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-out-of-memory-oom ▌

Operations Guides

Oracle out of memory: the Linux OOM killer, SGA, PGA, and random session deaths

Oracle sessions are dying at random. Users report sudden disconnects with no application-side explanation. There is no ORA- error returned to the client, no blocking session, no lock chain. The sessions simply vanish. In dmesg or journalctl -k you find the evidence: Out of memory: Kill process <pid> (oracle...).

Kernel evidence is decisive. A foreground Oracle process killed by OOM commonly surfaces to the client as ORA-03113 or ORA-03135; ORA-27300/ORA-27301 belong to OS-system-call failures and may appear in related traces, but do not assume that they are a direct alert-log symptom of every OOM kill.

The root cause: Oracle’s combined memory footprint exceeds physical RAM. The SGA (ideally pinned in hugepages), aggregate PGA across all dedicated server processes, and OS overhead push the system past available memory. The Linux OOM killer does not understand Oracle’s internal memory model. It ranks processes by memory consumption and kills the highest-scoring victim. Oracle server processes score high because they map the SGA and carry their own PGA, so they die first.

This failure mode is dangerous because the OOM killer can target any Oracle process. If it kills a critical background process such as DBWn, LGWR, PMON, or SMON, the instance can crash. Foreground-only kills cause random session deaths that look like network problems and send engineers down the wrong diagnostic path for hours.

What this means

Oracle on Linux is a multi-process architecture. The SGA is a shared memory region allocated at startup and held for the life of the instance. PGA is private memory allocated to each dedicated server process for sorting, hashing, and session state.

The Linux kernel accounts for memory per-process. It does not know that the SGA is shared across dozens of processes. It does not know about PGA_AGGREGATE_TARGET (a soft target) or PGA_AGGREGATE_LIMIT (a hard limit, introduced in 12c). When total system memory pressure exceeds a threshold, the OOM killer picks a victim based on its oom score, which is heavily influenced by the process’s resident set size.

Oracle processes score high because they map the SGA into their address space and carry their own PGA allocations. Without hugepages, the situation is worse: each process’s page table entries for the SGA consume additional kernel memory, sometimes gigabytes for large SGAs.

Oracle’s memory limits are advisory to the database but invisible to the kernel. PGA_AGGREGATE_LIMIT can prevent sessions from allocating more PGA by raising ORA-04036, but it does not prevent the kernel from killing processes when the system as a whole runs out of RAM.

flowchart TD
    A["SGA in hugepages, fixed allocation"] --> E["Physical RAM exhausted"]
    B["PGA aggregate grows: sorts, hash joins, leaks"] --> E
    C["OS and co-located processes"] --> E
    E --> F["OOM killer selects target"]
    F --> G["Oracle server process killed"]
    G --> H["User session disconnects"]
    F --> I["Background process killed: crash risk"]

Common causes

CauseWhat it looks likeFirst thing to check
SGA + PGA exceed physical RAMOOM kills in dmesg targeting oracle PIDs; random session drops`dmesg
HugePages not configuredPage table overhead consuming additional memory; SGA mapped via regular 4K pagesgrep -i huge /proc/meminfo; check HugePages_Total
AMM (MEMORY_TARGET) on LinuxSGA allocated via /dev/shm instead of hugepages; incompatible with HugePagesCheck memory_target in V$PARAMETER
PGA leak or runaway querySingle process PGA growing without bound; over allocation count rising in V$PGASTATV$PROCESS.PGA_MAX_MEM ordered descending
Co-located processes consuming RAMBackups, monitoring agents, or other databases on the same host`ps aux –sort=-%mem

Quick checks

All commands below are read-only.

