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 / cassandra / cassandra-bootstrap-stuck

Operations Guides

Cassandra node stuck in joining (UJ): bootstrap diagnosis

You add a node to the ring, run nodetool status, and see it stuck in UJ (Up/Joining) for hours. The cluster sees it in gossip, but it never transitions to UN (Up/Normal). Client drivers do not route traffic to it, so the expansion has not added usable capacity. Until the state changes, the node is a ghost member: visible to the ring but unable to serve reads or writes for its assigned token ranges.

Bootstrap streams the SSTables that belong to the new node’s assigned token ranges from current replica owners. The joining node is passive for client traffic until every byte is received, validated, and made available locally. If a stream stalls, fails silently, or the joining node is interrupted mid-transfer, it stays in UJ indefinitely. The most common root cause is not the joining node; it is the health and capacity of the source nodes serving the stream.

What this means

UJ means the node has passed gossip startup and token allocation, but has not finished ingesting its replica data. It holds a token assignment, so the cluster knows it owns ranges, yet it cannot serve them. Streaming sessions are TCP-based, long-lived transfers of SSTable files. They are vulnerable to anything that interrupts sustained disk read on the source side: disk saturation, GC pauses, corrupt files, or network blips.

Bootstrap progress can be persisted, but Cassandra 5.0 disables resumable bootstrap by default (CASSANDRA-17679); with partial progress, a restart may abort instead of resuming unless resume behavior is explicitly selected. Even so, the stream will not complete until every source-side blockage is cleared. Because streaming reads raw SSTables from disk, it competes directly with compaction, client reads, and memtable flushes on the source node. When those consumers saturate the disk, the stream starves.

flowchart TD
    A[Node enters UJ state] --> B[Select source replicas]
    B --> C[Stream SSTables per range]
    C --> D{Progress stalls?}
    D -->|No| E[Continue until complete]
    E --> F[Transition to UN]
    D -->|Yes| G[Check source disk I/O]
    G --> H[Check source GC and heap]
    H --> I[Check for corrupt SSTables]
    I --> J[Resume or restart join]
    J --> C

Common causes

CauseWhat it looks likeFirst thing to check
Source node disk saturationnodetool netstats shows no byte increase between samples; source iostat shows high %util or awaitiostat -x 1 on each source node
Source node GC pressureSource node drops messages or flaps between UP and DOWN during the streamGC logs and nodetool info heap usage on source
Corrupt SSTable on sourceStream fails repeatedly at the same file or token range; errors in system lognodetool verify on the source replica
Too many parallel token rangesHigh num_tokens creates many concurrent streams, overwhelming source heap or disknodetool netstats session count and num_tokens in cassandra.yaml
Thread pool saturation on sourcenodetool tpstats on source shows pending or blocked MutationStage or ReadStage tasksnodetool tpstats on source nodes
File descriptor exhaustionSource or joining node cannot open new SSTable componentsnodetool info FD count versus ulimit -n
Network or internode timeoutSession breaks with timeout errors in logs; network latency between nodes spikesConnectivity and error logs on both sides

Quick checks

# Confirm the node is still joining
nodetool status

# Inspect active streaming sessions and bytes received
nodetool netstats

# Check for backpressure in internal thread pools
nodetool tpstats

# Check source node disk saturation
iostat -x 1

# Review recent errors and timeouts
grep -iE "stream|timeout|corrupt" /var/log/cassandra/system.log

# Check heap and GC health on the source
nodetool info | grep -i "Heap Memory"
grep -i "pause" /var/log/cassandra/gc.log | tail -20

# Check compaction backlog on source
nodetool compactionstats

# Check file descriptor pressure
nodetool info | grep "File Descriptors"
ulimit -n

How to diagnose it

  1. Confirm UJ state with nodetool status and identify the streaming sources from nodetool netstats on the joining node.
  2. Sample nodetool netstats twice, spaced by a few minutes. If bytes received or files completed do not increment, the stream is stalled.
  3. Log into the source nodes identified in netstats. Run iostat -x 1 and check %util and await. If the disk backing the data directory is saturated, streaming reads are queued behind compaction and client traffic.
  4. On the source nodes, run nodetool tpstats. Sustained pending tasks in MutationStage, ReadStage, or CompactionExecutor mean the node is too loaded to serve streams promptly.
  5. Check the source node GC logs. Stop-the-world pauses longer than a few seconds can cause internode messaging timeouts, which tear down streaming sessions.
  6. Search system.log on both sides for CorruptSSTableException, FSError, or stream timeout messages. A single corrupt SSTable on a source replica can block an entire range transfer.
  7. If the joining node was restarted mid-bootstrap, check nodetool netstats for resumed progress. On versions that support resumable bootstrap, uncompleted ranges replay from the last checkpoint. Repeated restarts can still leave gaps or conflicting sessions. If sessions look inconsistent, restart the joining node only after all source nodes are stable.
  8. If the joining node has many concurrent sessions in nodetool netstats, check num_tokens in cassandra.yaml. A very high vnode count increases parallel stream count and can saturate source-side heap or I/O.

