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 / smartctl-disk-monitoring / smartctl-ssd-write-cliff ▌

Operations Guides

The SSD write cliff: latency spikes when the pre-erased block pool empties

Write latency on an SSD jumps from sub-millisecond to hundreds of milliseconds or seconds. Applications time out. The kernel log may show command timeouts. But smartctl -H says PASSED, every SMART attribute looks clean, and the drive has plenty of endurance left.

The write cliff happens when an SSD exhausts its pool of pre-erased NAND blocks. Under normal conditions, the controller performs garbage collection (GC) in the background: it reads valid pages from partially invalidated blocks, writes them elsewhere, and erases the now-empty block to replenish the free pool. When the write rate outpaces background GC, the free pool empties. Every host write now requires a synchronous erase cycle before it can complete, and latency explodes by 100x to 1000x.

The drive is healthy and will recover once GC catches up. The operational challenge is distinguishing the write cliff from real drive problems (pending sectors, endurance exhaustion, thermal throttling) and from a related pattern on SMR HDDs that produces identical symptoms.

What this means

NAND flash cannot overwrite data in place. A page must be erased before it can be written again, and erase operations work at the block level, where a block contains many pages. The SSD controller hides this behind a flash translation layer (FTL) that maintains a pool of pre-erased blocks for fast host writes and reclaims invalidated pages through background GC. Write amplification (the ratio of NAND writes to host writes, always at least 1, often 2-10x) is the cost of this abstraction.

The write cliff is the moment the pipeline breaks down. Background GC cannot reclaim blocks fast enough to keep the pre-erased pool stocked, so the controller enters foreground GC. Host write commands queue behind synchronous erase cycles. The drive returns no errors. It simply takes orders of magnitude longer to acknowledge writes.

flowchart TD
    A["Normal: background GC replenishes free blocks"] -->|"sustained write pressure"| B["Free block pool depleting"]
    B -->|"pool exhausted"| C["Foreground GC: synchronous erase before write"]
    C --> D["Write latency spikes 100-1000x"]
    D --> E["Application timeouts, command stalls"]
    C -->|"write pressure drops"| F["GC catches up, pool refills"]
    E -->|"write pressure drops"| F
    F --> A

The write cliff is transient. Reduce the write rate or give the drive idle time, and performance recovers. This distinguishes it from endurance exhaustion, where Percentage Used is at or above 100% and the physical NAND is worn out permanently.

Common causes

CauseWhat it looks likeFirst thing to check
Sustained writes without TRIMLatency spikes under write load, improves when idle. Write amplification is high because the controller cannot distinguish stale from valid pages.Run fstrim -v /mountpoint and check if latency improves
SSD nearly full (above 80%)Progressive write degradation that worsens as the drive fills. Less free space means less room for GC to work efficiently.df -h on the mounted filesystem
TRIM stripped by RAID controllerWrite latency grows over time and never recovers on its own. Common behind LSI/Broadcom MegaRAID and similar controllers.Check RAID controller documentation for TRIM passthrough support
High write amplification from random small writesPercentage Used climbs faster than expected from host write volume. Latency spikes are intermittent.Compare Data Units Written trend against application write volume
SMR HDD with CMR cache exhaustedWrite speed collapses to single-digit MB/s on what appears to be an SSD-style write cliff, but the device is a hard drive.Check drive model against manufacturer SMR/CMR datasheet
Firmware GC bugCumulative latency growth over weeks or months, even on low-write workloads. Not transient.Check firmware version against vendor advisories

Quick checks

Run these commands to narrow the diagnosis. All are read-only except fstrim, which issues discard commands to the drive but does not modify user data.

