Worked on the databricks/thanos repository to enhance HTTP data reception by introducing buffer pooling, which reduced heap allocations and garbage collection pressure. Focused on backend development using Go, the work included implementing memory usage safeguards to cap resource consumption and detaching exemplar labels from pooled buffers to prevent cross-request contamination. These changes improved ingestion throughput and made latency more predictable under high load, addressing performance and stability concerns in high-traffic environments. The approach demonstrated a strong understanding of Go memory management, buffer pooling design, and safe label handling, with incremental, well-documented code changes that targeted resource optimization and correctness.