Metrics and signals to monitor

SignalWhy it mattersWarning sign
Streaming incoming bytesDirect measure of bootstrap progressFlat for more than 30 minutes
Disk I/O await on sourceHigh await means source disk cannot read SSTables fast enoughawait greater than 50 ms sustained
GC pause duration on sourceLong pauses break internode TCP sessions and stall streamsPauses greater than 2 seconds
Pending compactions on sourceCompaction competes for the same disk as streaming readsCount trending upward during bootstrap
Thread pool pending tasksQueued tasks mean the source cannot keep up with requestsPending greater than 0 in MutationStage or ReadStage
Dropped messages on sourceThe node is shedding load; streams may be nextAny sustained non-zero rate
File descriptor usageFD exhaustion prevents opening SSTable filesUsage greater than 80% of ulimit
Pending flushesWrite path saturation delays all disk operationsMemtableFlushWriter pending greater than 0 sustained

Fixes

Address source node disk saturation

If iostat shows the data device is saturated, streaming cannot proceed until I/O is freed. Pause non-critical repairs, reduce compaction throughput with nodetool setcompactionthroughput, or schedule the bootstrap during a lower-traffic window. Adding IOPS to the source node or moving the commitlog to a separate device are longer-term fixes. Do not raise streaming socket timeouts to mask the stall; the timeout is a symptom, and extending it without fixing the source disk will prolong the incident.

Reduce pressure on source nodes

If the source node is in a GC death spiral or thread pool saturation, stop increasing load. Do not repeatedly trigger resume operations while the source is unhealthy; the stream will only fail again. Wait for the source node to return to a stable state with zero pending tasks and normal GC before allowing the join to continue.

Handle corrupt SSTables

If nodetool verify on a source node reports corruption, that SSTable must be replaced or repaired. nodetool verify reads every row and is expensive on large tables; run it during low traffic. If replication factor is greater than one, you can temporarily take the corrupt source node offline so the joining node streams from healthy replicas instead. After the new node joins, run a full repair on the affected range.

Resume or restart the joining node

If the stream failed but the joining node persists bootstrap state, resume only if resumable bootstrap is explicitly enabled. On Cassandra 5.0, nodetool bootstrap resume is disabled unless the bootstrap-progress property is explicitly set to false; --force overrides that guard and is potentially dangerous. Verify with nodetool netstats that progress continues. If the node does not support resumable bootstrap, you may need to wipe the data directory and restart the bootstrap from scratch after fixing the source-side issue.

WARNING: Wiping the data directory is destructive. Stop Cassandra, clear the data, commitlog, and saved_caches directories, and ensure the node is fully removed from the ring before you re-bootstrap.

Lower the parallel stream count

A high num_tokens value increases the number of token ranges and therefore the number of concurrent streaming sessions. If source nodes are OOMing or saturating disk, reducing num_tokens requires reconfiguring and re-bootstrapping the joining node, but it can make large-node bootstraps stable.

Run repair after recovery

Any bootstrap that was interrupted or resumed after timeout may have missed writes, especially if hints were not delivered during the window. Once the node reaches UN, run nodetool repair to reconcile any inconsistencies before the node serves production traffic.

Prevention

  • Validate source node health before bootstrap. Check nodetool compactionstats, heap usage, and disk headroom.
  • Schedule bootstrap during off-peak hours when source node I/O and GC are stable.
  • Monitor source node disk latency and thread pools continuously during the operation.
  • Keep num_tokens aligned with your heap and disk capacity. Very large nodes may need fewer vnodes.
  • Verify SSTable integrity with nodetool verify before major topology changes.
  • In containerized environments, use Pod Disruption Budgets to prevent mid-stream pod eviction.

How Netdata helps

  • Correlate flat streaming throughput on the joining node with disk latency spikes on the source node in the same time window.
  • Track GC pause duration on source nodes to preempt streaming timeouts before sessions break.
  • Alert on sustained pending tasks in the MutationStage and CompactionExecutor during bootstrap operations.
  • Monitor off-heap memory growth on source nodes to catch OOM risk from too many concurrent SSTable transfers.
  • Surface file descriptor utilization per node to detect the approach of ulimit exhaustion during heavy streaming.
The Netdata solution

Cassandra monitoring with Netdata

Netdata monitors Apache Cassandra with per-second metrics and automatic dashboards. Correlate GC pauses, compaction backlog, tombstone rates, pending hints, and disk usage across nodes to catch a creeping cluster before it tips over.