helps operations teams know where to apply emergency fixes
  3. It helps quickly create balanced scorecards for stakeholder review
  4. It helps link objective production data to the hypothesis being tested

Answer(s): D

Explanation:

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.






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