# Confirm OOM killer is targeting Oracle processes
# dmesg ring buffer may have rotated on busy systems; use journalctl for persistent logs
dmesg | grep -i "out of memory\|oom"
journalctl -k | grep -i "out of memory\|oom"
# Check hugepages configuration
grep -i huge /proc/meminfo
# Check available physical memory
free -h
# Check oom_score of the PMON process (requires ORACLE_SID exported)
cat /proc/$(pgrep -f "ora_pmon_$ORACLE_SID")/oom_score
# Check page table size for the PMON process (requires ORACLE_SID exported)
cat /proc/$(pgrep -f "ora_pmon_$ORACLE_SID")/status | grep VmPTE
-- Check Oracle memory parameters
SELECT NAME, VALUE FROM V$PARAMETER
WHERE NAME IN ('sga_target', 'sga_max_size', 'pga_aggregate_target',
               'pga_aggregate_limit', 'memory_target', 'memory_max_target',
               'use_large_pages');
-- Check PGA utilization and limits
SELECT NAME, VALUE/1048576 AS mb FROM V$PGASTAT
WHERE NAME IN ('aggregate PGA target parameter',
               'total PGA inuse', 'total PGA allocated',
               'maximum PGA allocated', 'over allocation count',
               'cache hit percentage');
-- Top PGA consumers by process
SELECT SPID, PGA_ALLOC_MEM/1048576 AS pga_alloc_mb,
       PGA_MAX_MEM/1048576 AS pga_max_mb
FROM V$PROCESS
ORDER BY PGA_ALLOC_MEM DESC
FETCH FIRST 10 ROWS ONLY;  -- 12c+; use ROWNUM <= 10 on 11g
# Check alert log for OOM-related errors
adrci exec="show alert -tail 100"

How to diagnose it

  1. Confirm the OOM killer fired. Run dmesg | grep -i "out of memory\|oom" or journalctl -k | grep -i oom. Look for entries that name Oracle processes. The process name typically contains oracle or the ORACLE_SID. If you find none, the session deaths may have a different cause: network drops, OS process limits, or Oracle’s own PGA_AGGREGATE_LIMIT raising ORA-04036.

  2. Quantify the memory budget gap. Compare SGA_TARGET (or SGA_MAX_SIZE) plus PGA_AGGREGATE_TARGET against physical RAM. Leave at least 20% for OS, filesystem cache, and co-located processes. If SGA plus PGA target is close to or exceeds physical RAM, the OOM killer is inevitable under load.

  3. Verify hugepages. Check /proc/meminfo for HugePages_Total and HugePages_Free. If HugePages_Total is 0, the SGA is using regular 4K pages, and page table overhead is silently consuming additional memory. Check the use_large_pages parameter in V$PARAMETER. Oracle recommends reserving at least 30% of total memory for standard pages and no more than 70% for HugePages.

  4. Identify the PGA pressure source. Query V$PGASTAT for total PGA allocated versus aggregate PGA target parameter. If total PGA allocated exceeds the target, Oracle is over-allocating. Check over allocation count: if it is growing, sessions are consuming more PGA than Oracle intended. Query V$PROCESS ordered by PGA_ALLOC_MEM to find the top consumers. A single process consuming several GB of PGA may indicate a runaway sort, hash join, or a PL/SQL collection growing without bounds.

  5. Check for AMM misconfiguration. If memory_target is set, Oracle uses Automatic Memory Management (AMM), which allocates SGA via /dev/shm instead of hugepages. AMM and HugePages are incompatible. ASMM (sga_target) with manual PGA management is the standard production configuration on Linux.

  6. Rule out non-Oracle memory consumers. Run ps aux --sort=-%mem | head -20 to see what else is consuming memory. Co-located databases, RMAN backups, monitoring agents, or JVMs can push the system over the edge.

Metrics and signals to monitor

SignalWhy it mattersWarning sign
dmesg/journalctl OOM entriesDirect evidence the kernel killed an Oracle processAny entry naming an oracle PID
total PGA allocated (V$PGASTAT)Aggregate PGA consumption across all sessionsExceeds PGA_AGGREGATE_TARGET or approaching PGA_AGGREGATE_LIMIT
over allocation count (V$PGASTAT)Oracle is allocating PGA beyond its soft targetGrowing counter
HugePages_Total (/proc/meminfo)Whether hugepages are configured at all0 means SGA uses 4K pages
Per-process PGA_MAX_MEM (V$PROCESS)Detects PGA leaks or runaway queriesSingle process with monotonically growing PGA
OS MemAvailable (/proc/meminfo)Actual RAM available including reclaimable cacheTrending toward zero

Fixes

Reduce PGA consumption

The most immediate lever is PGA_AGGREGATE_LIMIT. If it is unset or too high, set it to a value that, combined with SGA and OS overhead, stays safely below physical RAM. In 19c documentation, the default is at least 2 GB, 200% of PGA_AGGREGATE_TARGET, or 3 MB × PROCESSES, and cannot exceed 120% of physical memory minus total SGA; exact MEMORY_TARGET interactions are version-specific. If the default is too permissive for your hardware, set it explicitly.

