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Start with worker_processes auto;. NGINX will try to create workers for the CPU capacity visible to the NGINX process, which is usually the right baseline in a modern VM or container. First check the CPUs visible inside that same runtime—not the host’s total—then verify performance under representative traffic. Use a fixed number only when measurements, CPU quotas, affinity rules, or an operational constraint show that it is better.
What “CPU cores” means to NGINX
NGINX uses a two-level process model. One master process reads the configuration, opens listening sockets, and manages worker lifecycles. Worker processes accept connections and perform request processing. The worker_processes directive controls how many workers NGINX starts.
The important number is not necessarily the physical core count printed by a server inventory page. NGINX can use only the processing capacity exposed to its process. A virtual machine may be assigned fewer vCPUs than its host has cores. A container can be restricted by a CPU quota or a cpuset. An orchestrator can reserve or limit CPUs for a workload. Those limits define the CPU set that matters for worker sizing.
Hyper-threading and simultaneous multithreading also make “core” terminology ambiguous. Operating systems normally report logical processors, and automatic sizing works from the processors available to the process rather than attempting to distinguish physical cores from threads. Treat the reported effective CPU set as the starting capacity, then validate the result with real traffic.
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How to check the CPUs visible to NGINX
Run the check in the same operating-system environment where NGINX runs. A host-level command can overstate capacity when NGINX is inside a VM, container, cgroup, or cpuset.
Linux host or virtual machine
These commands provide progressively more detail:
nproc
nproc --all
getconf _NPROCESSORS_ONLN
lscpunprocis a useful first check of processing units available to the current process.nproc --allshows all processors known to the operating system, which can be higher than the effective set after affinity or quota restrictions.getconf _NPROCESSORS_ONLNreports processors currently online.lscpudisplays topology, including sockets, physical cores, logical CPUs, and NUMA information.
For a direct view of the process’s affinity mask, inspect the NGINX master process:
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pidof nginx
ps -o pid,psr,comm -p <master-pid>
taskset -cp <master-pid>Replace <master-pid> with the master process ID. The affinity result tells you which logical CPUs the process may run on. A mask can make the effective set smaller than the machine-wide total.
Docker or another container runtime
Enter the running container and run the same checks there:
docker exec -it <container-name> nproc
docker exec -it <container-name> getconf _NPROCESSORS_ONLNIf the container has a CPU quota, inspect the limit as well as the processor count. On systems using cgroup v2, this file commonly contains the quota and period:
docker exec -it <container-name> cat /sys/fs/cgroup/cpu.maxA value such as max 100000 means no cgroup CPU quota is set in that file. A pair of numbers such as 200000 100000 represents an allowance of two CPUs’ worth of time, although the exact scheduling behavior still depends on the runtime and host. A cpuset restriction can impose a separate limit, so check the CPUs assigned to the container when the numbers do not agree.
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Run a processor check in the pod rather than on the Kubernetes node:
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kubectl exec -it <pod-name> -- nproc
kubectl exec -it <pod-name> -- getconf _NPROCESSORS_ONLNReview the pod’s CPU requests and limits at the same time. A node may expose dozens of CPUs while the pod is limited to a fraction of one CPU or pinned to a small set. Configure NGINX for what the pod can actually schedule, not for the node’s total.
Windows environments
If NGINX is running directly on Windows, PowerShell can show logical processors:
Get-CimInstance Win32_Processor | Select-Object NumberOfCores,NumberOfLogicalProcessorsWhen NGINX is running in WSL, a VM, or a container on Windows, run the Linux command inside that environment. Its CPU view can differ from the Windows host.
Configure worker_processes
Place the directive in the main (top-level) NGINX configuration, outside the events and http blocks:
worker_processes auto;
events {
worker_connections 512;
}The accepted syntax is worker_processes number | auto. The documented default is 1, so an unmodified installation may run one worker even on a multi-CPU system. The auto parameter is supported in NGINX versions 1.3.8 and 1.2.5 and later release lines that include it.
With auto, NGINX attempts to detect the CPU capacity available to the process and choose a worker count. It is a starting policy, not a promise that every worker will be busy or that throughput will scale linearly. NGINX documentation notes that the optimal value also depends on the number of CPU cores, the number of hard disk drives storing data, and the load pattern.
After editing the file, test and reload it:
nginx -t
nginx -s reloadUse the service manager on distributions that manage NGINX as a service, for example:
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sudo systemctl reload nginxA reload starts the new worker generation while existing workers finish active requests. If the configuration test fails, correct the error before reloading; the old configuration remains in use until a valid reload succeeds.
Should the worker count equal the number of CPU cores?
Often, an explicit count near the effective CPU count is reasonable, and NGINX’s HTTPS guidance recommends several workers on multiprocessor systems, no fewer than the available CPU cores, with worker_processes auto; shown in its multi-core example. That guidance is a baseline rather than a universal performance law.
| Choice | What it does | When it fits | Risks or limits |
|---|---|---|---|
worker_processes auto; |
Attempts to select workers from the CPU capacity visible to NGINX. | Most VMs, containers, and general-purpose servers; environments whose CPU allocation can change. | Automatic detection cannot compensate for a low CPU quota, an unsuitable file-descriptor limit, or a workload bottleneck elsewhere. |
Explicit integer, such as worker_processes 4; |
Starts exactly the configured number of workers. | Measurements show a stable optimum, or an orchestrator, licensing policy, or deployment standard requires a fixed count. | Too few workers can leave CPU capacity unused; too many add scheduling and memory overhead without increasing useful work. |
Default value 1 |
Runs one worker when no directive is configured. | Small, low-traffic installations or compatibility testing. | It can underuse a multi-CPU system, especially for concurrent TLS, proxy, or static-file traffic. |
Do not multiply workers simply because a server reports more CPUs. Compare CPU utilization, request latency, throughput, queueing, and error rates before and after a change. A disk-heavy workload, slow upstream service, or restrictive connection limit may be the real bottleneck.
