The only agent that thinks for itself

Autonomous Monitoring with self-learning AI built-in, operating independently across your entire stack.

Unlimited Metrics & Logs
Machine learning & MCP
5% CPU, 150MB RAM
3GB disk, >1 year retention
800+ integrations, zero config
Dashboards, alerts out of the box
> Discover Netdata Agents

Centralized metrics streaming and storage

Aggregate metrics from multiple agents into centralized Parent nodes for unified monitoring across your infrastructure.

Stream from unlimited agents
Long-term data retention
High availability clustering
Data replication & backup
Scalable architecture
Enterprise-grade security
> Learn about Parents

Fully managed cloud platform

Access your monitoring data from anywhere with our SaaS platform. No infrastructure to manage, automatic updates, and global availability.

Zero infrastructure management
99.9% uptime SLA
Global data centers
Automatic updates & patches
Enterprise SSO & RBAC
SOC2 & ISO certified
> Explore Netdata Cloud

Deploy Netdata Cloud in your infrastructure

Run the full Netdata Cloud platform on-premises for complete data sovereignty and compliance with your security policies.

Complete data sovereignty
Air-gapped deployment
Custom compliance controls
Private network integration
Dedicated support team
Kubernetes & Docker support
> Learn about Cloud On-Premises

Powerful, intuitive monitoring interface

Modern, responsive UI built for real-time troubleshooting with customizable dashboards and advanced visualization capabilities.

Real-time chart updates
Customizable dashboards
Dark & light themes
Advanced filtering & search
Responsive on all devices
Collaboration features
> Explore Netdata UI

Monitor on the go

Native iOS and Android apps bring full monitoring capabilities to your mobile device with real-time alerts and notifications.

iOS & Android apps
Push notifications
Touch-optimized interface
Offline data access
Biometric authentication
Widget support
> Download apps

The future of infrastructure observability

See our strategic direction across AI-native observability, full-stack signals, operational intelligence, and enterprise platform maturity.

AI-native observability
Full-stack signal coverage
Operational intelligence
Enterprise platform maturity
Agent releases every 6 weeks
Cloud continuous delivery
> Explore Product Roadmap

Best energy efficiency

True real-time per-second

100% automated zero config

Centralized observability

Multi-year retention

High availability built-in

Zero maintenance

Always up-to-date

Enterprise security

Complete data control

Air-gap ready

Compliance certified

Millisecond responsiveness

Infinite zoom & pan

Works on any device

Native performance

Instant alerts

Monitor anywhere

AI-native observability

Continuous delivery

Open source foundation

80% Faster Incident Resolution

AI-powered troubleshooting from detection, to root cause and blast radius identification, to reporting.

True Real-Time and Simple, even at Scale

Linearly and infinitely scalable full-stack observability, that can be deployed even mid-crisis.

90% Cost Reduction, Full Fidelity

Instead of centralizing the data, Netdata distributes the code, eliminating pipelines and complexity.

See and Map Your Entire Network

Live topology, flow analytics, and SNMP device and trap monitoring — unified with your full-stack observability.

Control Without Surrender

SOC 2 Type 2 certified with every metric kept on your infrastructure.

Integrations

800+ collectors and notification channels, auto-discovered and ready out of the box.

800+ data collectors
Auto-discovery & zero config
Cloud, infra, app protocols
Notifications out of the box
> Explore integrations
Real Results
46% Cost Reduction

Reduced monitoring costs by 46% while cutting staff overhead by 67%.

— Leonardo Antunez, Codyas

Zero Pipeline

No data shipping. No central storage costs. Query at the edge.

From Our Users
"Out-of-the-Box"

So many out-of-the-box features! I mostly don't have to develop anything.

— Simon Beginn, LANCOM Systems

No Query Language

Point-and-click troubleshooting. No PromQL, no LogQL, no learning curve.

Enterprise Ready
67% Less Staff, 46% Cost Cut

Enterprise efficiency without enterprise complexity—real ROI from day one.

— Leonardo Antunez, Codyas

SOC 2 Type 2 Certified

Zero data egress. Only metadata reaches the cloud. Your metrics stay on your infrastructure.