# Check overall SMART health - should still say PASSED during a write cliff
smartctl -H /dev/sdX

# Check endurance metrics (NVMe)
smartctl -A /dev/nvme0n1 | grep -E "Percentage Used|Available Spare|Data Units Written"

# Check for command timeouts (ATA attribute ID 188, not universally implemented)
smartctl -A /dev/sdX | grep -i "Command_Timeout"

# Check write latency in real time (look at w_await and %util)
iostat -x 1

# Verify TRIM is supported and functional
lsblk -D
fstrim -v /mountpoint

# Check kernel logs for I/O timeouts or error recovery
dmesg | grep -iE "timeout|I/O error|reset" | tail -20

# Check SSD capacity utilization
df -h /mountpoint

# Check for media errors that would indicate real degradation, not GC
smartctl -A /dev/nvme0n1 | grep "Media and Data Integrity Errors"

# Check temperature (thermal throttling produces similar latency symptoms)
smartctl -A /dev/nvme0n1 | grep -i "Temperature"

How to diagnose it

  1. Confirm the latency pattern. Use iostat -x 1 and look at w_await (write latency) and %util. The write cliff produces high write latency while read latency may remain normal. If read latency is also spiking, check Current Pending Sector count (ID 197) and Offline Uncorrectable (ID 198) instead. See the related guide on Current_Pending_Sector non-zero.

  2. Verify SMART is clean. Run smartctl -A /dev/sdX (or /dev/nvme0n1). The write cliff should show clean media integrity: zero reallocated sectors, zero pending sectors, zero uncorrectable errors, zero media and data integrity errors (NVMe). If these are non-zero, you are looking at actual media degradation, not a write cliff.

  3. Check endurance to rule out wear-out. On NVMe, confirm Percentage Used is below 100% and Available Spare is above threshold. If Percentage Used is at or above 100%, the problem is endurance exhaustion, not the write cliff. See NVMe Percentage Used at or above 100%.

  4. Verify TRIM is working. Run fstrim -v /mountpoint. If it returns successfully and reports bytes trimmed, TRIM is functional. If it fails or reports zero bytes, the SSD is not receiving deallocation hints and GC efficiency is severely degraded. Behind RAID controllers, TRIM may be silently dropped.

  5. Check drive fullness. If the filesystem is above 80% capacity, the SSD has less working room for garbage collection. This is the single most common amplifier of the write cliff in production.

  6. Check for SMR if this is an HDD. SMR drives exhibit a similar performance collapse when their CMR cache fills. There is no universal SMART attribute to distinguish SMR from CMR. Do not rely on an exact hdparm -I string: some SMR drives expose zone/streaming capability fields, but device-managed SMR often does not self-identify. Check the model against the manufacturer’s SMR/CMR list or zoned-block-device documentation.

  7. Correlate latency with write rate. The write cliff is load-dependent. If latency spikes correlate with sustained write bursts and recover during idle periods, this confirms the diagnosis. If latency is high regardless of load, suspect a different problem.

Metrics and signals to monitor

SignalWhy it mattersWarning sign
Write latency (w_await in iostat)Direct measure of the symptom. The write cliff produces write-specific latency spikes.w_await jumping from sub-millisecond to tens or hundreds of milliseconds
NVMe Percentage UsedDistinguishes write cliff from endurance exhaustion. Write cliff occurs at any wear level.Above 100% means rated endurance is consumed; evaluate spare and media errors
NVMe Available SpareDistinguishes write cliff from spare pool exhaustion.Below the vendor-specific threshold means spare-pool pressure, not ordinary GC
Data Units Written / Total LBAs WrittenSustained high write rate is the root cause. Track the rate of change.Write rate trending upward without corresponding workload change
Command Timeout (ID 188)Some drives expose this. Foreground GC stalls produce timeouts.Non-zero or increasing
Drive temperatureThermal throttling produces similar latency symptoms but is caused by heat, not GC.Temperature above WCTEMP (NVMe) or above 60C (HDD)
Media and Data Integrity Errors (NVMe)Rules out actual NAND failure.Any non-zero value indicates real media problems, not write cliff
Filesystem utilizationAbove 80% full amplifies the write cliff.Approaching or above 80% used

Fixes

Restore TRIM

The most common cause of chronic write cliff behavior is TRIM not reaching the drive. Without TRIM, the controller cannot distinguish pages that the filesystem has freed from pages that still hold valid data. Every garbage collection cycle must treat stale pages as valid, copying them unnecessarily and inflating write amplification.

