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 / lvm / lvm-raid-mismatch-count ▌

Operations Guides

LVM RAID mismatch count: data integrity after a scrub

A non-zero raid_mismatch_count means the scrub found blocks where data on one leg disagrees with data on the other leg(s). This surfaces as the m flag in position 9 of lv_attr and in the raid_mismatch_count field of lvs. It demands investigation, though some mismatches turn out to be benign.

The operational question is not “do we have mismatches” but “is this real corruption or expected noise.” RAID1 and RAID10 arrays can report non-zero mismatch counts from documented edge cases in the kernel write path that produce alignment differences in transient data areas. Mismatches appearing after an unclean shutdown are expected until the scrub completes and should not trigger paging on initial boot.

This article covers how to interpret a non-zero mismatch count, how to distinguish benign from real corruption, and how to safely repair without making things worse.

What this means

When you run lvchange --syncaction check on a RAID LV, the kernel reads every block from every leg and compares them. Any block where the legs disagree increments the mismatch counter. The check action is read-only: it detects and reports but does not modify data.

After the scrub completes, raid_mismatch_count holds the total number of mismatched blocks found. The m character in position 9 of lv_attr (for example, Rwi-a-r-m-) indicates mismatches exist. The count persists until a subsequent scrub runs to completion with zero discrepancies.

A non-zero count means one of three things:

  1. Real data corruption. One or more blocks on a leg are genuinely wrong, typically from media degradation or a firmware bug.
  2. Benign alignment differences. RAID1 and RAID10 can produce these in transient data areas due to write-path edge cases. They do not represent corruption, but the counter cannot distinguish them from real problems.
  3. Transient post-crash state. After an unclean shutdown, dirty regions may show mismatches until the scrub reconciles them.

You cannot distinguish these three cases from the mismatch count alone. The count is a number, not a verdict. Correlating it with SMART data, kernel logs, and the trend across multiple scrubs is what separates a non-event from an incident.

Common causes

CauseWhat it looks likeFirst thing to check
Benign RAID1/RAID10 alignmentSmall, stable mismatch count on a healthy array with no dmesg errors and no degraded legsRe-run the scrub; if the count is stable or drops, likely benign
Post-crash dirty regionsm flag appears immediately after unclean shutdown, before scrub completesWait for the post-boot scrub to finish, then re-check
Real media corruptionMismatch count grows over repeated scrubs, dmesg shows medium errors on a PVCheck SMART data and dmesg for the affected device
dm-integrity counter stuckMismatches on LVs with --raidintegrity y, count never resets after checkCheck lvm2 version for the fix (LVM2 2.03.41, May 2026)
Unallocated space mismatchesCount is non-zero but the filesystem on the LV reports no errorsWrite to all free space to force synchronization, then re-scrub

Quick checks

# Check health status of all RAID LVs — position 9 of lv_attr
lvs -o lv_name,vg_name,lv_attr,raid_mismatch_count,raid_sync_action

# Filter for unhealthy LVs only
lvs -o lv_name,vg_name,lv_attr | awk 'substr($3,9,1) != "-" && NR>1'

# Detailed RAID health per device from device-mapper (no LVM lock needed)
dmsetup status <vg>-<lv>
# Health chars: A = alive and in-sync, a = alive but not in-sync, D = dead/failed

# Monitor an in-progress scrub
lvs -a -o name,raid_sync_action,sync_percent,copy_percent

# Verify no PVs are missing or degraded
pvs -o pv_name,vg_name,pv_attr,pv_size,pv_free
# Missing PVs may not appear in pvs output at all; check vgs for partial flag
# Missing PVs appear as "[unknown]" in pvs output on modern lvm2; older releases may omit the row entirely

# Check for kernel I/O errors on underlying devices
dmesg | grep -i 'error\|medium\|fail' | tail -50

# Check VG metadata consistency
vgck -v <vgname>

How to diagnose it

  1. Confirm the scrub has completed. A mismatch count is only meaningful after raid_sync_action shows the check is done and sync_percent is 100. If the scrub is still running, wait. Mismatches during an in-progress scrub are not final.