Full Coverage
800+ Collectors

Auto-discovered and configured. No manual setup required.

Any Notification Channel

Slack, PagerDuty, Teams, email, webhooks—all built-in.

Built for the People Who Get Paged

Because 3am alerts deserve instant answers, not hour-long hunts.

Every Industry Has Rules. We Master Them.

See how healthcare, finance, and government teams cut monitoring costs 90% while staying audit-ready.

Monitor Any Technology. Configure Nothing.

Install the agent. It already knows your stack.
From Our Users
"A Rare Unicorn"

Netdata gives more than you invest in it. A rare unicorn that obeys the Pareto rule.

— Eduard Porquet Mateu, TMB Barcelona

99% Downtime Reduction

Reduced website downtime by 99% and cloud bill by 30% using Netdata alerts.

— Falkland Islands Government

Real Savings
30% Cloud Cost Reduction

Optimized resource allocation based on Netdata alerts cut cloud spending by 30%.

— Falkland Islands Government

46% Cost Cut

Reduced monitoring staff by 67% while cutting operational costs by 46%.

— Codyas

Real Coverage
"Plugin for Everything"

Netdata has agent capacity or a plugin for everything, including Windows and Kubernetes.

— Eduard Porquet Mateu, TMB Barcelona

"Out-of-the-Box"

So many out-of-the-box features! I mostly don't have to develop anything.

— Simon Beginn, LANCOM Systems

Real Speed
Troubleshooting in 30 Seconds

From 2-3 minutes to 30 seconds—instant visibility into any node issue.

— Matthew Artist, Nodecraft

20% Downtime Reduction

20% less downtime and 40% budget optimization from out-of-the-box monitoring.

— Simon Beginn, LANCOM Systems

Pay per Node. Unlimited Everything Else.

One price per node. Unlimited metrics, logs, users, and retention. No per-GB surprises.

Free tier—forever
No metric limits or caps
Retention you control
Cancel anytime
> See pricing plans

What's Your Monitoring Really Costing You?

Most teams overpay by 40-60%. Let's find out why.

Expose hidden metric charges
Calculate tool consolidation
Customers report 30-67% savings
Results in under 60 seconds
> See what you're really paying

Your Infrastructure Is Unique. Let's Talk.

Because monitoring 10 nodes is different from monitoring 10,000.

On-prem & air-gapped deployment
Volume pricing & agreements
Architecture review for your scale
Compliance & security support
> Start a conversation

Monitoring That Sells Itself

Deploy in minutes. Impress clients in hours. Earn recurring revenue for years.

30-second live demos close deals
Zero config = zero support burden
Competitive margins & deal protection
Response in 48 hours
> Apply to partner

Per-Second Metrics at Homelab Prices

Same engine, same dashboards, same ML. Just priced for tinkerers.

Community: Free forever · 5 nodes · non-commercial
Homelab: $90/yr · unlimited nodes · fair usage
> Get the Homelab Plan

$1,000 Per Referral. Unlimited Referrals.

Your colleagues get 10% off. You get 10% commission. Everyone wins.

10% of subscriptions, up to $1,000 each
Track earnings inside Netdata Cloud
PayPal/Venmo payouts in 3-4 weeks
No caps, no complexity
> Get your referral link
Cost Proof
40% Budget Optimization

"Netdata's significant positive impact" — LANCOM Systems

Calculate Your Savings

Compare vs Datadog, Grafana, Dynatrace

Savings Proof
46% Cost Reduction

"Cut costs by 46%, staff by 67%" — Codyas

30% Cloud Bill Savings

"Reduced cloud bill by 30%" — Falkland Islands Gov

Enterprise Proof
"Better Than Combined Alternatives"

"Better observability with Netdata than combining other tools." — TMB Barcelona

Real Engineers, <24h Response

DPA, SLAs, on-prem, volume pricing

Why Partners Win
Demo Live Infrastructure

One command, 30 seconds, real data—no sandbox needed

Zero Tickets, High Margins

Auto-config + per-node pricing = predictable profit

Homelab Ready
Free Video Course

8-episode Netdata tutorial by LearnLinux.tv

76k+ GitHub Stars

3rd most starred monitoring project

Worth Recommending
Product That Delivers

Customers report 40-67% cost cuts, 99% downtime reduction

Zero Risk to Your Rep

Free tier lets them try before they buy

AI Support Assistant, Available 24/7

Nedi has access to all official documentation, source code, and resources. Ask any question about Netdata—responds in your language.

