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 / zfs / zfs-resilver-slow-stuck ▌

Operations Guides

ZFS resilver slow or stalled: multi-day rebuilds and the second-failure race

A disk was replaced, zpool status shows resilver in progress, and the ETA says three days. Or worse: the scanned byte count has not moved in twenty minutes. Either way, the pool is running with reduced redundancy, and every hour the resilver takes is an hour where the next disk failure becomes a data-loss event.

Two facts frame everything below. First, ZFS deliberately throttles resilver I/O so production traffic wins. A slow resilver is often the system working as designed; the throttle-vs-risk trade-off is a decision you make, not an accident. Second, on large RAIDZ pools of spinning disks, a multi-day resilver is normal arithmetic, and a resilver that is decelerating frequently means a second device in the same vdev is also failing. That second case is the one that kills pools.

This article covers how to tell “slow by design” from “slow because something is wrong”, how to baseline the expected rebuild time, and what to do when the progress counter stops moving.

What this means

Resilver is ZFS reconstructing data onto a replaced or faulted device. The mechanics differ by topology, and the difference drives rebuild time:

  • Mirror vdevs resilver by copying the device, mostly sequential I/O, proportional to device size. OpenZFS 2.0 also offers sequential resilver (zpool replace -s), which works on mirrors and dRAID but not RAIDZ, and automatically runs a scrub afterward to verify checksums.
  • RAIDZ resilver walks the block pointer tree and reconstructs only allocated blocks. That is proportional to used space rather than device size, but the I/O pattern is driven by metadata layout and can be effectively random on a fragmented pool. This is why a 60%-full RAIDZ2 of 18 TB HDDs can still take days.

During the entire window, the pool is DEGRADED. On RAIDZ1, one more device failure in that vdev is total data loss. RAIDZ2 buys you one more failure, but the window is still the highest-risk state the pool will be in. The goal is not “make resilver fast at all costs”. It is “make the vulnerability window as short as possible without taking production down”.

A stall is a different event. ZFS operators define it roughly as zero bytes of progress for 10+ minutes. Slow is a trade-off; stalled is a bug, a hung device, or a dying second disk, and it needs active diagnosis.

Common causes

CauseWhat it looks likeFirst thing to check
Default resilver throttlingSteady but slow progress; production latency acceptableCompare scan rate in zpool status against device sequential capability
RAIDZ metadata-driven rebuildSlow resilver on RAIDZ even with healthy disks; mirror pools on the same hardware rebuild much fasterPool topology in zpool status
Second device in the vdev is failingResilver rate decelerating over hours; READ or CKSUM counters climbing on a surviving devicezpool status error columns, zpool iostat -v 1, SMART
Production I/O contentionResilver rate collapses during business hours, recovers at nightzpool iostat -q 1 queue depths, latency baseline
Stalled scan (0 progress 10+ min)Byte count and percentage frozen; no ETA movementTwo zpool status samples 10 minutes apart; zpool events for deadman events
Resilver restartingProgress repeatedly returns to 0% or a new resilver starts after one finisheszpool history for repeated scan starts

Quick checks

All of these are read-only and safe on a production pool.

# Overall pool and scan state
zpool status -x
zpool status | grep -A5 scan

# Take two progress samples to distinguish slow from stalled
zpool status | grep -A5 scan
sleep 600
zpool status | grep -A5 scan
# Per-vdev throughput: which device is limiting the rebuild
zpool iostat -v 1

# Per-vdev latency: is one surviving disk much slower than its peers
zpool iostat -l -v 1
# TODO: verify -l flag availability by OpenZFS version; latency columns were added in later 2.x releases

# Queue depths: saturation (pend >> activ) vs a hang
zpool iostat -q -v 1
# Error counters on every device; zero is the only acceptable value
zpool status -v

# Kernel-level device distress
dmesg | grep -i -E "ata|sas|reset|timeout" | tail -50

# Hung I/O detection (in-memory only; check ZED logs for history)
zpool events -v | grep -i deadman

# SMART on the surviving members of the degraded vdev
smartctl -A /dev/sdX
# Current resilver/scan controls (module parameters, live view)
cat /sys/module/zfs/parameters/zfs_resilver_min_time_ms
cat /sys/module/zfs/parameters/zfs_scan_vdev_limit
ls /sys/module/zfs/parameters/ | grep -i -E "resilver|scan"

How to diagnose it

The core question: is the rebuild progressing at the rate physics allows, slower than physics allows, or not progressing at all?

