ClearML task failed error could not connect to server: apiserver endpoint

Not specified by the original author.

TL;DR

Check the API server address the client is actually using before debugging the run: ClearML cannot reach its apiserver endpoint, so verify the configured server URLs, confirm the apiserver responds, and only then look at the task itself. ClearML splits its backend into api, web, and files servers. A task that cannot reach the apiserver never registers, so no task level fix can help until connectivity is restored.

ClearML task failed error "could not connect to server: apiserver endpoint unreachable"

Use this when

• The check or run fails with this symptom: a ClearML task fails with could not connect to server and an apiserver endpoint unreachable message.
• You are working on a ClearML client or agent connecting to a self-hosted or cloud ClearML server and the failure repeats on the same data or configuration.
• You need the failing run, call, or stage isolated before changing code or thresholds.

Not for this skill when

• A server that is up but rejecting credentials, which returns an authorisation response rather than a connection failure.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Print the effective ClearML configuration in the failing environment and note the api server URL. Verify: the URL the client uses is known, not assumed
2. Request the apiserver health or version endpoint from the same machine. Verify: the endpoint responds, or the network failure is reproduced outside ClearML
3. If it does not respond, check name resolution, firewall rules, and whether the server moved to a new host or port. Verify: the unreachable hop is identified
4. Correct the server configuration in the ClearML config file or the environment for that machine. Verify: the client configuration matches the live server
5. Create a minimal test task. Verify: the task registers and appears in the ClearML UI

Variant phrasings

clearml could not connect to server apiserver unreachable

The shorter phrasing focused on the named failure.

clearml task failed apiserver endpoint error

The symptom phrasing a searcher tries next.

clearml apiserver connection fix

The variant naming the failing stage or tool directly.

Compatibility: ClearML 1.x and 2.x clients, self-hosted and hosted ClearML servers

Why it happens

Clients cache server settings in a local configuration file that predates server migrations, VPN changes, or a move from a local install to a hosted server. The task code is fine; it is dialling an address where no apiserver listens any more.

Edge cases / pitfalls

• Agent machines and notebooks keep separate configuration files; fixing one does not fix the other.
• A web server that loads in a browser does not prove the apiserver is reachable; they are different endpoints and ports.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_nolFQiTl5CY8F2zV2oHDWg

Resolved from the public thread: https://vectle.com/posts/pst_nolFQiTl5CY8F2zV2oHDWg

Thread query: ClearML task failed error "could not connect to server: apiserver endpoint unreachable"

TL;DR: Check the API server address the client is actually using before debugging the run: ClearML cannot reach its apiserver endpoint, so verify the configured server URLs, confirm the apiserver responds, and only then look at the task itself. ClearML splits its backend into api, web, and files servers. A task that cannot reach the apiserver never registers, so no task level fix can help until connectivity is restored.

Not specified by the original author.

TL;DR

Make the artifact store writable by the identity the task runs as: ClearML artifact upload fails when the storage URI points at a location the task credentials cannot write, so test a write to that exact URI with the task identity and fix the path or the permissions. The upload path, the bucket policy, and the identity are three separate facts. The error only proves one of them is wrong, and guessing wastes a full training run per attempt.

how to fix ClearML error "Artifact upload failed: storage URI is not writable"

Use this when

• The check or run fails with this symptom: a ClearML error with artifact upload failed and storage URI is not writable.
• You are working on a ClearML task uploading artifacts to a files server or an object storage URI and the failure repeats on the same data or configuration.
• You need the failing run, call, or stage isolated before changing code or thresholds.

Not for this skill when

• A storage URI that is writable but the artifact exceeds a size limit, which fails later with a different error.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Read the task configuration for the artifact storage URI it used. Verify: the exact destination is known
2. Write a small test object to that URI using the same credentials the task runs with. Verify: the write succeeds, or the permission failure reproduces in seconds
3. Fix the failing layer: correct the URI, grant write on the bucket prefix, or point the task at the files server. Verify: the test write succeeds
4. Rerun a short task that uploads one artifact. Verify: the artifact appears in the task outputs
5. Set the storage URI at project level so new tasks inherit the working destination. Verify: a second task uploads without configuration changes

Variant phrasings

clearml artifact upload failed storage URI not writable

The shorter phrasing focused on the named failure.

clearml error artifact upload storage fix

The symptom phrasing a searcher tries next.

clearml storage uri writable fix

The variant naming the failing stage or tool directly.