  2. Rule out the post-crash transient. If the system recently rebooted after an unclean shutdown, the m flag may appear until the post-boot scrub reconciles dirty regions. Wait for the scrub to complete, then re-check the count.

  3. Check whether any legs are degraded. Use dmsetup status <vg>-<lv> and look at the health characters. If any device shows D (dead), the array is degraded and you have a bigger problem than the mismatch count. Address the dead leg first. See LVM RAID or mirror degraded.

  4. Determine the RAID level. RAID1 and RAID10 can produce benign mismatches from write-path edge cases. These exist in transient data areas and do not represent corruption, but the counter cannot distinguish them from real problems.

  5. Run a second scrub and compare counts. After the first scrub reports a mismatch count, run lvchange --syncaction check again. If the count drops or disappears, it was likely transient or benign. If the count is identical, it could be persistent corruption or a stable benign alignment difference. If the count grows, investigate hardware immediately.

  6. Check for unallocated space mismatches. Mismatches can reside in unallocated space on the filesystem. The RAID layer tracks all blocks, including ones the filesystem has never written to. Writing to all free space can force synchronization and reduce the count. This is a known cause of confusing-but-benign mismatch reports.

  7. Check SMART and dmesg for hardware errors. If you suspect real corruption, correlate the mismatch with SMART error logs and kernel I/O error messages for the underlying physical devices. Medium errors, read retries, and reallocated sectors all point to media degradation.

  8. Check whether dm-integrity is enabled. If the LV was created with --raidintegrity y, there was a known bug where syncaction check would detect mismatches but the counter would never reset to zero, and syncaction repair was refused with the message “Use syncaction check to detect and correct integrity checksum mismatches.” This was fixed in LVM2 2.03.41 (May 2026), which allows syncaction check and syncaction repair directly on integrity-enabled LVs. Most distribution lvm2 packages still predate 2.03.41, so check your package version before assuming the fix is present.

flowchart TD
    A["raid_mismatch_count > 0"] --> B{"Scrub completed?"}
    B -- No --> C["Wait for completion
Do not alert yet"] B -- Yes --> D{"Recent unclean
shutdown?"} D -- Yes --> E["Wait for post-boot scrub
Re-check count"] D -- No --> F{"Any leg shows D
in dmsetup status?"} F -- Yes --> G["Address dead leg first
Higher priority than mismatches"] F -- No --> H{"RAID1 or RAID10?"} H -- Yes --> I["May be benign
Re-scrub and compare"] H -- No --> J["More likely real
Check SMART and dmesg"] I --> K{"Count stable or
dropping?"} K -- Yes --> L["Likely benign
Monitor trend"] K -- No --> M["Investigate hardware
Consider repair"] J --> M

Metrics and signals to monitor

SignalWhy it mattersWarning sign
raid_mismatch_countDirect indicator of data divergence between legsAny non-zero value after a completed scrub
lv_attr position 9 (m)Health flag that surfaces mismatches without querying the countm appears where - was previously
raid_sync_actionTells you whether a scrub is in progress and what typeStuck in check or repair for hours with no progress
copy_percentRebuild or resync progress for the arrayStuck at the same value for over an hour
dmsetup status health charsPer-device RAID health (A/a/D)Any D means a dead leg, which takes priority over mismatch investigation
PV accessibilityMissing PV means degraded array, not just mismatchesPV absent from pvs output, VG showing partial flag in vgs
Kernel I/O errors in dmesgHardware-level signal of media degradationmedium error, I/O error, or read retries on PV devices
SMART error logsPhysical disk health independent of the LVM layerReallocated sectors, pending sectors, UDMA CRC errors

Fixes

Run a check scrub

# Read-only detection — does not modify data
lvchange --syncaction check <vg>/<lv>

This is always the first step. It populates raid_mismatch_count without writing anything. Monitor progress with lvs -a -o name,raid_sync_action,sync_percent. Do not act on a count until the scrub completes. This action is safe to run during production operation, though it generates additional read I/O.

