FROM ON-DEMAND TO POOLED: OPTIMIZING COMPUTE CONTAINER ALLOCATION FOR CLOUD-BASED NOTEBOOK ENVIRONMENTS - CHEEKURI, KARTHIK CHAKRAVARTHY (TPM – Testing, Psychometrics, Methodology in Applied Psychology, 2025)
Interactive notebook capabilities integrated within cloud database systems face inherent challenges related to provisioning latency and resource utilization. Traditional on-demand provisioning models create dedicated compute environments at runtime, installing required software components during session initialization, which introduces significant startup delays and inefficient resource allocation patterns. The architectural transition to pre-warmed container pools addresses these challenges by maintaining ready-to-deploy compute environments that can be instantly assigned to users upon request. This pooling strategy enables millisecond-scale allocation compared to the multi-second delays characteristic of just-in-time provisioning. Empirical results demonstrate a reduction in startup time from 4.2 seconds to 180 milliseconds, representing a 95.7% improvement. Container lifecycle management incorporates efficient reset mechanisms that return idle resources to the pool rather than destroying them, enabling reuse across multiple user sessions. Individual containers serve an average of 3.4 sessions, compared to 1.0 in on-demand models. The transformation substantially reduces the total number of compute containers required by 38% while simultaneously improving user experience through near-instantaneous session availability. Cost per active session decreased by 31% through improved resource efficiency. Shorter idle timeout periods further enhance resource efficiency without compromising user productivity. This architectural evolution demonstrates how strategic resource pooling and reuse patterns can simultaneously optimize both performance characteristics and operational costs in cloud-based interactive computing platforms.