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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallA Docker build that dies on a VPS is usually a host-resource, daemon, storage, or builder problem—not a mysterious Dockerfile failure. Start by confirming the daemon endpoint, read its logs, then check host memory, swap, Docker’s data filesystem, the selected BuildKit builder, and kernel or daemon configuration. The error you saw determines which branch to follow.
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Start with a five-minute triage
Do not rewrite the Dockerfile before collecting evidence. A build can fail because the Docker daemon stopped, the kernel killed a process, the filesystem holding Docker data filled up, or BuildKit is using a different builder than you expected. Run the following commands from the VPS and save their output with the failed build’s timestamp.
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docker info
sudo systemctl is-active docker
sudo systemctl status docker --no-pager
printf 'DOCKER_HOST=%sn' "$DOCKER_HOST"
docker buildx lsdocker info confirms that the client can reach a daemon and shows the Docker root directory, storage driver, server architecture, and available resources. systemctl is-active gives a quick running or stopped result; status often includes the latest startup error. An unexpected DOCKER_HOST value can point the client at a remote or unreachable endpoint instead of the local socket. If you normally use a Docker context, list and inspect it as well:
docker context ls
docker context showIf the daemon is inactive, do not keep retrying the build. Continue with the log procedure below; the startup failure is the primary problem.
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Read the daemon and kernel logs before changing settings
Docker’s documentation notes that daemon logs can diagnose failures that the build output reduces to a generic EOF or connection error. On a systemd-based Linux VPS, inspect the service journal around the failure:
sudo journalctl -xu docker.service --since '30 minutes ago'
sudo journalctl -k --since '30 minutes ago'On distributions that also write traditional logs, check /var/log/syslog or /var/log/messages. Search for the exact build time and terms such as oom, killed process, no space left on device, overlay, failed to start, panic, and EOF. A kernel message is especially important: the shell may only report that a command exited, while the kernel records which process it killed.
If normal daemon logging is insufficient, enable Docker debug logging carefully. Edit /etc/docker/daemon.json and add the JSON key debug with a Boolean value of true, preserving valid JSON and any existing settings. Then reload or restart Docker according to the distribution’s service policy and capture the resulting journal. Turn debug logging back off after diagnosis if the extra volume is not needed.
sudo systemctl reload docker
sudo journalctl -u docker.service -n 200 --no-pagerIf a reload is unsupported or the configuration is rejected, use a controlled restart only after checking the file syntax and confirming that stopping the daemon will not interrupt production containers.
Diagnose memory exhaustion and OOM kills
A small VPS can run out of RAM during a compiler, linker, package installation, or image-compression step even when the final container is small. Docker states that when containers attempt to use more memory than the system has available, an out-of-memory exception can occur and the kernel OOM killer may stop either a container or the Docker daemon. That is why a build may appear to lose its connection halfway through.
Confirm that the host, not just a build container, ran out of memory
free -h
swapon --show
sudo dmesg -T | grep -i -E 'oom|killed process|out of memory'
sudo journalctl -k | grep -i -E 'oom|killed process|out of memory'Look at the available memory value, not merely the amount labeled free. An empty swapon --show result means the host has no active swap; adding swap can provide emergency headroom, but it is slower than RAM and does not make an undersized machine suitable for sustained parallel compilation. Some VPS providers prohibit or discourage swap, so follow the provider’s policy before creating it.
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Check whether other services consumed the missing memory. Databases, game servers, monitoring agents, and multiple simultaneously running containers compete with the build for the same host pool. Stop nonessential services for the build window or move the build to an isolated runner rather than relying on a fragile margin.
Reduce peak memory during the build
- Run one expensive compilation or asset step at a time instead of launching several independent jobs.
- Limit compiler parallelism with the build system’s job option; a high CPU count does not mean the VPS has enough RAM for that many workers.
- Do not start the full application stack, databases, or test services while the image is compiling unless the build genuinely needs them.