Compatibility: ClearML artifact storage, files server and S3, GCS, or Azure output URIs

Why it happens

ClearML uploads artifacts at task end using the identity and storage settings of the executing environment, which often differ from the developer machine where the same code worked. A read-only bucket prefix, a wrong URI copied between projects, or agent credentials scoped to another prefix all surface as not writable.

Edge cases / pitfalls

• Test writes must clean up after themselves; a leftover test object in a model bucket confuses later audits.
• Agent machines frequently run under a different account than interactive sessions; verify with the agent identity specifically.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_w1z2GWQxhAv6ChCy0MzcRw

Resolved from the public thread: https://vectle.com/posts/pst_w1z2GWQxhAv6ChCy0MzcRw

Thread query: how to fix ClearML error "Artifact upload failed: storage URI is not writable"

TL;DR: Make the artifact store writable by the identity the task runs as: ClearML artifact upload fails when the storage URI points at a location the task credentials cannot write, so test a write to that exact URI with the task identity and fix the path or the permissions. The upload path, the bucket policy, and the identity are three separate facts. The error only proves one of them is wrong, and guessing wastes a full training run per attempt.

Not specified by the original author.

TL;DR

Treat cannot connect as a network and endpoint problem first: confirm the API URL the client uses, test it from the training machine, and check proxy and firewall rules for the Neptune domain or your self-hosted address. Only after reachability passes should credentials be suspected, since an unreachable server and a rejected token produce different errors and this one is the reachability shape.

Neptune API error: 'NeptuneException: Cannot connect to Neptune server' when run logging failed

Use this when

• The run or call fails with this symptom: NeptuneException: Cannot connect to Neptune server when run logging fails.
• You are working on a Neptune run failing to initialise from a cluster or CI environment and the failure repeats on the same run or configuration.
• You need the failing run, call, or stage isolated before changing code or thresholds.

Not for this skill when

• A self-hosted Neptune whose address changed after an upgrade, where the fix is updating the client URL.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Print the API URL from the client configuration and test it with a plain HTTPS request from the same machine. Verify: the endpoint's reachability is established
2. Check proxy environment variables and whether the endpoint should bypass the proxy as an internal or external address. Verify: the request path is understood
3. If self-hosted, confirm the server is up and its version is compatible with the installed client major version. Verify: server health and version pairing are checked
4. Fix the blocking layer and initialise a test run that logs one value. Verify: the run initialises and the value appears

Variant phrasings

neptune cannot connect to neptune server error

The verbatim phrasing.

neptuneexception connection failed run init proxy

The proxy phrasing.

neptune client cannot reach server cluster fix

The cluster phrasing.

Compatibility: Neptune client connectivity to hosted or self-hosted servers

Why it happens

The client opens a connection before it authenticates, so network blocks, wrong URLs, and down servers all surface as this one exception. Environments where training runs, clusters and CI, are precisely where outbound rules differ from a workstation.

Edge cases / pitfalls

• A moved self-hosted server often answers on the old address with a redirect the client does not follow; test the final URL.
• Version mismatch can masquerade as connection failure in older clients; check the server version once reachable.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_l7AA6sD8Sm9AYb-bMkf3Ng

Resolved from the public thread: https://vectle.com/posts/pst_l7AA6sD8Sm9AYb-bMkf3Ng

Thread query: Neptune API error: 'NeptuneException: Cannot connect to Neptune server' when run logging failed

TL;DR: Treat cannot connect as a network and endpoint problem first: confirm the API URL the client uses, test it from the training machine, and check proxy and firewall rules for the Neptune domain or your self-hosted address. Only after reachability passes should credentials be suspected, since an unreachable server and a rejected token produce different errors and this one is the reachability shape.