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Open the application in Coolify, choose Resource Limits, enter CPU and memory values, select Save changes, then redeploy or restart the application. Coolify recreates the containers with the new Docker settings. Confirm the result in Metrics, inspect Runtime Logs, and send representative traffic to check latency and health checks.
What Coolify’s resource limits control
Coolify stores resource settings with an application and translates them into Docker runtime options when it creates the application’s containers. The settings govern how much CPU time and memory a container may use, how Docker prioritizes it during contention, and how it behaves when the host is under pressure.
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Before you choose values
Measure the application’s normal and peak usage
Use the application’s existing Metrics view to observe CPU utilization, peak memory, and swap behavior. Capture traffic that represents real use rather than relying on an idle container. Include startup, background jobs, scheduled tasks, uploads, and any other operations that produce short-lived peaks.
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Leave headroom between the observed peak and the configured ceiling. A value that exactly matches one brief measurement can fail as soon as a request takes longer, several requests arrive together, or a runtime briefly allocates memory for a garbage-collection cycle. The objective is predictable behavior, not the smallest possible number.
Decide whether you need a cap or only a priority
If you need to prevent one application from consuming all available CPU, configure a CPU limit. If several containers should be allowed to use spare CPU but one should receive more attention during contention, use CPU weights. A weight does not reserve processor capacity, so it cannot guarantee a minimum throughput when the host is already saturated.
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Check host capacity first
Limits divide the capacity that already exists; they do not increase it. For an infrastructure decision, compare the host’s available CPU and RAM, storage and network limits, geographic location, reliability, and total cost. When the application’s measured requirement exceeds the current server, resizing or migration is more appropriate than repeatedly raising a container limit.
Set limits in Coolify
- Open the relevant application in the Coolify dashboard.
- Select Resource Limits.
- Enter the CPU and memory settings described in the sections below. Values can be changed independently; leave a setting at its unconfigured value when you do not want that control.
- Select Save changes.
- Redeploy or restart the application. Coolify must recreate the containers for the saved runtime options to take effect.
- Open Metrics and confirm that CPU and memory behavior matches the intended configuration.
- Review Runtime Logs, then send representative traffic and verify response times and health-check results.
Saving the form without a redeploy or restart does not guarantee that an already-running container has been replaced with one carrying the new settings. Treat the recreation and verification steps as part of the change, not as optional cleanup.
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CPU settings explained
| Setting | Accepted value | What it does | Documented default |
|---|---|---|---|
| CPU limit | A whole or decimal number, such as 2 or 0.5 |
Caps the CPU amount available to the container. 0 means no configured limit, allowing use of all CPUs subject to other constraints. |
0 for an unconfigured limit |
| CPU set | CPU numbers or ranges, such as 0-2 or 0,1,3 |
Restricts the container to the listed CPU IDs. | Not configured unless you enter a set |
| CPU weight | A whole number of 0 or greater |
Changes relative priority when containers compete for CPU time; it does not reserve CPU capacity. | 1024 |
CPU limit
Enter a decimal when the application should receive only a fraction of a CPU, or a whole number when it may use multiple CPUs. For example, 0.5 expresses a half-CPU limit and 2 expresses a two-CPU limit. Entering 0 removes the configured cap and allows the container to use all CPUs available to it.
A low cap can make a healthy application appear broken under load: requests take longer, startup work is throttled, and health checks may time out. Increase the limit only after confirming in Metrics that CPU saturation, rather than memory pressure or an application error, is the cause.
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Use a set when placement matters as well as quantity. The range 0-2 selects CPUs 0, 1, and 2; the list 0,1,3 selects those three IDs. A CPU set can isolate a workload from other containers, but it also reduces the CPUs that workload can use. Choose IDs that exist on the host and recheck behavior after a host resize, because the available numbering can change.
CPU weight
The default weight is 1024. During contention, Docker uses weights to decide how to share available CPU time among competing containers. A larger weight gives an application a greater relative priority than a container with a smaller weight; it does not create reserved or guaranteed CPU time. If the host has idle capacity, both containers may still run without an obvious difference.
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Use weights for relative preference, not for a latency or throughput promise. Verify the effect with representative traffic and Metrics rather than assuming that a particular weight produces a fixed percentage of a CPU.
Memory settings and units
Coolify accepts 0 or a number followed by b, k, m, or g. Units are case-insensitive, so values such as 256m and 1g are valid examples. Keep the unit attached to the number and avoid adding explanatory text in the field.
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|---|---|---|
| Memory reservation | A reservation used in Docker’s memory-pressure accounting | It influences how Docker accounts for pressure; it is not the hard maximum. |
| Memory limit | The container’s hard memory cap | Exceeding the cap can cause Docker to terminate a process for running out of memory. |
| Memory and swap limit | The total of memory plus swap available to the container | It governs the combined allowance rather than RAM alone. |
| Swappiness | A value from 0 to 100 |
It controls the container’s tendency to use swap within the configured memory-and-swap policy. |
The documented default for an unconfigured memory limit is 0. Swappiness has a documented default of 60. A value of 0 is accepted in memory fields; interpret each field according to its specific Docker meaning rather than assuming that every zero represents the same behavior.
Choose a hard memory limit
Start with the application’s measured working set and add headroom for normal peaks. The hard limit must cover the process, its runtime, loaded libraries, connection pools, caches, and concurrent requests. If the working set is larger than the cap, Docker can terminate the process instead of allowing it to continue.