Deployment & configuration
Troubleshooting & sizing
Alerts & notifications
Evidence-based answers
> Ask Nedi now

Never Fight Fires Alone

Docs, community, and expert help—pick your path to resolution.

Learn.netdata.cloud docs
Discord, Forums, GitHub
Premium support available
> Get answers now

60 Seconds to First Dashboard

One command to install. Zero config. 850+ integrations documented.

Linux, Windows, K8s, Docker
Auto-discovers your stack
> Read our documentation

76,000+ Engineers Strong

615+ contributors. 1.5M daily downloads. One mission: simplify observability.

Per-Second. 90% Cheaper. Data Stays Home.

Side-by-side comparisons: costs, real-time granularity, and data sovereignty for every major tool.

See why teams switch from Datadog, Prometheus, Grafana, and more.

> Browse all comparisons
Edge-Native Observability, Born Open Source
Per-second visibility, ML on every metric, and data that never leaves your infrastructure.
Founded in 2016
615+ contributors worldwide
Remote-first, engineering-driven
Open source first
> Read our story
Promises We Publish—and Prove
12 principles backed by open code, independent validation, and measurable outcomes.
Open source, peer-reviewed
Zero config, instant value
Data sovereignty by design
Aligned pricing, no surprises
> See all 12 principles
Edge-Native, AI-Ready, 100% Open
76k+ stars. Full ML, AI, and automation—GPLv3+, not premium add-ons.
76,000+ GitHub stars
GPLv3+ licensed forever
ML on every metric, included
Zero vendor lock-in
> Explore our open source
Build Real-Time Observability for the World
Remote-first team shipping per-second monitoring with ML on every metric.
Remote-first, fully distributed
Open source (76k+ stars)
Challenging technical problems
Your code on millions of systems
> See open roles
Meet the Team Behind Netdata
Conferences, meetups, and tradeshows where you can see Netdata in action and talk to the engineers who build it.
Live demos and deep dives
Book 1-on-1 meetings
Talks and panel sessions
Event recaps and photos
> See all events
Talk to a Netdata Human in <24 Hours
Sales, partnerships, press, or professional services—real engineers, fast answers.
Discuss your observability needs
Pricing and volume discounts
Partnership opportunities
Media and press inquiries
> Book a conversation
Your Data. Your Rules.
On-prem data, cloud control plane, transparent terms.
Trust & Scale
76,000+ GitHub Stars

One of the most popular open-source monitoring projects

SOC 2 Type 2 Certified

Enterprise-grade security and compliance

Data Sovereignty

Your metrics stay on your infrastructure

Validated
University of Amsterdam

"Most energy-efficient monitoring solution" — ICSOC 2023, peer-reviewed

ADASTEC (Autonomous Driving)

"Doesn't miss alerts—mission-critical trust for safety software"

Community Stats
615+ Contributors

Global community improving monitoring for everyone

1.5M+ Downloads/Day

Trusted by teams worldwide

GPLv3+ Licensed

Free forever, fully open source agent

Why Join?
Remote-First

Work from anywhere, async-friendly culture

Impact at Scale

Your work helps millions of systems

$ guides / bind-dns / bind-dns-monitoring-maturity-model ▌

Operations Guides

BIND monitoring maturity model: from survival to expert

Most BIND deployments catch complete outages but miss the slow-burn failures that cause real incidents: cache pressure spirals, recursive client exhaustion, DNSSEC signature expiry, and kernel-level UDP drops that BIND itself never sees.

This article maps four monitoring maturity levels, from Survival to Expert. Each level adds signals that catch failure patterns invisible to the previous one. Use this as an inventory checklist: identify your current level, then decide which signals to add next based on whether you run a recursive resolver, an authoritative-only server, or a mixed-role deployment.

