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 / oracle-database / oracle-database-rac-gc-buffer-busy ▌

Operations Guides

Oracle RAC global cache waits: gc buffer busy, interconnect health, and workload affinity

In Oracle RAC, the global cache (gc) wait events describe time spent moving or coordinating access to data blocks across instances. When these waits dominate the top wait list, the cluster is paying for cross-instance coordination instead of serving work. The signal is clear in V$SYSTEM_EVENT, but the cause is not.

gc buffer busy waits are the most misunderstood of these events. They are not transfer waits. They are contention waits. The same hot blocks are being requested from multiple instances, and sessions queue behind an in-flight transfer instead of getting their own block right away. The fix is almost always workload affinity, not interconnect tuning.

The interconnect is the other half. Block transfers between instances happen over the cluster interconnect, and latency there dominates transfer waits. On a healthy dedicated interconnect, average gc transfer waits sit under 1ms. Above 3ms indicates congestion. Above 10ms indicates interconnect failure or silent failover to the public network.

What this means

The gc% events in V$SYSTEM_EVENT split into two families. Confusing them wastes diagnosis time.

Transfer waits describe the block actually moving over the interconnect:

  • gc cr grant 2-way, gc cr block 2-way, gc cr block 3-way for consistent read transfers
  • gc current grant 2-way, gc current block 2-way, gc current block 3-way for current mode transfers

Average latency under 1ms is normal on a dedicated high-speed interconnect (InfiniBand, 10GbE or better). Above 3ms indicates congestion or an undersized link. Above 10ms indicates interconnect failure or failover to the public network.

Contention waits describe a session waiting for a block that someone else is already transferring:

  • gc buffer busy acquire: another session on the same local instance already has an open global cache lock request for that block, so your session waits behind it instead of issuing a redundant request
  • gc buffer busy release: a remote instance holds the global cache lock for the block and has not released it yet, so your session waits for the remote transfer to complete

These are not interconnect problems. They are workload placement problems. The same hot block is being touched from multiple instances, and the cluster is serializing on the lock instead of serving concurrent work.

flowchart TD
  A["gc% waits in top events"] --> B{"Transfer or contention?"}
  B -->|"gc cr/current block"| C["Transfer wait: tune interconnect"]
  B -->|"gc buffer busy acquire/release"| D["Contention: fix workload affinity"]
  C --> E{"avg latency"}
  E -->|"< 1ms"| F["Normal cross-instance traffic"]
  E -->|"> 3ms"| G["Congestion: NIC, UDP, MTU"]
  E -->|"> 10ms"| H["Verify V$CLUSTER_INTERCONNECTS IS_PUBLIC"]

Common causes

CauseWhat it looks likeFirst thing to check
Workload not partitioned across instancesgc buffer busy acquire and release dominate; same SQL_IDs active on multiple instancesV$ACTIVE_SERVICES and where sessions actually land vs. service placement
Interconnect failover to public networkAverage gc transfer waits jump 10x to 100x; private interface traffic near zeroV$CLUSTER_INTERCONNECTS.IS_PUBLIC on the active interface
Interconnect congestion or packet lossgc waits >3ms average; gc blocks lost non-zero; NIC errorsOS-level NIC stats and UDP socket overflows
Hot blocks from monotonic keysgc buffer busy concentrated on specific segments; local buffer busy waits tooV$INSTANCE_CACHE_TRANSFER and V$SEGMENT_STATISTICS
Instance rebalance after node failuregc traffic spikes during recovery; transfers between surviving nodesCluster node status and recent instance restarts

