C# Metrics Libraries

App Metrics is an open-source and cross-platform .NET library used to record and report metrics within an application.

StatsD is a metrics aggregator and UDP collection server that collects system counters and timers. It functions as a time-series data forwarder, receiving high-frequency metric updates via a lightweight line protocol and summarizing them before flushing the data to a backend. The project features a pluggable metrics backend framework, allowing aggregated statistics to be routed to various third-party monitoring services or time-series databases such as Graphite. It supports horizontal scaling and high availability through a proxy ring distribution system that forwards incoming packets across

Quickwit is a cloud-native, distributed search engine designed for observability data such as logs, traces, and metrics. It functions as an observability backend that decouples compute from storage by persisting indices directly in S3-compatible cloud object stores. The system is distinguished by its compatibility with the Elasticsearch REST API, allowing it to integrate with existing clients and log shippers without reconfiguration. It also serves as an OpenTelemetry data indexer, ingesting technical data via the OpenTelemetry Protocol using gRPC and HTTP. The engine utilizes a hybrid of co

Fluent Bit is a cloud-native log shipper and unified telemetry collector designed as a resource-efficient data pipeline. It ingests logs, metrics, and traces from multiple sources, processing them in real-time before routing the data to external storage backends. The project functions as a real-time stream processor and OpenTelemetry log processor, capable of transforming and filtering data using SQL and conditional logic. It also acts as a distributed tracing agent that can sample traces to reduce data volume while preserving full request paths. The system provides reliable data delivery th

Netdata is a distributed observability platform designed for real-time infrastructure monitoring and performance tracking. It functions as a high-frequency agent that collects system, container, and application metrics with per-second precision, providing both local visualization and centralized aggregation across complex, multi-cloud environments. The platform distinguishes itself through edge-based intelligence, utilizing local machine learning models to automatically detect performance anomalies without requiring manual configuration or external query engines. Its architecture prioritizes

Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r

KEDA is a Kubernetes event-driven autoscaler and cloud event scaling engine. It functions as a custom metrics provider that monitors external event sources—including message brokers, databases, and cloud metrics—to dynamically adjust the replica counts of containerized workloads. The project is distinguished by its scale-to-zero workflow, which reduces workloads to zero replicas during inactivity and automatically restarts them when new events are detected. It operates as a multi-cloud event trigger system, using a pluggable scaler interface to integrate with a wide array of third-party servi