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 / docker / docker-log-rotation

Operations Guides

Docker log rotation: preventing json-file logs from filling disk

Docker’s default json-file log driver appends every line of container stdout and stderr to a JSON file on the host under /var/lib/docker/containers/<id>/. Without size limits, that file grows monotonically. A single verbose container can consume tens of gigabytes, and because the driver is the default, this often happens silently until /var/lib/docker fills. At that point image pulls fail, container creates are rejected, and the daemon may hang on storage operations. This guide covers how to cap log files with daemon.json and per-container log-opt overrides, verify the caps are working, and choose a different driver when json-file is not appropriate.

What This Means

In production, json-file is convenient because docker logs works out of the box and the output is machine-readable JSON. The tradeoff is that the daemon keeps every log line on disk unless you tell it otherwise. The logs are stored in the container directory, but docker system df reports the writable layer, not json-file logs, so it can understate their disk cost. Exited containers also retain their logs until the container is removed. When disk exhaustion hits, the failure mode is a cascade: writes slow, daemon latency spikes, image pulls and container creates fail, and in extreme cases dockerd becomes unresponsive while containers continue running. Rotation is not a performance tweak. It is an availability requirement for any node using json-file.

Common Causes

CauseWhat it looks likeFirst thing to check
No log-opts in daemon.jsonContainer log files grow without bound across the hostcat /etc/docker/daemon.json and docker info | grep -i "logging driver"
Per-container override without limitsOne container’s directory is far larger than the restdocker inspect --format '{{json .HostConfig.LogConfig}}' <id>
High-volume application loggingDisk growth tracks traffic spikes or batch jobsdocker logs --tail 100 <id>
Exited containers not prunedDisk usage climbs while the running container count stays flatdocker ps -a --filter status=exited
json-file used for centralised aggregationLogs are written to disk and then read by a node agent, doubling I/Odocker info | grep -i "logging driver"

Quick Checks

# Check the active default logging driver
docker info | grep -i "logging driver"

# Inspect daemon configuration for log options
cat /etc/docker/daemon.json

# Check a container's specific log configuration
docker inspect --format '{{json .HostConfig.LogConfig}}' <container_id>

# See container directory sizes, which include json-file logs and container metadata
du -sh /var/lib/docker/containers/*/ 2>/dev/null | sort -rh | head -10

# List stopped containers that still retain logs and layers
docker ps -a --filter status=exited --format '{{.ID}} {{.Names}}'

# Check Docker-wide disk usage and reclaimable space
docker system df -v

If daemon.json is missing or has no log-opts block, the host has no default rotation. If a container’s LogConfig shows no max-size, that container is unprotected regardless of the daemon default.

How To Diagnose It

  1. Confirm the driver and locate the largest consumers. Run docker info | grep -i "logging driver" and du -sh /var/lib/docker/containers/*/. If the driver is json-file and individual container directories are hundreds of megabytes or larger, logs are the likely culprit. This tells you whether the fix is rotation or a driver migration. Next, inspect the daemon configuration.

  2. Inspect daemon.json for log-opts. Look for a log-opts key containing max-size and max-file. Why: the daemon default applies to every container created after the daemon reads the policy. Result: if these keys are missing, nothing limits log growth. Next: add the policy and plan a daemon restart.

  3. Inspect existing containers for overrides. Run docker inspect --format '{{json .HostConfig.LogConfig}}' on large containers. Why: per-container --log-opt flags override the daemon default. Result: if a container specifies its own driver or omits max-size, it will grow without the daemon safeguard. Next: recreate the container with explicit limits.

  4. Verify container creation time relative to policy changes. Check when the container was created versus when daemon.json was last modified and the daemon restarted. Why: Docker applies logging configuration at container creation time; changes are not retroactive. Result: containers started before the policy change continue under the old rules. Next: recreate stale containers after the daemon restart.

  5. Audit exited containers. Run docker ps -a --filter status=exited. Why: stopped containers retain log files until removed. Result: a large population of exited containers can explain disk pressure even when running containers look fine. Next: prune exited containers after confirming you do not need their logs.