Lowering PGA_AGGREGATE_TARGET causes Oracle to manage PGA more aggressively, spilling sorts and hash joins to temp tablespace sooner. This trades query performance for memory safety. It is a better tradeoff than random session kills.

If a specific process is consuming excessive PGA (a PL/SQL collection leak or an unbounded sort), killing that session resolves the immediate pressure. Investigate the SQL or PL/SQL to prevent recurrence.

Ensure SGA uses hugepages

Without hugepages, each Oracle server process carries page table entries for the entire SGA. For large SGAs, page table overhead can consume significant additional kernel memory that is invisible to Oracle’s memory views.

Configure hugepages by setting vm.nr_hugepages in /etc/sysctl.conf to cover the SGA size. Each hugepage is 2 MB on most x86_64 Linux distributions. Set use_large_pages to ONLY to force the instance to fail startup if insufficient hugepages are available. AUTO_ONLY is also valid from 19c onward: it calculates and requests the required HugePages and fails startup if they cannot be allocated. Either setting makes misconfiguration obvious rather than allowing a silent fallback to 4K pages.

The memlock ulimit for the Oracle OS user must be set high enough to lock the HugePages into memory. Oracle’s 19c Linux installation guidance is at least 90% of current RAM when HugePages are enabled (and unlimited on Exadata).

Reboot after changing vm.nr_hugepages if memory is fragmented, as the allocation may fail silently on a running system.

Disable AMM if using MEMORY_TARGET

If memory_target is set, Oracle uses AMM, which allocates SGA via POSIX shared memory (/dev/shm) instead of hugepages. AMM and HugePages are incompatible. To switch from AMM to ASMM plus manual PGA management:

  1. Set sga_target and pga_aggregate_target to explicit values.
  2. Unset memory_target and memory_max_target.
  3. Restart the instance.

Requires a restart. Validate in a non-production environment first.

Protect critical processes (last resort, with caveats)

Setting oom_score_adj to -1000 (or the older oom_adj to -17) makes a process immune to the OOM killer. This can protect critical Oracle background processes. However, if the system genuinely runs out of memory and the OOM killer cannot kill the protected process, the kernel may panic or kill other processes instead. This buys time but does not solve the underlying memory budget problem. Fix the memory budget first.

Prevention

  • Budget memory explicitly. Ensure SGA_TARGET plus PGA_AGGREGATE_TARGET plus OS overhead plus co-located processes stay below 80% of physical RAM.
  • Set PGA_AGGREGATE_LIMIT explicitly. Do not rely on the default if your hardware or workload does not match the formula assumptions.
  • Verify hugepages after every restart. Check /proc/meminfo for HugePages_Free and the alert log for messages about hugepage allocation failures.
  • Monitor over allocation count in V$PGASTAT. A growing counter means PGA pressure is building before it becomes an OOM event.
  • Watch per-process PGA_MAX_MEM. A process whose PGA grows monotonically over its session lifetime has a leak. Alert when any process exceeds a threshold appropriate for your workload.
  • Keep Oracle off hosts with unpredictable co-tenants. RMAN backups, JVM application servers, and monitoring agents on the same host create memory pressure spikes that are invisible to Oracle-only monitoring.

Monitoring with Netdata

When the Netdata Oracle collector runs alongside OS metrics, you can correlate database-level memory with kernel-level pressure:

  • Per-second OS memory metrics: MemAvailable, MemFree, swap usage, and hugepage utilization collected every second, so you can see the memory cliff approaching before the OOM killer fires.
  • Per-process RSS tracking: surfaces per-process memory consumption, making it obvious when Oracle processes or co-located applications consume disproportionate RAM.
  • OOM kill event detection: detects kernel OOM kills in real time and correlates them with memory pressure trends, so you do not have to grep dmesg after the fact.
  • Oracle integration signals: PGA utilization, SGA component sizes, and session counts from V$PGASTAT and related views collected alongside OS metrics.

For setup, see Oracle Database monitoring with Netdata.

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.