- Use a multi-stage Dockerfile so toolchains and intermediate artifacts do not remain in the final image; this reduces storage and transfer size, although it does not automatically lower the peak memory of a single compile.
- For repeatable heavy builds, resize the VPS or use a dedicated builder with more memory rather than repeatedly retrying the same workload.
A container-level memory limit can make a failure look deterministic, but the kernel log still decides whether the host OOM killer was involved. Check the build command, Compose configuration, and any CI runner limits for values that are lower than the VPS capacity.
Find and clear Docker data or inode exhaustion
The message no space left on device can mean ordinary bytes are exhausted, inodes are exhausted, or a temporary filesystem used by a layer has filled. Check all three views:
df -h
df -i
docker system df
docker info --format '{{.DockerRootDir}}'
DOCKER_ROOT=$(docker info --format '{{.DockerRootDir}}')
df -h "$DOCKER_ROOT"
df -i "$DOCKER_ROOT"Docker commonly stores images, writable layers, and BuildKit data below /var/lib/docker, but the root can be configured elsewhere. The filesystem that contains that directory—not necessarily the filesystem where your source checkout lives—is the one that must have free capacity. Inode exhaustion is common on systems with enormous numbers of small files and can occur while gigabytes remain available.
Prune only data you understand
docker system df separates images, containers, local volumes, and build cache and shows reclaimable space. Remove stopped containers, unused networks, dangling images, or old cache only after confirming that no deployment or rollback depends on them. Build cache can be inspected and pruned separately:
docker builder du
docker builder pruneThe interactive confirmation is a safety boundary. A broad command such as docker system prune can remove more than a build cache; read its prompt and options before accepting. Never delete a volume merely because it is large unless you have verified that its data is disposable and backed up.
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Configure BuildKit garbage collection for a small disk
BuildKit retains reusable layers so later builds are faster, but a small VPS can accumulate cache faster than it can be reclaimed. Docker’s current documentation describes default garbage-collection thresholds of reservedSpace: 10% of total disk or 10 GB, whichever is lower, and maxUsedSpace: 60% of total disk or 100 GB, whichever is lower (Docker documentation, 2026). These are disk thresholds, not guarantees that a build will always fit.
Set cache age and disk limits appropriate to your workload through the builder configuration, then monitor the result with docker builder du and df. A short cache lifetime lowers storage pressure but causes more downloads and recompilation. A long-lived cache speeds recurring builds but requires more persistent disk. Change one policy at a time and observe whether the next build reaches the intended cache behavior.
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BuildKit is not simply a faster version of the legacy builder. It can skip unused stages, avoid sending ignored context files, execute independent operations in parallel, and manage a content-addressed cache. Those optimizations can reduce total work, but parallel execution can raise peak memory and a large context can consume disk before the first instruction runs.
Make the build context small
Create a precise .dockerignore beside the Dockerfile. Exclude source-control metadata, local dependency directories, build outputs, test recordings, logs, virtual environments, and other files that are not required by any COPY or ADD instruction. Review exceptions carefully: excluding a generated file that a build needs causes a missing-file error, while sending a multi-gigabyte directory increases upload time and temporary storage use.
Build from the smallest practical directory and specify the Dockerfile explicitly when several are present:
docker build --file Dockerfile --tag example:diagnostic .Inspect the early build output for the context-transfer size. A context that is unexpectedly large is a design defect even if the current VPS happens to survive it.
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Use multi-stage builds deliberately
Keep compilers, package managers, and test tools in a builder stage, then copy only runtime artifacts into the final stage. This reduces the resulting image and the amount transferred to production. It does not eliminate the builder stage’s peak RAM or cache use, so pair it with controlled parallelism and cache limits when the compilation itself is the failing operation.
Split exceptionally large operations
A single RUN instruction that downloads dependencies, compiles a project, creates assets, and compresses them can have a large peak working set and produces little diagnostic separation. Where practical, split independent work into clear stages so logs identify the failing operation and BuildKit can reuse successful layers. Do not split commands solely to create dozens of tiny layers; each layer has metadata and storage overhead.