Signal names come from BIND’s statistics channel (JSON at /json/v1/*, XML at /xml/v3/*), OS-level sources like /proc/net/snmp, and rndc commands. Verify counter names against the statistics output for the exact BIND release in use.

flowchart TD
    L1["L1 Survival
named alive, canary, RSS"] L2["L2 Operational
rate, SERVFAIL, cache, resources"] L3["L3 Mature
RTT, kernel drops, leading indicators"] L4["L4 Expert
per-thread, signing, entropy, NTP"] L1 --> L2 L2 --> L3 L3 --> L4

Level 1: survival

Level 1 answers one question: is named running and answering queries? You will miss every degradation condition, but you will know about total outages.

SignalWhat it catchesSource
Process livenessnamed crashed or killedpgrep -x named
UDP canary queryListener not responding on primary transportdig +time=2 +tries=1 @127.0.0.1 <domain> A (recursive) or dig +norecurse @127.0.0.1 <zone> SOA (authoritative)
TCP canary queryListener not responding on TCP (large responses, zone transfers at risk)Same query with +tcp flag
Process RSSnamed consuming all system memory/proc/$(pgrep -x named)/status VmRSS field

Use pgrep -x named (exact match), not -f, to avoid false positives from named-checkzone or named-checkconf. The canary query must be role-correct: a recursive resolver should probe a domain requiring recursion; an authoritative server should probe +norecurse against a locally served zone. A REFUSED response is not a dead service. It means the ACL denied the query, which may be correct behavior.

What Level 1 cannot detect: rising latency, declining cache hit ratio, increasing SERVFAIL, approaching resource limits, kernel packet drops, zone transfer failures, or DNSSEC validation problems. A BIND server can be slowly dying for days while passing every Level 1 check.

Level 2: operational

Level 2 answers: is BIND working correctly under production load, and are resources healthy?

SignalWhat it catchesSource
Incoming query rateTraffic anomalies, DDoS, flash crowdsRequestv4, Requestv6 in NSStats
SERVFAIL rateResolution failures (upstream timeout, DNSSEC, broken delegation, recursive limit)QrySERVFAIL in NSStats, as ratio of classified responses
Recursive clientsBIND’s circuit breaker approaching trip pointRecursClients in NSStats, as percentage of recursive-clients limit (default 1000)
Cache hit ratioCache effectiveness declining, leading to upstream loadCacheHits / (CacheHits + CacheMisses) per view
Protocol distributionTCP share elevation (truncation, transfers, attacks)QryUDP, QryTCP in NSStats
Query rejectionsACL misconfiguration or unauthorized accessAuthQryRej, RecQryRej in NSStats
CPU utilizationProcessing bottleneckProcess-level CPU for named
File descriptor usageFD exhaustion causing silent query drops/proc/$(pgrep -x named)/fd count vs limit
SOA serial consistencyZone transfer failure between primary and secondaryExternal SOA query comparison
DNSSEC validation failuresClock drift, expired trust anchors, upstream signing issuesValFail per-view resolver stat
Zone load healthZone failed to load after reload or restartBIND logs, rndc zonestatus

The most important transition from Level 1 to Level 2 is monitoring RecursClients as a percentage of the configured limit. The recursive-clients option (default 1000) is BIND’s circuit breaker. A soft quota is 90% for a configured limit of 1000 or less (900), or the limit minus 100 when larger; exceeding it causes BIND to abort its oldest query. At the hard limit, BIND also aborts its oldest query and the new recursive query fails with SERVFAIL. This is how a single slow upstream nameserver cascades into a local resolver outage: the count climbs from stressed to broken with no graceful degradation in between.

Express SERVFAIL rate as a ratio: QrySERVFAIL divided by the sum of classified responses (QrySuccess + QrySERVFAIL + QryNXDOMAIN + QryFORMERR + QryNxrrset + QryReferral). Normal is near 0%. Above 0.1% warrants investigation. Above 1% indicates a systemic problem. BIND caches SERVFAIL according to servfail-ttl (default 1 second, maximum 30 seconds), so a momentary upstream outage can briefly sustain SERVFAIL after recovery. Fixing upstream does not instantly fix the metric.

named starts successfully even if individual zones fail to load. Process liveness checks do not cover this. After every rndc reload, verify zone count via rndc status and scan logs for load failures.