Quick checks

-- gc wait events by total time waited
SELECT EVENT, TOTAL_WAITS, TIME_WAITED_MICRO,
       ROUND(TIME_WAITED_MICRO/NULLIF(TOTAL_WAITS,0)/1000, 2) AS avg_ms
FROM V$SYSTEM_EVENT
WHERE EVENT LIKE 'gc%'
ORDER BY TIME_WAITED_MICRO DESC;
-- verify Oracle is using the private interconnect, not the public network
SELECT NAME, IP_ADDRESS, IS_PUBLIC, CON_ID
FROM V$CLUSTER_INTERCONNECTS;
-- IS_PUBLIC should be NO for the interface Oracle is actually using
-- per-instance block transfer and congestion stats (19c column: INSTANCE)
SELECT INSTANCE, CLASS, CR_BLOCK, CR_BUSY, CR_CONGESTED,
       CURRENT_BLOCK, CURRENT_BUSY, CURRENT_CONGESTED
FROM V$INSTANCE_CACHE_TRANSFER
ORDER BY CR_BLOCK + CURRENT_BLOCK DESC;
-- CR_BUSY / CURRENT_BUSY non-zero = contention. CR_CONGESTED = interconnect saturation.
-- compare with all configured interfaces to catch misconfiguration
SELECT * FROM V$CONFIGURED_INTERCONNECTS;
# verify interconnect interface and MTU at the OS level
ip link show <interconnect_interface>
# look for mtu 9000 if jumbo frames are configured
# verify OCR-registered interface configuration (read-only)
oifcfg getif
# confirm the private subnet is registered as cluster_interconnect, not public
-- services defined in the cluster (use srvctl or DBA_SERVICES for preferred-instance placement)
SELECT NAME, NETWORK_NAME FROM V$ACTIVE_SERVICES;

How to diagnose it

  1. Confirm gc waits are a meaningful slice of DB time. A handful of milliseconds per wait on a busy cluster is normal. Look at gc wait time as a percentage of total DB time. Above 15% sustained warrants investigation.

  2. Separate transfer waits from contention waits. If gc cr block 2-way, gc cr block 3-way, gc current block 2-way, or gc current block 3-way dominate with high average latency, you have an interconnect problem. If gc buffer busy acquire or gc buffer busy release dominate, you have a workload placement problem.

  3. For transfer waits, verify the interconnect interface. Query V$CLUSTER_INTERCONNECTS. The IS_PUBLIC column should be NO. If it is YES, Oracle is using the public network for cache fusion traffic, and latency will be 10x to 100x higher than expected. This is a critical misconfiguration.

  4. For transfer waits on a correctly private interconnect, check OS-level signals. Look at NIC error counters, UDP socket buffer overflows, switch port errors, and MTU mismatches. A jumbo frame configured on one node and standard 1500 on another silently fragments packets.

  5. For contention waits, identify the hot blocks. V$INSTANCE_CACHE_TRANSFER shows which instance pairs exchange the most blocks. CR_BUSY and CURRENT_BUSY indicate contention rather than clean transfers. Drill into V$SEGMENT_STATISTICS for buffer busy waits per segment to find the specific objects.

  6. For contention waits, look at where the workload is running. If the same SQL_IDs are active on multiple instances against the same hot tables, that is the cause. RAC cache fusion tolerates cross-instance access but does not make parallel writers on the same block cheap.

Metrics and signals to monitor

SignalWhy it mattersWarning sign
gc wait average latencyDirect measure of interconnect performance>3ms sustained, >10ms is page-worthy
gc waits as % of DB timeShows whether gc is the bottleneck or just noise>15% sustained
V$CLUSTER_INTERCONNECTS.IS_PUBLICCatches silent failover to public networkIS_PUBLIC = YES on the active interface
V$INSTANCE_CACHE_TRANSFER.CR_BUSY / CURRENT_BUSYDistinguishes contention from clean transfersNon-trivial values sustained
gc blocks lostIndicates dropped interconnect packetsAny non-zero value
NIC error counters and UDP socket overflowsLower-layer causes of high gc latencyNon-zero errors or overflows

Fixes

Interconnect failover to public network

This is the highest-impact RAC performance problem and the easiest to verify. If V$CLUSTER_INTERCONNECTS shows the public interface in use, Oracle fell back from the private interconnect. Causes include bond failure, switch failure, or a misconfigured interface registration in the OCR.