  1. Confirm the scan is running and note the numbers. zpool status shows bytes scanned, current rate, percentage, and ETA on the scan: line. Write down the scanned-bytes value. Treat the ETA with suspicion: it is computed from the average rate since start, so it is routinely inaccurate, especially early.

  2. Baseline the expected time. Estimate from used capacity and realistic device throughput, not from the ETA. For RAIDZ, the driver is used space: a pool with 40 TB allocated, rebuilt through surviving HDDs that can each sustain roughly 150-200 MB/s sequential under shared load, lands in the tens-of-hours range before you subtract the throttle and production contention. For mirrors, the driver is full device size but the I/O is sequential. If your observed rate is within a plausible factor of that estimate, you are looking at a long-but-normal rebuild. If it is 10x off, keep digging.

  3. Distinguish slow from stalled. Take two zpool status samples 10 minutes apart. If the scanned-bytes counter has not moved, that is a stall. If it moved, compute the effective rate yourself ((bytes2 - bytes1) / 600) and compare against step 2.

  4. Check for a second failing device. This is the highest-stakes branch. In zpool status, look at the READ, WRITE, and CKSUM columns on the surviving members of the degraded vdev. Any non-zero value, especially one that increments between samples, is a dying disk. Cross-check with zpool iostat -v 1 (one device markedly slower than its peers) and smartctl -A on that device. A decelerating resilver plus climbing error counters means you are losing the second-failure race in real time.

  5. Separate throttling from hardware. During a quiet window, watch zpool iostat -q -v 1. If pending queues on the data vdevs are near-empty while the resilver rate stays low, the scan engine is yielding to (nonexistent) production I/O and the throttle is the limiter. If pending queues are deep and latency is up, the backend is saturated and the resilver is competing for real bandwidth.

  6. If stalled, look for hung I/O. Check zpool events -v | grep -i deadman. Deadman events mean an individual I/O has been stuck for minutes, which points at a device, cable, or controller problem rather than ZFS scheduling. Correlate with dmesg for link resets or timeouts. Sequential scans checkpoint progress (by default every two hours) so a reboot resumes from the last checkpoint rather than always from zero. A replacement that starts while resilver progress is below zfs_resilver_defer_percent (default 10%) can restart from scratch; check zpool history for repeated scan starts.

flowchart TD
  A[Resilver running] --> B{Progress moving over 10 min?}
  B -- No --> C[Stalled scan]
  C --> D[Check deadman events and dmesg]
  D --> E[Device, cable, or controller fault]
  B -- Yes --> F{Rate near physics estimate?}
  F -- Yes --> G[Normal long rebuild: monitor and wait]
  F -- No, slower --> H{Error counters climbing on survivors?}
  H -- Yes --> I[Second device failing: escalate now]
  H -- No --> J{Queues deep, latency high?}
  J -- Yes --> K[Production contention or saturated backend]
  J -- No --> L[Throttle-limited: consider tuning trade-off]

Metrics and signals to monitor

SignalWhy it mattersWarning sign
Resilver rate and scanned bytes (zpool status scan line)Defines the length of the reduced-redundancy windowZero progress for 10+ minutes; rate decelerating over hours
Per-vdev READ/WRITE/CKSUM countersThe early warning for the second failureAny non-zero value; any increment during the resilver
Per-vdev latency (zpool iostat -l -v)A surviving disk going slow before it diesOne device consistently several times slower than peers
Queue depth (zpool iostat -q -v)Separates backend saturation from a hangSustained pend » activ on data vdevs
Pool state and per-vdev stateDEGRADED is expected; any additional state transition is an emergencyA second device going UNAVAIL or FAULTED mid-resilver
Deadman events (zpool events, via ZED for persistence)Detects hung I/O behind a stalled scanAny deadman event
Application-facing latencyThe cost side of the throttle trade-offSustained latency far above baseline during the rebuild

Fixes

If the rebuild is normal but long

Do less. The default throttling exists to keep production latency acceptable, and on large HDD RAIDZ pools a multi-day rebuild is expected behavior. Reduce discretionary load (backups, scrubs on other pools sharing the enclosure, bulk jobs), keep watching the error counters on survivors, and let it finish. Resilver and scrub are mutually exclusive per pool, and a resilver preempts a running scrub, so do not expect scrub results while this is ongoing.

