What method will best help Jared estimate the downtime that will result from a planned change?

The most effective method for Jared to estimate the downtime resulting from a planned change is by performing the change in a test environment. This approach allows him to simulate the planned change under controlled conditions without impacting the production environment. By doing so, he can assess various factors that may influence downtime, including the efficiency of the change process, any unexpected complications that may arise, and the time required for the system to recover after the change.

Testing the change in a non-production environment provides valuable insights into the real-world implications of the change. It enables Jared to identify potential issues in advance and gauge whether the downtime predicted aligns with what is actually observed during the simulation. This real-time data gathering helps inform a more accurate estimate for the planned implementation.

While reviewing service level agreements might provide guidelines on acceptable downtime or service interruptions, it does not give direct insights into how much downtime will be specifically incurred for this change. Consulting with stakeholders may yield different perspectives or expectations regarding downtime but lacks empirical evidence needed for accurate estimation. Documenting previous downtimes can inform Jared about past experiences but isn't as effective as conducting a current test that directly replicates the conditions of the planned change.