Engineering Excellence for Operational Simplicity

Every principle directly maps to architectural decisions and product capabilities. For example, ‘Your Infrastructure, Your Data, Your Control’ manifests as edge-native architecture where all observability data stays on-premises. ‘Transparent Economics’ becomes flat per-node pricing with no hidden fees. ‘Intelligence Without Complexity’ delivers as zero-configuration auto-discovery and algorithmic dashboards. These aren’t aspirational statements - they’re engineering commitments validated by 80,000+ GitHub stars and 1.5M daily downloads.

We choose values over short-term profit every time. Our business model aligns with these principles: we profit by making monitoring better (engineering excellence), not by charging for metrics volume. When faced with decisions like ‘should we add per-metric pricing?’ or ‘should we centralize data for easier monetization?’, we consistently choose the path that serves customer operational needs - even if it means lower short-term revenue. This long-term thinking has built trust with 80,000+ GitHub community members.

These principles guide every technical and product decision at Netdata. When we face choices, we ask: ‘Does this serve our users’ operational needs? Does this simplify their work? Does this respect their data and their control?’ If the answer is no, we don’t do it. Our open-source foundation (GPLv3+) provides community accountability - any deviation from these values would be immediately visible in our code. Additionally, our SOC 2 Type 2 certification and OpenSSF best practices provide external validation of our commitments.

Absolutely. Our performance claims are backed by independent research and reproducible benchmarks. The University of Amsterdam study (ICSOC 2023) independently validated Netdata as the most energy-efficient monitoring solution with lowest CPU and memory overhead. Our Prometheus comparison is a Netdata benchmark with methodology published at netdata.cloud/blog/netdata-vs-prometheus-2025/. Additionally, our open-source code (80,000+ GitHub stars) allows anyone to audit our implementation and verify claims directly.

We’re transparent about limitations and honest about fit. For example, if you need a full APM suite, we’ll tell you what Netdata’s distributed tracing covers (OpenTelemetry traces with duration heatmaps, RED analysis, waterfalls and span details) and recommend complementary tools. If you need code-level profiling, we’ll explain our process-level monitoring capabilities and suggest integration with dedicated APM tools. We compete by being better at what we do, not by claiming to do everything. Our goal is to be the best infrastructure observability platform, not to lock you into an all-or-nothing relationship.

Our pricing model directly embodies our values: predictable per-node pricing for infrastructure monitoring with volume discounts, no charges for metrics volume, Logs Monitoring (querying logs in place), users, data retention or containers, no hidden fees. This transparent pricing means you can scale infrastructure freely without anxiety about monitoring bills. We profit when you succeed and grow your infrastructure - not when you generate more metrics. Compare this to volume-based platforms where success (more metrics, more logs) means exponentially higher bills. Our economics align with your operational needs, not against them.

We provide two AI integration paths that respect your choice: (1) Netdata Cloud AI Features with managed LLM access and optimized playbooks, and (2) Model Context Protocol (MCP) for bring-your-own-LLM using Claude, ChatGPT, Gemini, or custom models. This dual approach means you’re never locked into our AI vendor choices. Additionally, our ML-based anomaly detection runs locally on every metric automatically - not as a premium feature requiring configuration. ML requires 15 minutes for first anomaly detection and reaches full confidence in 2 days. We embed AI throughout the platform to democratize expertise, not to create vendor dependency.