
Jonathan Jaegerman developed core backend features for the temporalio/sdk-go and temporalio/sdk-java repositories, focusing on scalable workload handling and resource tracking. He engineered dynamic autoscaling for task pollers in Go, enabling the system to adjust poller concurrency based on load, which improved throughput and resource utilization. In Java, he implemented async workflow polling slot usage tracking, ensuring accurate slot accounting during asynchronous execution. Both projects included comprehensive automated and unit tests to validate behavior under varying conditions. Jonathan’s work demonstrated depth in concurrency, backend development, and testing, addressing system reliability and efficiency for high-concurrency distributed workflow environments.
March 2026 monthly summary for temporalio/sdk-java focused on delivering Async Workflow Polling Slot Usage Tracking and strengthening tests and stability. Implemented marking of task slots as used when an async poll task executes, updated the polling flow accordingly, and added slot supplier tests to validate used-slot tracking during workflow execution. The change reduces risk of slot leakage and improves resource accounting and reliability in asynchronous polling.
March 2026 monthly summary for temporalio/sdk-java focused on delivering Async Workflow Polling Slot Usage Tracking and strengthening tests and stability. Implemented marking of task slots as used when an async poll task executes, updated the polling flow accordingly, and added slot supplier tests to validate used-slot tracking during workflow execution. The change reduces risk of slot leakage and improves resource accounting and reliability in asynchronous polling.
Month: 2025-11 — Delivered a dynamic autoscaling feature for task pollers in temporalio/sdk-go to improve throughput, efficiency, and responsiveness under varying load conditions. Implemented adaptive poller deployment that scales from the initial count to the maximum pollers, supported by automated tests validating autoscaling behavior. Updated worker base logic to support max poller count and added scalable poller concurrency tests. This work enhances resource utilization, reduces latency during bursts, and positions the SDK for higher concurrent workloads.
Month: 2025-11 — Delivered a dynamic autoscaling feature for task pollers in temporalio/sdk-go to improve throughput, efficiency, and responsiveness under varying load conditions. Implemented adaptive poller deployment that scales from the initial count to the maximum pollers, supported by automated tests validating autoscaling behavior. Updated worker base logic to support max poller count and added scalable poller concurrency tests. This work enhances resource utilization, reduces latency during bursts, and positions the SDK for higher concurrent workloads.

Overview of all repositories you've contributed to across your timeline