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 / php-fpm / php-fpm-session-lock-contention ▌

Operations Guides

PHP-FPM session lock contention: file sessions serializing a user's requests

A single user reports AJAX-heavy pages loading slowly, but the server has spare worker capacity and CPU is barely loaded. The PHP-FPM status page shows active workers climbing toward max_children. You raise max_children and nothing improves. The slow log, when configured, shows stack traces parked at session_start().

This is session lock contention. PHP’s default file-based session handler acquires an exclusive flock(LOCK_EX) on the session file at session_start() and holds it until the script ends or session_write_close() is called. When one browser session makes concurrent requests (parallel AJAX calls, SPA data fetching, long-polling, upload progress checks), those requests serialize completely behind that single lock.

Each blocked request occupies a worker slot while sleeping on a kernel flock, burning near-zero CPU. Raising max_children does not help: the new workers immediately block on the same lock.

What this means

PHP’s files session handler (the default) calls flock(fd, LOCK_EX) inside session_start(). The call blocks until no other process holds the lock. For a request that only reads $_SESSION and never writes, the lock is still held for the full request duration. There is no read-shared mode.

Two properties make this especially insidious:

  • session.lazy_write does not help. This INI setting (default 1 since PHP 7.0) skips the write call if session data has not changed, but it does not release the lock early. The lock is held from session_start() until session_write_close() or script shutdown. Even read-only session access blocks all other requests for the same session ID.
  • max_execution_time does not interrupt the block. On typical non-Windows PHP-FPM builds it measures CPU time, not wall-clock time; time spent sleeping inside flock is not CPU time. If PHP is built with --enable-zend-max-execution-timers (ZTS builds default to it since PHP 8.3), elapsed time including blocking waits counts instead. request_terminate_timeout in PHP-FPM is your only reliable kill switch for stuck workers, and even that only fires on wall-clock duration from request acceptance.

The serialization is per session ID, not global. One user with ten parallel AJAX requests sees all ten queue behind one lock. Two hundred users doing the same thing at once means two hundred independent lock queues, each consuming workers. Aggregate worker utilization climbs, CPU stays low, throughput collapses.

sequenceDiagram
    participant Browser
    participant Nginx
    participant W1 as FPM Worker A
    participant W2 as FPM Worker B
    participant W3 as FPM Worker C
    participant SF as Session file (flock LOCK_EX)

    Browser->>Nginx: AJAX req 1 (sess=abc)
    Browser->>Nginx: AJAX req 2 (sess=abc)
    Browser->>Nginx: AJAX req 3 (sess=abc)
    Nginx->>W1: dispatch req 1
    Nginx->>W2: dispatch req 2
    Nginx->>W3: dispatch req 3
    W1->>SF: flock(LOCK_EX) acquired
    W2->>SF: flock(LOCK_EX) BLOCKED
    W3->>SF: flock(LOCK_EX) BLOCKED
    W1-->>SF: script ends, lock released
    Note over W2,SF: lock acquired by W2
    W2-->>SF: script ends, lock released
    Note over W3,SF: lock acquired by W3
    W3-->>SF: script ends, lock released

Common causes

CauseWhat it looks likeFirst thing to check
AJAX-heavy page firing parallel requests with the same session cookieOne user’s page load is slow, server-wide metrics look normalSlow log for session_start() frames on AJAX endpoints
Long-running request holding the session lock (file upload, report generation, slow external API call)Intermittent slowness on specific endpoints, other requests for same user stall behind itPer-worker request duration on the full status page
Polling endpoint (chat, notifications, progress) using PHP sessionsSteady-state worker saturation with low CPU, slow log shows polling URIsWhether the polling route actually needs session write access
SPA batch-fetching multiple data endpoints on route changeBursty latency spikes when users navigate, resolves between navigationsBrowser devtools network tab for parallel same-session requests
Read-only endpoint that calls session_start() out of habit or framework defaultEndpoints that never write $_SESSION still blockApplication code or framework middleware for unnecessary session_start() calls

