# deepops-ai/deepops **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/deepops-ai-deepops).** 3,965 stars · 500 forks · TypeScript · NOASSERTION ## Links - GitHub: https://github.com/deepops-ai/deepops - Homepage: https://deepops.io - awesome-repositories: https://awesome-repositories.com/repository/deepops-ai-deepops.md ## Topics `apm` `jaeger` `observability` `opentelemetry` `prometheus` `tracing` `xo` ## Description DeepOps is a full-stack observability platform and application performance monitoring tool. It serves as a distributed service observability suite designed to track response times, resource usage, and service health across diverse infrastructure layers. The platform functions as a cross-stack telemetry aggregator, unifying metrics and logs into a single data stream. It incorporates a heuristic anomaly detection system that analyzes performance baselines to identify statistical outliers and predict operational failures. The system covers a broad range of monitoring capabilities, including real-time latency monitoring, distributed trace correlation, and cross-layer resource profiling. It utilizes multi-dimensional data indexing to filter and analyze system metrics across complex technology stacks. ## Tags ### DevOps & Infrastructure - [Observability Stacks](https://awesome-repositories.com/f/devops-infrastructure/observability-stacks.md) — Provides an integrated suite for collecting, storing, and visualizing telemetry data across diverse infrastructure stacks. ### System Administration & Monitoring - [Application Performance Monitoring](https://awesome-repositories.com/f/system-administration-monitoring/application-performance-monitoring.md) — Provides a comprehensive system for tracking response times and resource usage to resolve production bottlenecks. ([source](https://deepops.io)) - [Anomaly Detection](https://awesome-repositories.com/f/system-administration-monitoring/anomaly-detection.md) — Analyzes performance baselines to identify statistical outliers and predict operational failures proactively. - [Real-Time Application Performance Monitors](https://awesome-repositories.com/f/system-administration-monitoring/application-performance-monitoring/application-performance-monitoring/real-time-application-performance-monitors.md) — Provides live analysis of application performance metrics with real-time monitoring views. - [Distributed Observability Platforms](https://awesome-repositories.com/f/system-administration-monitoring/distributed-observability-platforms.md) — Offers a unified platform for monitoring health and latency across complex microservice architectures. - [Telemetry Aggregators](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/cross-account-observability-aggregators/telemetry-aggregators.md) — Centralizes and routes observability streams from multiple infrastructure layers into a unified view. - [Observability Platforms](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms.md) — Aggregates logs, metrics, and traces to provide a unified view of health and latency across distributed stacks. - [Telemetry Collection and Aggregation](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/telemetry-collection-aggregation.md) — Unifies metrics and logs from diverse infrastructure layers into a single data stream for holistic observation. - [Distributed Observability Platforms](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/telemetry-collection-aggregation/distributed-observability-platforms.md) — Aggregates telemetry from multiple nodes into a centralized architecture for scalable observability of service health and performance. - [Service Discovery & Observability](https://awesome-repositories.com/f/system-administration-monitoring/service-discovery-observability.md) — Measures service health and latency across complex stacks to identify operational issues. - [Service Observability Integrations](https://awesome-repositories.com/f/system-administration-monitoring/service-discovery-observability/service-observability-integrations.md) — Measures service health and latency across distributed stacks using tracing, metrics, and logging. ([source](https://cdn.jsdelivr.net/gh/deepops-ai/deepops@main/README.md)) - [Infrastructure Monitoring](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/metric-performance-monitors/infrastructure-monitoring.md) — Collects and tracks system metrics and resource utilization to detect potential failures before they impact users. ### Data & Databases - [Unified Telemetry Backends](https://awesome-repositories.com/f/data-databases/query-engines/promql-compatible-engines/embedded-promql-in-sql/unified-telemetry-backends.md) — Aggregates metrics and logs from diverse infrastructure layers into a single telemetry pipeline. - [Multi-Dimensional Data Indexing](https://awesome-repositories.com/f/data-databases/multi-dimensional-data-indexing.md) — Organizes system metrics by multiple attributes to allow rapid filtering and drilling down into bottlenecks. ### Networking & Communication - [Correlation Tracing](https://awesome-repositories.com/f/networking-communication/communication-protocols-architectures/request-processing-architectures/request-processing/middleware-based-request-pipelines/correlation-tracing.md) — Links requests across multiple microservices using unique identifiers to map full user transaction paths. ### Development Tools & Productivity - [Cross-Layer Profilers](https://awesome-repositories.com/f/development-tools-productivity/debugging-profiling-testing/debugging-diagnostics/performance-resource-profilers/resource-profiling-suites/cross-layer-profilers.md) — Correlates hardware and software consumption patterns to identify the root causes of application performance drops. ### Software Engineering & Architecture - [Performance Baseline Analyzers](https://awesome-repositories.com/f/software-engineering-architecture/baseline-management/agent-performance-baselines/performance-baseline-analyzers.md) — Identifies performance anomalies by comparing real-time data against historical heuristics to detect outliers. ### Testing & Quality Assurance - [Request Latency Sampling](https://awesome-repositories.com/f/testing-quality-assurance/performance-testing-analysis/performance-diagnostics/performance-measurement/request-latency-sampling.md) — Provides continuous sampling of server request response times to detect performance degradation. - [Resource Exhaustion Profilers](https://awesome-repositories.com/f/testing-quality-assurance/performance-testing-analysis/performance-profiling/hardware-resource-profilers/resource-exhaustion-profilers.md) — Monitors hardware and software consumption to correlate resource exhaustion with application performance drops.