Verify the builder, endpoint, and target architecture
The default docker build builder uses the BuildKit library bundled with the Docker daemon. docker buildx build may use a configured alternative builder, with its own endpoint, workers, cache, and platform capabilities. A build that works on one machine can therefore fail on a VPS because it is using a different builder than expected.
docker buildx ls
docker buildx inspect --bootstrapIn the output, identify the selected builder, its driver, endpoint, worker status, supported platforms, and whether bootstrap completed successfully. If the builder is stopped, points at an unreachable host, or reports a worker for a different architecture, fix that selection before changing application code.
Native versus emulated builds
Check the VPS architecture with uname -m and compare it with the image platform you request. A native build generally has the most predictable performance. Cross-architecture builds that execute foreign binaries through emulation need additional memory and can be much slower; a heavy ARM-on-AMD64 or AMD64-on-ARM compile can exhaust a small machine even when a native build succeeds.
uname -m
docker buildx inspect --bootstrap
docker buildx build --platform linux/amd64 --tag example:diagnostic .Use the platform flag only when you need that target, and ensure the selected worker actually supports it. For regular multi-platform releases, a dedicated or remote builder with native workers can isolate emulation overhead from the production VPS. That adds network and CI configuration, so document credentials, cache location, and failure recovery before switching.
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Repair daemon configuration and kernel conflicts
Duplicate host settings
A daemon that refuses to start immediately after editing daemon.json often has a configuration conflict rather than a corrupted image. Docker documents a common case in which the hosts directive is supplied both in /etc/docker/daemon.json and as a dockerd command-line flag from the systemd unit. Remove the duplicate according to the unit’s configuration, validate the remaining setting, and then reload systemd:
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sudo systemctl daemon-reload
sudo systemctl restart docker
sudo systemctl status docker --no-pagerDo not expose a TCP daemon socket merely to work around a local client error. A remote Docker socket is a high-impact control interface; use the distribution’s documented, authenticated transport and firewall policy if remote administration is required.
Kernel and module compatibility
Docker relies on kernel features and modules for namespaces, cgroups, overlay filesystems, networking, and storage. Older or incompatible kernels, missing modules, or provider restrictions can produce storage-driver errors, networking failures, or daemon startup problems. Record the kernel and storage details from uname -a and docker info, then compare them with the Docker release and the VPS image’s supported configuration. Updating the kernel or changing storage drivers is an infrastructure change: schedule it, back up data, and verify that existing images and containers remain usable.
Use the error message as a decision map
| Observed symptom | Most likely branch | First evidence to collect |
|---|---|---|
| Cannot connect to the Docker daemon | Stopped service, wrong DOCKER_HOST, unreachable remote context, or daemon startup failure |
docker info, service status, context listing, and daemon journal |
OOMKilled, kernel out-of-memory messages, or abrupt death during a heavy RUN |
Host memory pressure or a lower container/runner limit | free -h, swapon --show, kernel journal, and active processes |
no space left on device |
Docker-data bytes, temporary space, inode exhaustion, or BuildKit cache growth | df -h, df -i, Docker root path, and docker system df |
| Hang, EOF, or failure only during ARM/AMD64 cross-builds | Unbootstrapped or wrong buildx worker, unreachable endpoint, or emulation memory pressure | docker buildx ls, docker buildx inspect --bootstrap, platform and architecture output |
| Daemon will not start after a JSON edit | Invalid JSON, duplicate flags, especially a second hosts setting, or unsupported kernel configuration |
Systemd unit, daemon journal, and the last configuration change |
Apply the least disruptive fix that matches the evidence
- Capture the failure. Record the command, image tag, target platform, start time, and the last 100–200 lines of build and daemon output. This prevents a cleanup action from erasing the clue.
