
Over four months, Hookak Kim enhanced observability and performance management across the longhorn-manager and longhorn-instance-manager repositories. He developed engine-aware metrics collection, enabling reliable monitoring for both V1 and V2 data engines, and introduced Prometheus-integrated metrics for disk and replica resources. Using Go, gRPC, and Protocol Buffers, he implemented QoS controls for replica rebuilding, allowing bandwidth management at both per-volume and global levels. His work included disk performance monitoring APIs and a targeted bug fix to ensure type compatibility in rebuild status reporting. These contributions improved system reliability, proactive monitoring, and operational efficiency in distributed, cloud-native storage environments.

July 2025 performance summary focusing on delivering high-value features, robust observability, and API maturity across longhorn-manager and longhorn-instance-manager. Highlights include QoS-enabled replica rebuilds, disk performance monitoring with Prometheus exposure, and enhanced disk metrics APIs, underpinned by a targeted bug fix to ensure type compatibility in rebuild status reporting.
July 2025 performance summary focusing on delivering high-value features, robust observability, and API maturity across longhorn-manager and longhorn-instance-manager. Highlights include QoS-enabled replica rebuilds, disk performance monitoring with Prometheus exposure, and enhanced disk metrics APIs, underpinned by a targeted bug fix to ensure type compatibility in rebuild status reporting.
April 2025 Monthly Summary: Focus on delivering observability enhancements and QoS-based control for replica rebuilding across Longhorn projects. The work delivered improves system observability, performance predictability, and operational efficiency, enabling faster issue diagnosis, capacity planning, and safer upgrades. Key tech areas: Prometheus metrics integration, ReplicaCollector, QoS policies for per-volume/global rebuild, CRD/types updates, and SPDK rebuild QoS RPCs.
April 2025 Monthly Summary: Focus on delivering observability enhancements and QoS-based control for replica rebuilding across Longhorn projects. The work delivered improves system observability, performance predictability, and operational efficiency, enabling faster issue diagnosis, capacity planning, and safer upgrades. Key tech areas: Prometheus metrics integration, ReplicaCollector, QoS policies for per-volume/global rebuild, CRD/types updates, and SPDK rebuild QoS RPCs.
March 2025 monthly summary focusing on the longhorn-manager work on engine rebuild progress monitoring. Delivered a new engine metrics collector and a rebuildStatus metric to track rebuild percentage, data recovery, and synchronization processes. No major bugs fixed documented in this period in the provided data. This instrumentation enhances observability, enables proactive maintenance, and supports faster MTTR in rebuild scenarios. Technologies demonstrated include metrics instrumentation, monitoring integration, and code tracing via the commit referenced below.
March 2025 monthly summary focusing on the longhorn-manager work on engine rebuild progress monitoring. Delivered a new engine metrics collector and a rebuildStatus metric to track rebuild percentage, data recovery, and synchronization processes. No major bugs fixed documented in this period in the provided data. This instrumentation enhances observability, enables proactive maintenance, and supports faster MTTR in rebuild scenarios. Technologies demonstrated include metrics instrumentation, monitoring integration, and code tracing via the commit referenced below.
February 2025: Delivered engine-aware MetricsGet capabilities across Longhorn components to enable reliable metrics collection from both V1 and V2 data engines. Implemented core changes in ProxyOps and data engine handling, updating client and proxy layers to support multiple engine types and ensure metrics can be fetched regardless of underlying engine version. This work lays the foundation for improved observability, capacity planning, and SLA reporting across multi-engine deployments.
February 2025: Delivered engine-aware MetricsGet capabilities across Longhorn components to enable reliable metrics collection from both V1 and V2 data engines. Implemented core changes in ProxyOps and data engine handling, updating client and proxy layers to support multiple engine types and ensure metrics can be fetched regardless of underlying engine version. This work lays the foundation for improved observability, capacity planning, and SLA reporting across multi-engine deployments.
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