Run a repair scrub

# WARNING: repair makes data consistent but may pick the wrong copy.
# It cannot determine which leg has the correct data.
lvchange --syncaction repair <vg>/<lv>

The repair action detects mismatches and writes corrected blocks to make the legs consistent. The critical limitation: repair does not know which copy is correct. The man page explicitly warns that repair may result in consistent but incorrect data. If you have application-level checksums or filesystem integrity verification, run them after repair.

For RAID1 where you know one PV is failing or corrupt, prefer lvchange --rebuild <PV> <vg>/<lv> over repair. The --rebuild flag rebuilds from the known-good leg to the specified device, which is safer when you have high confidence about which leg holds the correct data.

The dm-integrity workaround (older lvm2)

If your LV uses --raidintegrity y and you are running lvm2 from before the May 2026 fix, syncaction repair may be refused. The workaround is to temporarily disable integrity:

# WARNING: temporarily removes the integrity layer.
# This is disruptive and bypasses integrity checking until re-enabled.
lvconvert --raidintegrity n <vg>/<lv>
lvchange --syncaction repair <vg>/<lv>
lvconvert --raidintegrity y <vg>/<lv>

LVM2 2.03.41 and later allow syncaction check and syncaction repair directly on integrity-enabled LVs without this workaround; verify your lvm2 package version, since most distro releases predate it.

Force synchronization of unallocated space

If mismatches persist primarily in unallocated space and you have confirmed the filesystem itself is healthy:

# WARNING: this fills the filesystem completely until ENOSPC.
# Applications writing to the same filesystem will fail while this runs.
# Run only during a maintenance window or on a quiesced filesystem.
dd if=/dev/zero of=/mountpoint/fillfile bs=1M status=progress
rm /mountpoint/fillfile
lvchange --syncaction check <vg>/<lv>

This writes zeros to all free space, forcing the RAID layer to synchronize blocks that were never written. Schedule it during a maintenance window. After the fill file is removed, re-scrub to verify the mismatch count has dropped.

Prevention

  • Schedule regular scrubs. Run lvchange --syncaction check on RAID LVs periodically (weekly or monthly depending on data criticality). Regular scrubs catch corruption early and keep the mismatch count meaningful as a trend signal rather than a one-time surprise.

  • Do not page on post-boot mismatches. After an unclean shutdown, mismatches may appear transiently until the scrub completes. Gate alerts on system uptime greater than 600 seconds and require the scrub to have completed before alerting.

  • Verify your lvm2 version if using dm-integrity. The fix in LVM2 2.03.41 (May 2026) changes how syncaction check and syncaction repair interact with integrity-enabled LVs. Older versions have a known bug where the mismatch counter never resets and repair is refused.

  • Track mismatch count trends, not just current values. A stable count of 12 that has been the same for months is different from a count that went from 0 to 12 in the last scrub. Historical data tells you whether the situation is changing, which is the single most useful signal for distinguishing benign from active corruption.

  • Correlate with SMART data. Media errors are the most common cause of real (non-benign) mismatches. Proactive SMART monitoring catches degrading disks before they produce RAID-level corruption.

  • Document which LVs are RAID1/RAID10. These levels can produce benign mismatches. Having this context in your runbook prevents unnecessary escalation when a stable non-zero count appears on a known-healthy RAID1 volume.

How Netdata helps

  • Per-second collection on raid_mismatch_count and lv_attr health flags catches the transition from - to m immediately, rather than waiting for the next cron-based lvs poll that may be tens of seconds behind.
  • ML-based anomaly detection on mismatch count trends distinguishes a stable, known-benign count from a sudden jump that indicates active corruption, reducing false escalations on RAID1 volumes with expected alignment differences.
  • Correlation with disk I/O latency and error rates from /proc/diskstats and SMART data connects RAID-level mismatches to the specific underlying physical device that is degrading.
  • Kernel log collection surfaces dmesg I/O errors, medium errors, and device reset messages alongside the mismatch flag, providing the corroboration needed to separate real corruption from benign alignment differences.
  • Historical trending of mismatch counts across scrub cycles shows whether the count is stable, growing, or shrinking over time, which is the single most useful signal for distinguishing benign from active corruption.