File descriptor limits are OS-controlled. The BIND files option is deprecated in 9.18 and removed in 9.20. Default ulimit -n is often 1024, which is dangerously low for a busy resolver. BIND logs “too many open files” and silently drops queries when the limit is hit.

Level 3: mature

Level 3 answers: is BIND degrading, and are there invisible failures the previous levels missed? This is where leading indicators and kernel-level signals enter.

SignalWhat it catchesSource
Resolver RTT distributionUpstream nameserver latency increasingQryRTT10, QryRTT100, QryRTT500, QryRTT800, QryRTT1600, QryRTT1600+ per view
Resolver failure countersTimeouts, lame delegations, socket failuresQueryTimeout, Lame, Retry per-view resolver stats
NumFetchPer-view active outbound fetch pressureNumFetch per-view resolver stat
Response code breakdownGranular error pattern (NXDOMAIN spike, REFUSED shift)rcodes section: NOERROR, NXDOMAIN, SERVFAIL, REFUSED individually
UDP RcvbufErrorsKernel dropping packets before BIND sees them/proc/net/snmp Udp column
TCP connection countTCP accumulation causing FD pressuress -tan filtered to port 53
RRL activityRate limiting throttling legitimate traffic or blocking attackRateDropped, RateSlipped in NSStats
RPZ rewritesThreat interception spike (malware outbreak)RPZRewrites in NSStats
Update activityDynamic update failures or unauthorized attemptsUpdateDone, UpdateFail in NSStats
Socket statisticsSocket-level patterns for FD diagnosisSockStats counters
OpCode and QType distributionAmplification attacks (ANY), tunneling (TXT), reconnaissanceopcodes, qtypes sections
SOA expire countdownSecondary zone approaching expiry cliffrndc zonestatus <zone>
Cache eviction countersCache under memory pressure, undersizedDeleteLRU, DeleteTTL in cachestats
Control-plane responsivenessrndc degraded, incident response impairedrndc status execution timing

The most important addition at Level 3 is UdpRcvbufErrors from /proc/net/snmp. BIND’s statistics only count queries it successfully read from the socket. Packets dropped by the kernel due to receive buffer overflow produce no log entry, no counter, nothing in BIND’s own accounting. Teams typically discover this during an incident where “BIND is fine but queries are disappearing.” The metric is invisible to BIND and must be collected from the OS.

The second key addition is the SOA expire countdown. Serial mismatch tells you a transfer failed, but the real danger is how much time remains before the secondary stops serving the zone entirely. Once expired, the secondary returns SERVFAIL or REFUSED for that zone. rndc zonestatus <zone> shows the expire time directly. Alert when the runway drops below 50% of the SOA expire value. Escalate at 25% or 24 hours, whichever is shorter. This is a ticking bomb, not a self-healing condition.

Resolver RTT buckets measure outbound recursive query response times to upstream nameservers, not end-to-end client-perceived latency. BIND has no native inbound latency histogram. A shift toward higher RTT buckets indicates upstream degradation, which drives cache-miss latency and recursive client accumulation. These are per-view counters, so in split-horizon deployments, check each view separately.

Cache eviction counters (DeleteLRU, DeleteTTL) reveal whether the cache is at capacity and evicting entries before TTL expiry. Rapid DeleteLRU increase correlates with undersized max-cache-size and declining hit ratio.

Level 4: expert

Level 4 answers: is the resolver secure, correlated across system layers, and ahead of every known failure mode? These are the signals experienced operators add after major incidents.

