
Developed a time-estimation feature for in-progress jobs in the aws-deadline/deadline-cloud repository, enhancing planning visibility and SLA management for users. The solution was implemented in Python, focusing on backend and CLI development. The estimation logic calculates the average duration of completed tasks and multiplies it by the number of remaining tasks, presenting the result in a human-readable format such as “5 minutes” or “1 hour, 30 minutes.” Integration work ensured that both the job list and job get endpoints surfaced these estimates. Edge cases, including jobs with no completed tasks or already finished jobs, were handled by returning “N/A.”
March 2026: Delivered a new time-estimation capability for in-progress jobs in aws-deadline/deadline-cloud, significantly improving planning visibility and SLA management. The feature estimates remaining time by averaging durations of completed tasks and multiplying by the number of remaining tasks, outputting human-readable durations (e.g., '5 minutes', '1 hour, 30 minutes') and returning 'N/A' when estimation is not possible (no completed tasks yet or job is finished). Implemented end-to-end integration with both the deadline job list and the deadline job get endpoints to surface the estimates.
March 2026: Delivered a new time-estimation capability for in-progress jobs in aws-deadline/deadline-cloud, significantly improving planning visibility and SLA management. The feature estimates remaining time by averaging durations of completed tasks and multiplying by the number of remaining tasks, outputting human-readable durations (e.g., '5 minutes', '1 hour, 30 minutes') and returning 'N/A' when estimation is not possible (no completed tasks yet or job is finished). Implemented end-to-end integration with both the deadline job list and the deadline job get endpoints to surface the estimates.

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