Run fstrim -v /mountpoint to issue a one-time TRIM. Then verify that periodic TRIM is scheduled (typically via a systemd timer or cron job). Behind RAID controllers, check whether TRIM passthrough is supported and enabled. Some LSI/Broadcom MegaRAID firmware versions support TRIM passthrough but require explicit configuration.

Reduce drive fullness

Keep SSDs below 80% capacity. As the drive fills, the controller has fewer free blocks to work with, and GC efficiency drops sharply. If the filesystem is above 80%, freeing space or moving data to other volumes is the fastest path to recovery. Increasing over-provisioning (leaving unpartitioned space at the end of the drive) gives the controller more working room without affecting the filesystem.

Throttle the write workload

If the write rate is genuinely exceeding what the SSD can sustain, the long-term fix is to reduce write volume. Options include moving write-heavy workloads (database WAL, log ingestion, swap) to drives with higher sustained write ratings or more over-provisioning, tuning the application’s write batching behavior, or adding SSDs to spread the write load.

Let the drive recover

If the SSD has already hit the write cliff, reducing the write rate and leaving the drive powered on and idle allows background GC to catch up. There is no universal vendor idle-recovery interval: recovery depends on capacity, over-provisioning, fragmentation, and the preceding write burst. Monitor latency and write-completion behavior rather than waiting a fixed interval. This is not a permanent fix. If the write rate that triggered the cliff resumes, the cliff will recur.

Address firmware bugs

Some SSD firmware versions have garbage-collection defects that cause cumulative latency growth independent of write pressure. This article does not maintain a model/firmware list; check the affected drive’s vendor firmware advisories. Firmware update procedures vary; some require a power cycle or briefly take the device offline. Plan accordingly.

Handle SMR drives

If the affected device is an SMR HDD, the write performance collapse is expected behavior once the CMR cache fills. There is no fix at the drive level. The operational response is to either avoid sustained write workloads (SMR drives are fine for archival reads) or replace the drive with a CMR model. SMR drives in ZFS resilver or RAID rebuild scenarios can turn an hours-long operation into one measured in days.

Prevention

  • Keep SSDs below 80% full. More free space means more working room for background GC.
  • Ensure TRIM reaches the drive. Verify TRIM works behind RAID controllers. Schedule periodic fstrim if the filesystem does not issue continuous discard.
  • Monitor write rate against rated endurance. Track Data Units Written or Total LBAs Written over time. A sudden increase in write rate without a corresponding workload change indicates a problem (misconfigured application, runaway logging).
  • Select the right drive for the workload. Enterprise SSDs with higher over-provisioning sustain higher write rates before hitting the cliff. Consumer SSDs in write-heavy enterprise workloads are a common mismatch.
  • Avoid SMR drives for write-intensive workloads. Check the datasheet before deployment. SMR drives are appropriate for sequential write-once, read-many workloads, not for databases, logs, or RAID/ZFS pools that require sustained random write performance.
  • Track firmware versions fleet-wide. Known GC bugs affect specific firmware versions. Monitoring firmware version lets you proactively identify and patch affected drives before latency starts growing.

How Netdata helps

  • Per-second disk latency metrics let you pinpoint the exact moment write latency spikes and correlate it with write throughput. The write cliff produces a distinctive pattern: write latency spikes while read latency stays flat, and the spike resolves when the write rate drops.
  • SMART attribute collection feeds Percentage Used, Available Spare, Data Units Written, and Media Errors into the same dashboard as disk latency. This makes it straightforward to distinguish the write cliff (clean SMART, high latency) from endurance exhaustion (Percentage Used above 100%) or media degradation (rising reallocated or pending sectors).
  • Temperature correlation helps separate thermal throttling from the write cliff. Both produce latency spikes, but only thermal throttling correlates with temperature approaching the vendor threshold.
  • Anomaly detection on write latency and write throughput can surface the write cliff before it triggers application timeouts. A sudden latency spike that deviates from the established baseline pattern is the earliest signal.
  • Historical correlation across the write cliff episode and recovery shows whether the condition is transient (GC catching up) or recurring (chronic workload mismatch), which drives the decision between a tactical fix (TRIM, free space) and a strategic fix (drive replacement, workload redistribution).