Quick checks

# Check session handler and save path (path varies by distro and php.ini)
php -r "echo 'handler: ' . ini_get('session.save_handler') . \"\n\"; echo 'path: ' . ini_get('session.save_path') . \"\n\"; echo 'lazy_write: ' . ini_get('session.lazy_write') . \"\n\";"

# Check for multiple processes holding or waiting on the same session file.
# Adjust the path to match your session.save_path.
lsof /var/lib/php/sessions/sess_* 2>/dev/null | awk '{print $9}' | sort | uniq -c | sort -rn | head

# Alternative with fuser if lsof is unavailable. Output format differs: PIDs
# are printed per file rather than one row per descriptor.
fuser /var/lib/php/sessions/sess_* 2>/dev/null

# Fetch the full status page (requires pm.status_path set in the pool config;
# the URL path depends on your web server and pm.status_path value).
curl -s http://127.0.0.1/status?full | head -80

# Slow log entries showing session_start blocking (requires request_slowlog_timeout > 0)
grep -A8 "session_start" /var/log/php-fpm/slow.log | head -40

# Confirm request_slowlog_timeout is configured (0 means disabled)
php-fpm -tt 2>&1 | grep -E "slowlog|request_slowlog_timeout"

# Check whether read_and_close or session_write_close is already used in the codebase
grep -rn "read_and_close\|session_write_close" /path/to/app/

If session.save_handler returns files, you are vulnerable to this contention pattern. If lsof shows two or more FPM worker PIDs against the same sess_* file, you have active contention right now.

How to diagnose it

  1. Confirm the slow log is capturing session_start frames. If request_slowlog_timeout is 0 (disabled, the default), enable it first. A value of 2-5 seconds is sufficient for detecting session lock contention. Restart or reload the pool for the change to take effect, then wait for a reproduction or trigger one. The stack trace should show the worker stopped inside session_start() or the session open callback, with last request cpu near zero on the full status page.

  2. Cross-reference with lsof output. Run the lsof command from the quick checks during a slow period. Multiple worker PIDs against a single session file confirms that requests are queuing on the lock, not on compute or database I/O.

  3. Check the CPU-to-active-process ratio. Compare active processes from the status page against host CPU. If active workers are high but CPU utilization is low (under 20-30%), the workers are sleeping on something. Session locks are one cause; slow database queries and external API timeouts are the other usual suspects. The slow log distinguishes them: session lock contention shows session_start() in the trace, database contention shows PDO or mysqli calls.

  4. Identify the originating endpoints. The full status page exposes request URI per worker. Look for patterns where multiple workers are serving the same user’s session (identical or related URIs from the same session cookie). AJAX endpoints, polling routes, and SPA data-fetch paths are the usual offenders.

  5. Distinguish from genuine worker exhaustion. In real worker exhaustion (traffic spike or slow backend), the slow log shows diverse URIs and diverse blocking points (database, curl, file I/O). In session lock contention, the slow log concentrates on session_start() and the affected URIs are all from the same session ID. The telltale sign is low CPU with high active workers and session_start() in every slow trace.

Metrics and signals to monitor

SignalWhy it mattersWarning sign
Slow requests counter rateEach increment is a request that exceeded request_slowlog_timeout, and the slow log tells you whereSustained non-zero rate with session_start frames in the log
Active processes vs system CPUWorkers sleeping on flock show high active count but low CPUActive climbing past 80% of max_children while CPU stays flat
Per-worker request duration (full status)Blocked requests show long durations with low last request cpuBimodal distribution: some workers fast, some parked for seconds
Per-worker request URI (full status)Identifies which endpoints are involved in contentionMultiple workers serving related URIs from the same session
max children reached counterIndicates the pool tried to scale and could notIncrementing while CPU stays low suggests I/O-bound workers, not compute saturation

Fixes

Close the session early in application code

The primary mitigation is calling session_write_close() as early as possible in the request lifecycle, after the last read or write to $_SESSION. This releases the flock immediately, letting the next queued request proceed.