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Use a reservation for pressure accounting
A reservation is useful when you want Docker’s pressure accounting to recognize an expected level of memory use, but it does not replace the hard limit. Set it with the distinction in mind: reservation describes pressure expectations, whereas the memory limit determines the ceiling.
Account for swap explicitly
The memory-and-swap limit covers RAM plus swap. It therefore may be larger than the memory limit when swap use is part of the design. Swappiness from 0 through 100 controls how readily the container uses swap under the applicable policy. Monitor swap behavior in Metrics after changing it; a setting that avoids termination can still increase latency if the workload begins swapping heavily.
How CPU and memory choices interact
CPU and memory failures can look similar from the outside: both may produce slow responses, failed health checks, or restarts. Use Metrics to separate them. Sustained CPU saturation with stable memory points toward a CPU limit, CPU set, or weight issue. A rising memory curve, swap activity, or an out-of-memory exit points toward memory sizing.
Changing both resources at once makes diagnosis harder. When possible, adjust one category, redeploy, and observe representative traffic before changing the other. Record the old values so you can restore them if the new configuration causes a regression.
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Health checks deserve special attention. A low CPU limit can leave an application alive but too slow to answer checks before their timeout, resulting in repeated restarts even when memory is adequate. Increase CPU allowance or revise the workload only after Runtime Logs and Metrics show that CPU throttling is the limiting factor.
Verify the change after recreation
- Metrics: Check CPU utilization, memory use, and swap behavior after the new container starts. Look at both steady-state use and peaks produced by representative traffic.
- Runtime Logs: Search for out-of-memory exits, repeated restarts, and health-check failures. Note the time of each event so it can be compared with the traffic pattern and metric peak.
- Representative traffic: Exercise the endpoints and background paths that matter to users. Confirm response times remain acceptable rather than relying only on a successful deployment.
- Headroom: Confirm that the host still has capacity for the application and other services. A container can stay below its own limit while the server as a whole is close to exhaustion.
Verification should cover the busiest expected period, not just the first minute after restart. A configuration that passes an idle check may fail when concurrent requests, scheduled work, or cache warm-up occur.
Troubleshoot common failures
The new value appears to have no effect
- Confirm that you selected Save changes in Resource Limits.
- Redeploy or restart so Coolify recreates the container. Existing containers do not necessarily receive changed runtime options in place.
- Recheck Metrics and Runtime Logs on the newly created container rather than on an older deployment.
The container exits with an out-of-memory event
- Compare the peak working set with the configured memory limit in Metrics.
- Review Runtime Logs for the out-of-memory exit and any restart loop.
- Raise the hard limit only if the host has sufficient RAM, or reduce the application’s working set. If the host cannot provide the required memory, resize or move the resource.
Health checks time out after a CPU change
- Check whether CPU utilization is pinned at the configured limit while checks are running.
- Review Runtime Logs for health-check failures and repeated restarts.
- Increase the CPU limit, broaden an overly restrictive CPU set, or remove an unnecessary cap after confirming that CPU is the bottleneck.
Latency rises after enabling swap
- Inspect swap behavior in Metrics and correlate it with response-time changes.
- Check the memory-and-swap limit and swappiness value together; they control different parts of the policy.
- Prefer enough physical memory for the working set when latency is sensitive, rather than treating swap as equivalent to RAM.
Direct Docker edits disappear
Coolify may recreate a managed container during a redeploy, restart, or other lifecycle action. A manual Docker change made directly to that container can therefore be lost. Put lasting changes in Coolify’s resource settings or in the source Docker Compose file instead.
Coolify settings versus Docker Compose
Coolify’s Resource Limits screen is the appropriate place for application-level CPU and memory controls when the application is managed through the dashboard. If the project is defined by Docker Compose, persistent configuration can also belong in the source Compose file. Keep the source of truth consistent so a later recreation does not undo the intended limits.
Custom Docker Options are limited to supported runtime flags such as --shm-size and --ulimit. Use the dedicated CPU and memory fields when those controls are available instead of trying to encode them as arbitrary custom options. This keeps the settings visible in Coolify and aligned with the application’s lifecycle.
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Resource limits help isolate workloads on a host, but they cannot manufacture CPU cycles or RAM. If measured CPU demand remains above what the current server can supply, or the application’s working set cannot fit with safe headroom, resize the current server or move the resource to a larger server.
Compare candidate infrastructure on the dimensions that affect this workload: available CPU and RAM, storage performance and capacity, network limits, geographic location, reliability, and total cost. After migration, repeat the Metrics, Runtime Logs, and representative-traffic checks because a different host changes the available capacity and may change CPU numbering used by a CPU set.
Quick Recap
A practical decision checklist
- Measure normal and peak CPU, memory, and swap use before changing limits.
- Choose a CPU limit when you need a ceiling; choose CPU weight when you need relative priority during contention.
- Use a CPU set only when restricting processor IDs is an intentional placement decision.
- Enter memory values with an explicit unit such as
256mor1g; units are case-insensitive. - Keep the hard memory limit above the measured working set and leave headroom for peaks.
- Understand reservation, hard limit, memory-plus-swap limit, and swappiness as separate controls.
- Save the settings, redeploy or restart, and verify the recreated container.
- Use Metrics, Runtime Logs, and representative traffic to validate CPU, memory, health checks, restarts, and latency.
- Store lasting configuration in Coolify or the source Compose file, not in ad hoc edits to a managed container.
- Resize or migrate when the host cannot provide the resources the workload actually requires.
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