  6. Check application log velocity. Run docker logs --tail 100 <container_id>. Why: if an application emits megabytes per minute, a small max-size may rotate too frequently, while a large one may still exhaust disk if max-file is high. Result: you may need to reduce application verbosity or switch to a streaming driver such as fluentd or syslog.

flowchart TD
    A[Check json-file log sizes] --> B{Rotation configured in daemon.json?}
    B -->|No| C[Add max-size and max-file to daemon.json]
    B -->|Yes| D{Container created after config?}
    D -->|No| E[Recreate container to pick up policy]
    D -->|Yes| F[Verify log file count and sizes]
    F -->|Still growing| G[Check application log volume]
    F -->|Within limits| H[Monitor disk growth trends]
    C --> I[Restart dockerd]
    G --> J[Reduce verbosity or switch log driver]

Metrics & Signals To Monitor

SignalWhy it mattersWarning sign
Docker disk usage by containersjson-file logs live inside container directoriesAny single container directory > 5 GB
Exited container countStopped containers retain logs until removedCount growing without automated cleanup
Docker disk usage growth rateUnbounded logs can exhaust space faster than expectedGrowth > 1 GB/day without workload change
Disk free on /var/lib/dockerRotation is a safeguard, not a guarantee< 20 % free
Docker daemon response latencyDisk pressure from logs degrades daemon performanceSustained latency > 500 ms

Fixes

If The Cause Is Missing Rotation Configuration

Create or edit /etc/docker/daemon.json:

{
  "log-driver": "json-file",
  "log-opts": {
    "max-size": "10m",
    "max-file": "3"
  }
}

Apply the change with a daemon restart:

# Disruptive: restarts dockerd and briefly affects all containers
systemctl restart docker

After the restart, only new containers pick up the policy. Existing containers continue with their previous configuration until recreated.

If The Cause Is Per-Container Overrides Without Limits

Recreate the container with explicit log options:

docker run --log-driver json-file \
  --log-opt max-size=10m \
  --log-opt max-file=3 \
  ...

Docker applies log configuration at creation time. You cannot update log driver options on a running container.

If The Cause Is An Unsuitable Log Driver

If you are shipping logs to a central system, writing everything to json-file on disk may be redundant. Consider an alternative:

DriverStores logs on host disk?Rotation handled byBest for
json-fileYes, in container directoryDocker daemon via max-size/max-fileLocal debugging, small deployments
localYes, in a binary formatDocker daemon with built-in rotationProduction nodes that need minimal overhead
journaldNo, forwarded to systemd journaljournald configurationSystems already centralising the systemd journal
syslogNo, forwarded to syslog daemonsyslog daemon configurationTraditional syslog infrastructure
fluentdNo, forwarded to FluentdFluentd pipelineEnvironments with existing Fluentd aggregation

Switching the daemon default requires editing daemon.json and restarting dockerd. Existing containers remain on their original driver until recreated.

If The Cause Is Application Log Volume

Reduce verbosity at the application level if possible. If the workload legitimately emits high volumes, avoid json-file entirely and stream directly to fluentd or syslog so the host disk is not the bottleneck.

If The Cause Is Accumulated Exited Containers

Remove stopped containers and reclaim their logs and writable layers:

# Destructive: removes all stopped containers
docker container prune -f

Warning: This deletes stopped containers and their logs. Confirm you do not need the data. For targeted cleanup, remove specific containers by ID or name.

Prevention

  • Set log-opts in daemon.json as part of host provisioning. Do not rely on operators to remember --log-opt flags.
  • Monitor Docker disk usage by containers and alert at 70% of the /var/lib/docker filesystem. Waiting until 95% leaves no room for cleanup operations.
  • Schedule automated pruning of exited containers.
  • Evaluate log driver choice during service design. json-file is convenient for local debugging but becomes a liability on high-traffic nodes.
  • Test rotation by starting a verbose container and verifying that total log size stays within max-size multiplied by max-file.

How Netdata Helps

  • Netdata tracks Docker disk usage by category, so you can see when container layers and logs dominate the total.
  • Container state counts surface exited containers that are quietly consuming disk.
  • Host disk space monitoring on the /var/lib/docker filesystem gives early warning before rotation policies are stressed.
  • Correlating disk usage spikes with container start events helps distinguish log growth from image pulls or build cache.
The Netdata solution

Docker monitoring with Netdata

Netdata auto-discovers every container and monitors Docker with per-second CPU, memory, disk, and network metrics plus ML anomaly detection. Catch disk exhaustion, OOM cascades, daemon hangs, and log explosions before they take the host down.