// After all session reads/writes are done:
$_SESSION['last_activity'] = time();
session_write_close();

// Long-running work (API call, file processing, report generation) proceeds
// without holding the session lock.
$response = $httpClient->get('/slow-endpoint');

This is the lowest-risk fix because it does not change the session backend or application architecture. The tradeoff is that you cannot write to $_SESSION after calling session_write_close(). If you need to update session state later in the request, restructure the code to write first, close, then do the slow work.

Use read_and_close for read-only requests

Since PHP 7.0, session_start() accepts an options array. Passing ['read_and_close' => true] reads the session data and immediately releases the lock. This is useful for endpoints that need to check authentication or read session state but never modify it.

session_start(['read_and_close' => true]);
$user_id = $_SESSION['user_id'] ?? null;
// Lock is already released. Concurrent requests for this session proceed immediately.

One caveat: read_and_close does not update the session file’s modification time. If your application relies on session.gc_maxlifetime for session expiry based on last access time, read-only requests will not refresh the timer. Sessions can be garbage collected while still in active read-only use.

Do not start sessions on endpoints that do not need them

API endpoints returning JSON, static data endpoints, polling routes, and health checks often call session_start() through framework middleware even when they never touch $_SESSION. Audit your routing and middleware configuration. If an endpoint does not read or write session data, it should not start a session. This eliminates lock contention entirely for those routes.

Switch to a session backend with different locking semantics

If application-level fixes are impractical (large codebase, framework constraints, many endpoints), switching the session handler changes the locking model:

  • Redis (phpredis): Does not lock by default; phpredis 4.1 introduced opt-in locking with redis.session.locking_enabled=1. Without explicit locking enabled, concurrent requests for the same session proceed in parallel. This eliminates file-based flock contention but means concurrent writes to the same session can produce last-write-wins behavior.
  • Memcached: Locks by default (memcached.sess_locking defaults to on). Switching to Memcached does not eliminate contention by itself, but the locking implementation uses a retry loop rather than a kernel flock, which can behave differently under high contention and avoids NFS-related flock issues.

Switching handlers requires careful testing of session consistency assumptions in your application. If your code assumes serialized session access (for example, using $_SESSION as a per-request mutation guard), removing locking can introduce race conditions.

Separate long-running endpoints from session-using ones

File uploads, report generation, and external API calls that take seconds should not hold a session lock. Either call session_write_close() before the slow work begins, or route these endpoints through a mechanism that does not use PHP sessions (a signed token, a job queue with polling, or a separate API path).

Prevention

  • Enable request_slowlog_timeout on every production pool. Without it, you have no visibility into where workers are blocking. A value of 2-5 seconds catches session lock contention before it saturates the pool.
  • Audit session_start() calls. Every endpoint that starts a session but does not need write access should use read_and_close or skip the session entirely. Frameworks that auto-start sessions on every request are the most common source of unnecessary locks.
  • Design parallel endpoints to be sessionless. If a page fires ten AJAX requests on load, at most one should hold a session lock. The other nine should authenticate via a token or cookie that does not require session_start().
  • Document the flock behavior for your team. The default file handler’s exclusive locking is not obvious from the API surface. Developers who have not encountered it will assume read-only session access is concurrency-safe.

How Netdata helps

  • Per-second active and idle process counts let you see the active-but-low-CPU pattern that distinguishes lock contention from compute-bound saturation. A sudden climb in active workers with flat CPU is the leading indicator.
  • Slow requests counter tracked as a rate, not just a cumulative gauge, surfaces the moment requests start exceeding request_slowlog_timeout. Correlate the rate spike with the slow log to confirm session_start() frames.
  • CPU utilization alongside PHP-FPM metrics on the same dashboard makes the I/O-bound diagnosis immediate. Low CPU with high active workers points to flock, database waits, or external API stalls; the slow log disambiguates.
  • Anomaly detection on active process count can flag unexpected saturation events that do not match traffic patterns, which is often how session lock contention first surfaces during an AJAX-heavy page redesign or SPA migration.
  • Listen queue depth monitoring at per-second resolution catches the downstream effect: once session-serialized workers fill the pool, the listen queue builds and connections start refusing.