The fix is to correct the OCR-registered interface with oifcfg and restart the affected instance or instances. The private subnet must be registered as cluster_interconnect, and the public subnet as public. This is disruptive: cache fusion traffic re-routes only after instance restart. Plan a window. Do not attempt this on a live production cluster without testing the change in a non-production environment first.

Interconnect congestion and packet loss

If the private interconnect is in use but gc latency is high, the link is saturated or losing packets. Common causes:

  • UDP receive buffer sizes too small, causing socket overflows and silent packet loss. Check OS-level UDP stats.
  • Switch port speed fixed instead of auto-negotiate, or duplex mismatches.
  • MTU mismatch between nodes, with jumbo frames on one and standard 1500 on another, causing fragmentation.
  • Single interconnect link where a bonded pair should be in use.

Verify jumbo frames are configured end-to-end on the private network. Check ip link show on all nodes for MTU 9000. Check switch configuration for the private VLAN.

Workload without service affinity

This is the most common RAC performance mistake. Running the same workload across all instances without service-based partitioning causes gc buffer busy waits because every instance fights over the same hot blocks.

The fix is service-based workload partitioning. Define application-specific services with preferred and available instances, and route each application tier to its service. A service that serves the OLTP workload should prefer one instance and only fail over to another when the preferred instance is down. A batch service should prefer a different instance. Under normal operation, each hot block has one writer instance, and cache fusion transfers happen only on failover, not during steady state.

This is a design change, not a parameter change. It requires application connection string changes, service definitions, and coordination with whoever owns the application deployment.

Hot blocks from monotonic keys

If gc buffer busy waits concentrate on specific segments, look at the workload pattern. Monotonically increasing sequences or right-hand index inserts on a single table create hot leaf blocks. When sessions on multiple instances insert into the same hot index leaf, every insert triggers a cross-instance lock transfer.

Local fixes include reverse key indexes (which spread inserts across the index but defeat range scans), hash partitioning of the index, or larger sequence cache sizes to reduce enq: SQ - contention on the sequence itself. The RAC-specific fix is still workload affinity: keep the inserting workload on one instance so the hot block never crosses the interconnect.

Prevention

  • Service-based workload partitioning. Every application tier should map to a service with preferred instances. Without this, RAC scales worse than single instance under write contention.
  • Interconnect monitoring, not just database monitoring. Track gc wait latency, V$CLUSTER_INTERCONNECTS.IS_PUBLIC, NIC error counters, and gc blocks lost as first-class signals.
  • Jumbo frames on the private network from day one. Retrofitting MTU 9000 on a live cluster is error-prone.
  • UDP buffer sizing on all nodes. Default OS UDP receive buffer sizes are often too small for RAC cache fusion traffic under load.
  • Service placement review after every node failure. When a node restarts, services may rebalance. Verify the workload is back on its preferred instances before declaring the incident over.

How Netdata helps

  • Per-second gc wait latency. The average wait time per gc event is the single most useful RAC performance signal. A spike from 1ms to 5ms shows up immediately, before users notice.
  • IS_PUBLIC correlation. When gc latency jumps, the first question is whether Oracle fell back to the public network. Correlating gc waits with V$CLUSTER_INTERCONNECTS output answers that question in one view.
  • gc waits vs. local buffer busy waits. Distinguishing local hot block contention (single instance) from cross-instance contention (RAC) tells you whether the fix is index design or service placement.
  • Transfer waits vs. contention waits. Splitting gc cr/current block waits from gc buffer busy waits tells you whether to tune the interconnect or tune the workload.
  • Per-instance load balance. If one instance carries 80% of the active sessions, service affinity is not working. Correlating active session count per instance with gc wait time shows this clearly.

Netdata’s Oracle Database monitoring with Netdata brings these signals together with per-second metrics and ML anomaly detection.

The Netdata solution

Oracle Database monitoring with Netdata

Netdata monitors Oracle Database with per-second metrics and automatic dashboards. Watch wait events, redo and archive-log activity, tablespace and undo space, and session and lock activity so the failure modes in these runbooks surface before the instance hangs.