How many worker_connections do you need?
worker_connections sets the maximum simultaneous connections opened by one worker. Its documented default is 512. The limit includes connections to proxied upstream servers, not only client sockets, and it cannot exceed the process open-file limit.
For a rough planning ceiling, the configured worker count multiplied by worker_connections gives the sum of per-worker connection slots. It is not a guaranteed client count: a reverse-proxy request can consume one connection to the client and another to an upstream, keep-alive connections remain open, and operating-system file-descriptor limits can cap the result first.
Raise the value only after checking the open-file limit and the workload’s connection pattern:
ulimit -n
cat /proc/<master-pid>/limits | grep -i "open files"Changing worker_processes without raising a restrictive descriptor limit does not create more usable connections. Conversely, increasing worker_connections consumes more potential descriptors and memory, so size it for measured concurrency rather than an arbitrary large number.
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A practical tuning procedure
- Measure the effective CPU set. Run
nprocor the equivalent command inside the VM, container, or pod that runs NGINX. Record quotas and affinity masks when they apply. - Set the baseline. Add
worker_processes auto;at the top level. Keep the existingeventsblock, or defineworker_connections 512;explicitly so the starting value is clear. - Validate syntax. Run
nginx -tand fix every reported path, permission, or syntax error before attempting a reload. - Reload safely. Use
nginx -s reloador the appropriate service-manager reload command. Confirm that the new workers appear and that the master remains healthy. - Apply representative load. Include the traffic mix that matters: static files, TLS handshakes, dynamic proxying, long-lived keep-alive connections, or disk-heavy responses. A short synthetic burst can produce a different answer from normal traffic.
- Observe the right signals. Compare CPU utilization per worker, latency percentiles, throughput, active connections, upstream timings, retries, and 4xx/5xx rates. Also watch memory and open-file usage.
- Change one variable at a time. If CPU is saturated and latency improves with a different count, test an explicit integer around the measured optimum. If workers are idle while another resource is constrained, adding workers will not solve the problem.
- Recheck after deployment changes. A new container limit, VM size, CPU pinning policy, TLS configuration, or upstream service can invalidate a previously optimal worker count.
When an explicit worker count is justified
Stable, measured performance
Choose an integer when controlled tests repeatedly show lower latency or higher throughput than auto and the CPU allocation is stable. Document the test conditions, because a count tuned for static files may not suit TLS termination or proxy-heavy traffic.
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CPU quotas and fractional allocations
A container limited to a fraction of a CPU should not be treated like a host with many logical processors. Automatic detection may follow the visible CPU set, but a quota can still throttle execution. Verify both the count and the quota before deciding that more workers are needed.
Operational or licensing constraints
An orchestrator, capacity policy, or software integration may require a fixed number of processes. In that case, set the mandated integer and validate connection, descriptor, and latency behavior under the actual limit.
Debugging and isolation
A temporary single-worker configuration can make troubleshooting easier by reducing process-level variation. It is a diagnostic choice, not evidence that one worker is optimal for production.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.CPU affinity: use it only deliberately
worker_cpu_affinity can bind workers to CPU sets represented by bitmasks. Workers are not bound to specific CPUs by default. The documented auto affinity mode is available on FreeBSD and Linux.
Affinity can help when you have a deliberate CPU-placement design, such as isolating NGINX from another latency-sensitive process. It can also hurt when it conflicts with a container’s cpuset or an orchestrator’s CPU assignment. If a process is already restricted to a small mask, adding an incompatible affinity map can leave workers competing on fewer CPUs than intended. Start without affinity, inspect the effective mask, and introduce binding only when measurements and the deployment design justify it.
Common symptoms and fixes
Only one worker appears on a multi-core machine
Check whether worker_processes is omitted or set to 1. Confirm the active configuration with nginx -T, then add worker_processes auto; or a measured integer and reload.
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More workers do not increase throughput
Inspect upstream response time, disk wait, network capacity, TLS cost, CPU quotas, and open-file limits. Worker count cannot remove a bottleneck outside request scheduling.
Connections stop increasing despite available CPU
Check worker_connections, the number of workers, and the master and worker open-file limits. Remember that proxied connections consume slots too. Raise limits in a coordinated change and verify memory usage.
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Compare the host total with nproc inside the runtime, then inspect container or VM quotas and cpusets. The process’s effective CPU set, not the host inventory, is the relevant capacity.
Reload fails after editing the directive
Run nginx -t to identify the exact file and line. Ensure the directive is at the top level, uses an integer or auto, and is supported by the installed NGINX version. Do not force a reload until the test passes.
Recommended starting configuration
For a current multi-CPU installation, this is a conservative baseline:
worker_processes auto;
error_log /var/log/nginx/error.log warn;
pid /run/nginx.pid;
events {
worker_connections 512;
}The paths are examples; retain the paths used by your distribution. Tune worker_connections and the open-file limit independently from the worker count, then measure under the traffic the server is expected to handle. Keep an explicit worker number only when the evidence or deployment requirements are stronger than the flexibility provided by auto.
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