If the throttle is the limiter and you accept the trade-off

You can raise resilver priority with current scan controls such as zfs_resilver_min_time_ms (default 1500 ms) and zfs_scan_vdev_limit (default 16 MiB per leaf device) under /sys/module/zfs/parameters/. This is a live, reversible change, but understand what you are buying: every extra I/O the scan issues is an I/O production traffic does not get, and latency will rise. Change one parameter at a time, measure the effect on both the scan rate and application latency, and record the original values so you can revert. A reasonable policy is to raise resilver priority during off-peak hours and restore defaults during peak.

If production is suffering and you need relief now

On supported versions, zpool scrub -p <pool> pauses an active scan, including a resilver. This is the correct lever when the alternative is an application incident, but be explicit about the cost: pausing extends the reduced-redundancy window. Pause during the peak, resume immediately after.

If a second device is failing

The resilver is no longer the event; the second disk is.

  • Stop all non-essential write load to reduce stress on the degraded vdev.
  • Pull SMART data on the suspect device and prepare its replacement immediately.
  • If the suspect device is erroring hard, offlining it may reduce error-storm contention, but only if the remaining redundancy still covers the vdev. On RAIDZ1 already down one disk, offlining a second device takes the pool to FAULTED. Know your topology before you touch anything.
  • If errors are appearing on multiple unrelated devices simultaneously, suspect RAM or the controller rather than the disks and follow the multi-device checksum failure path instead.

If the scan is stalled with no progress

Work the hardware path, not the ZFS path: deadman events, dmesg link resets, per-device latency, cabling and controller health. A resilver frozen at zero bytes is almost always a device that is physically present but not servicing I/O. Resolve the underlying fault, then confirm the scan resumes. Avoid repeated reboots as a diagnostic: they do not fix hung devices and they cost you whatever progress was not yet durable.

For mirror pools: use sequential resilver next time

On supported OpenZFS versions, zpool replace -s performs a sequential resilver in a mirror vdev that is substantially faster than the default healing resilver, followed by an automatic scrub to verify integrity. It is not available for RAIDZ. For RAIDZ pools, the levers are topology planning and capacity headroom, covered below.

Prevention

  • Baseline before you need it. Record actual resilver times per pool after every replacement, alongside used capacity. A stored baseline turns “is this slow?” into a comparison instead of a guess.
  • Treat DEGRADED as a same-day ticket. The pool stays online after a disk failure, which makes it easy to defer. Every day deferred is a day in the single-failure-away state. Replacements and spares should be stocked before the failure, not ordered after.
  • Prefer RAIDZ2 or RAIDZ3 for large spinning disks. The larger the disks, the longer the rebuild, and the more a single parity device is worth. RAIDZ1 on multi-TB HDDs is where multi-day resilvers and single-failure tolerance combine into the worst risk profile.
  • Scrub on schedule and alert on results. Scrubs surface slowly dying disks (rising repaired-error counts) weeks before they fail outright, which lets you replace proactively instead of resilvering under pressure.
  • Configure hot spares and autoreplace where appropriate, and verify ZED is alerting on pool events so DEGRADED and deadman events page someone rather than sitting in zpool status.
  • Monitor fragmentation and capacity. A heavily fragmented, near-full pool resilvers slower and scrubs slower. Both trends are visible long before a disk fails.

How Netdata helps

  • Resilver progress as a time series: Netdata tracks pool scan state continuously, so you can see the rebuild rate trend and spot deceleration or a flatline instead of relying on point-in-time zpool status checks.
  • Per-vdev error counters alongside the rebuild: READ, WRITE, and CKSUM counts per device are charted next to scan progress, which is exactly the correlation that exposes a second failing disk mid-resilver.
  • Per-vdev latency and queue depth: correlating device latency with scan rate separates “throttled by design” from “backend saturated” from “one disk dying” without manual iostat sessions.
  • Pool state transitions and ZED events: DEGRADED, additional vdev failures, and deadman events become alerts with history, not lines you had to be watching to catch.
  • Latency impact of the throttle trade-off: application-visible storage latency during the rebuild lets you tune resilver priority against a measured cost instead of guessing.