SignalWhat it catchesSource
Per-thread CPU utilizationSingle-thread bottleneck while aggregate CPU looks moderatepidstat -t -p $(pgrep -x named)
rndc recursing samplingWhich upstream nameservers are causing recursive pile-uprndc recursing output analysis
Cache memory trackingCache consuming memory, approaching max-cache-sizeTreeMemInUse, HeapMemInUse, CacheNodes in cachestats
RRSIG expiryAuthoritative signatures approaching expiry (silent signing failure)dig <zone> RRSIG +dnssec +multiline, rndc signing -list <zone>
Query name entropyRandom subdomain attack (water torture)Query name distribution analysis from logs or sampling
NTP clock offsetClock drift causing DNSSEC validation failurestimedatectl status, chronyc tracking
Per-core CPU and IRQ/softirqIRQ imbalance causing packet processing bottleneckmpstat -P ALL 1 5
Source port entropyWeak randomization, cache poisoning vulnerabilitydig +short porttest.dns-oarc.net TXT @127.0.0.1
Statistics channel response timeBIND under severe internal pressureTime the statistics channel HTTP response
Zone file integrity checksumsUnauthorized zone modificationsChecksum comparison after each reload
DNSSEC signing freshnessInline signing silently failed (missing .signed.jnl)File presence check for .signed.jnl

Per-thread CPU matters because BIND 9.16+ uses one worker thread per CPU core by default (-n flag to override). Aggregate CPU can look moderate while a single thread is saturated, creating a bottleneck invisible in process-level metrics. Use pidstat -t or thread-level views to see per-thread distribution. Per-core CPU saturation and IRQ/softirq imbalance compound this: if network interrupts are not balanced across cores, one core handles all packet processing while others sit idle.

RRSIG expiry monitoring is essential for authoritative zones with inline signing. Auto-signing can silently fail when key files are missing, permissions are wrong, or disk is full. No log error is produced, no .signed.jnl file is created, and the zone continues being served with expiring signatures because the authoritative server does not validate its own signatures. Validating resolvers worldwide reject the zone when signatures expire, producing hours-long outages invisible from the authoritative operator’s perspective. The only reliable detection is checking actual RRSIG validity windows and .signed.jnl file presence.

NTP offset tracking matters because DNSSEC depends on accurate time. Even 5 minutes of clock drift can cause validation failures. Correlating NTP offset with ValFail counters catches this before it manifests as broad SERVFAIL for signed domains.

Source port entropy is the last line of defense against cache poisoning. BIND randomizes source ports for outbound recursive queries. NAT devices, firewalls, or misconfiguration can constrain this entropy. The porttest.dns-oarc.net probe reports the quality of randomization. Anything below “GREAT” warrants investigation.

rndc recursing sampling reveals which upstream nameservers are causing pile-up during recursive resolution cascades. During incidents, this distinguishes a single bad upstream from a broad network issue. It is invaluable during incidents but almost never collected proactively.

Cross-level failure patterns

Three composite failure patterns span multiple levels and require cross-level signal correlation to diagnose correctly:

  • Recursive resolution cascade: RecursClients climbing toward limit (Level 2) plus QueryTimeout increasing per view (Level 3) plus rndc recursing showing pile-up on specific upstreams (Level 4). CPU may remain moderate because threads are blocked waiting, not computing.
  • DNSSEC time bomb: ValFail spiking (Level 2) plus SERVFAIL for signed domains while unsigned domains work normally (Level 3) plus NTP offset drift (Level 4). The +cd flag in dig bypasses validation and confirms DNSSEC as the cause.
  • Zone staleness cascade: SOA serial mismatch between primary and secondary (Level 2) plus expire countdown shrinking (Level 3) plus DNSSEC signing freshness check for the zone (Level 4).

How Netdata helps

Netdata’s BIND collector ingests statistics channel data at per-second granularity, which matters for several reasons specific to this maturity model:

  • Rate computation is automatic. BIND’s counters are cumulative since process start. Netdata computes deltas and rates, so you see queries-per-second and SERVFAIL-per-second without manual sampling intervals.
  • Kernel metrics sit alongside BIND metrics. UdpRcvbufErrors from /proc/net/snmp appears on the same timeline as BIND’s query counters, making the Level 3 kernel-drop gap immediately visible without a separate dashboard.
  • Per-view breakdowns surface cache hit ratio, resolver failure counters (QueryTimeout, Lame), and RTT distributions in context, supporting split-horizon debugging.
  • Process-level metrics (RSS, FD count, per-thread CPU) are collected natively alongside the BIND collector, so Level 4 signals do not require separate tooling or manual correlation.