- Restore daemon reachability. If the service is stopped, fix the startup error shown in the journal. If the service is healthy, correct the Docker context or
DOCKER_HOSTrather than restarting blindly. - Relieve confirmed memory pressure. Stop nonessential workloads, lower build concurrency, and use provider-approved swap if appropriate. If the same step still reaches the kernel OOM killer, move it to a larger or isolated builder.
- Relieve confirmed disk pressure. Identify the full mount and inode count, remove only verified-unused images, stopped containers, and cache, then set BuildKit thresholds or expand the Docker-data disk.
- Correct the builder and platform. Bootstrap the intended buildx builder, select a worker that supports the target, and avoid emulation for routine builds when a native worker is available.
- Reduce future demand. Tighten
.dockerignore, use multi-stage output, split oversized operations where useful, and schedule cache maintenance. - Rebuild once with observability. Run the same command while watching
free -h,df -h, and the daemon journal. A successful retry after a targeted change confirms the branch; a different failure should be diagnosed afresh.
Choose a remedy by operating constraint
| Remedy | Memory headroom | Docker-data disk | Architecture | Cache persistence | Operational control | Infrastructure cost |
|---|---|---|---|---|---|---|
| Reduce parallelism and prune verified-unused cache | May lower peak use; does not add RAM | Recovers existing space | No change | Less persistent cache | Simple but recurring maintenance | Low |
| Configure age and disk thresholds | No direct change | Prevents unbounded cache growth | No change | Predictable, potentially colder cache | Requires monitoring and tuning | Low |
| Resize VPS RAM or add approved swap | Adds headroom; swap is slower | No change unless the plan includes disk | Usually unchanged | Cache can remain local | Few moving parts after resize | Recurring capacity cost |
| Expand the Docker-data volume | No direct change | Adds durable space and inodes | No change | More cache can persist | Simple after migration or volume change | Recurring storage cost |
| Use a dedicated or remote builder | Moves peak demand away from production | Moves or separates cache | Can provide native workers | Depends on builder retention and network | More CI, access, and network configuration | Builder and transfer cost |
Pruning and cache policy are sensible when failures are occasional and the VPS has adequate headroom. Resizing is operationally simpler when the workload is stable and the provider can add capacity. A separate builder is justified when production availability, cross-architecture output, or sustained compilation makes resource contention unacceptable.
Prevent the next crash
Set a capacity baseline
Measure a normal build’s peak resident memory, duration, context size, Docker-data growth, and cache-reclaimable amount. Keep a margin for the VPS’s ordinary services; a build that consumes every available megabyte is already an outage risk. Repeat the measurement after changing compiler parallelism, target platforms, or dependency versions.
Make cleanup intentional
Schedule inspection rather than blind deletion. Alert on both byte and inode utilization for the mount containing Docker’s root directory. Track cache age and reclaimable size, and document which images, volumes, and stopped containers are safe to remove. A cleanup policy that nobody can explain is not a recovery plan.
Separate production from compilation
Running builds on the same VPS as a live service couples deploy activity to customer traffic, databases, and logs. If builds regularly approach the machine’s memory or disk limits, isolate them on a larger builder and publish the resulting image to the deployment workflow. Keep the builder’s credentials, network access, cache retention, and platform support explicit so a remote endpoint does not become the next single point of failure.
Verify that the fix held
sudo systemctl is-active dockerreports an active daemon after the change.docker infocompletes without a connection or storage-driver error.docker buildx inspect --bootstrapshows the intended worker and target platform.- The Docker-data mount has both byte and inode headroom before the build begins.
- Kernel and daemon logs contain no new OOM, filesystem, or startup errors during the build.
- The image is tagged and inspectable, and the build did not depend on an accidentally deleted volume or an unreachable remote context.
Once those checks pass, rerun the original command without unrelated Dockerfile changes. If it fails again, the new timestamp and resource readings will identify whether the remaining constraint is memory, storage, architecture, or daemon configuration instead of leaving you with another unexplained crash.
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