Cases9 cases

1 to 5 of 9

1. IL-0130 Deployments of large models from Vertex Model Garden failed with "Model server never became ready" in most regions for 13 days after a storage provisioning configuration change

   Google Cloud2024

   Symptoms

   From 22 October 2024 at 14:08 US/Pacific, customers deploying large models, those that need more than 100 GB of disk, through Vertex AI Online Prediction (Vertex Model Garden deployments) had their deployments fail with the error "Model server never became ready".

   Deploys failing

   Trigger

   A recent change introduced an internal storage provisioning configuration error.

   Root cause

   Configuration change

   Component

   –

   Contributing factor

   –

   Detection

   The incident began on 22 October 2024 at 14:08 but was first posted on the status page on 4 November 2024 at 13:17 US/Pacific, about 13 days later. The first post said large Vertex Model Garden deployments (greater than 100GB) on a GKE Autopilot cluster might fail.

   Remediation

   • rolled back the configuration change that introduced the storage provisioning error

   Lessons

   A configuration error that affects only one class of deployments, here models needing more than 100 GB of disk, can stay in place across most regions for almost two weeks. The visible symptom, a model server that never becomes ready, does not point at storage provisioning, and the fix was to roll the configuration back. The report lists no follow-up actions.

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2. IL-0131 A new kind of GenerateContent request made Vertex AI prediction API servers segfault, and once enough of them restarted at the same time the serving fleet could not carry the load

   Google Cloud2024

   Symptoms

   From 12:06 US/Pacific on 12 June 2024, services built on Vertex AI Prediction began reporting failed user requests in eight regions: us-central1, asia-southeast1, europe-west3, europe-west4, us-east1, us-west1, northamerica-northeast1 and us-east4.

   High error rateHigh latencyIntermittent timeouts

   Trigger

   Starting on 8 June 2024, a new form of user request to the GenerateContent API caused intermittent segmentation faults in the Vertex Serving Prediction API servers; on 12 June the rate of such requests increased.

   Root cause

   Software defect

   Component

   Model inference serverCloud load balancer

   Contributing factor

   Partial rolloutNo headroom

   Detection

   Internal production monitoring alerted engineers to the segfaults on 10 June 2024 at 07:35 US/Pacific, before any visible customer impact; on 12 June services built on Vertex Prediction reported failing user requests.

   Remediation

   • confirmed the new failures came from the same segfault found on 10 June
   • accelerated the rollout of the fix that was already in progress, completed at 15:59 US/Pacific

   Action items

   • Ensure early signals of server binary issues are captured in production health analysis and investigated in time
   • Ensure release validation of feature changes and updates in production

   Lessons

   A crash that only some requests trigger can stay invisible while load balancers route around the restarting servers. It becomes an outage when the share of such requests grows until too many servers are restarting at once. Here the cause was known and a fix was rolling out two days before customers were affected, but the progressive rollout had not finished when the triggering traffic increased; Google's follow-up is to investigate early signals of server binary issues in time.

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3. IL-0021 GKE GPU nodes on Container-Optimized OS could not download NVIDIA drivers (403 Forbidden) and came up without working GPUs

   Google Cloud2024

   Symptoms

   From 08:00 US/Pacific on 12 March 2024, GKE GPU nodes running Container-Optimized OS (COS) that were newly created or recreated came up with GPU drivers that did not work, so workloads that used the GPUs could not run. GKE showed elevated errors.

   GPU unavailableNode NotReady

   Root cause

   Dependency failure

   Component

   GPU driverNode operating system imageNode pool

   Contributing factor

   Automation amplification

   Detection

   The report does not say how Google detected the issue. Affected users saw "Failed to download GPU driver installer, status: 403 Forbidden" on the GPU node when installing the driver.

   Remediation

   • Halted automatic node recreations, which attempt GPU driver downloads, until the issue was mitigated
   • Worked with the driver partner to resolve access to the driver download bucket

   Lessons

   The status page report states no lessons or follow-up actions.

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4. IL-0141 gke-metadata-server versions 0.4.272 to 0.4.280 flooded Cloud Logging with "Unable to sync sandbox" debug logs on GKE clusters with Workload Identity, using up logging quota and adding billable usage

   Google Cloud2023

   Symptoms

   Google Kubernetes Engine (GKE) customers with Workload Identity enabled saw a high logging rate. Debug log lines containing the string "Unable to sync sandbox" were ingested into Cloud Logging, used up the Cloud Logging ingestion quota and, beyond the free monthly allotment, produced extra billable usage. Workload Identity is opt-in on GKE Standard and always enabled on GKE Autopilot.

   Log floodHigh latency

   Trigger

   GKE clusters ran gke-metadata-server versions 0.4.272 to 0.4.280, which contained an incorrect configuration that wrote "Unable to sync sandbox" debug logs at a high rate.

   Root cause

   Software defect

   Component

   Credential broker for pods

   Contributing factor

   –

   Detection

   The first status update was posted at 13:32 US/Pacific on 2023-11-02, and the updates told customers how to check a cluster from the version annotation on the gke-metadata-server DaemonSet.

   Remediation

   • rolled out a fix across the GKE fleet so the excess logs were no longer ingested into Cloud Logging
   • offered GKE Rapid channel customers a control plane upgrade to 1.28.2-gke.1157000 or above, or 1.27.7-gke.1038000 or above, as a workaround

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5. IL-0142 GKE clusters on 1.24 and later wrote unexpected fluentbit error entries such as "Failed to get record: decoder: failed to decode payload: EOF" that used up the Logging API write quota for some customers

   Google Cloud2023

   Symptoms

   From 07:13 US/Pacific on 6 July 2023, GKE customers saw unexpected additional error and warning entries in their cluster logs, written to the Cloud Logging project that holds the clusters. Standard and Autopilot clusters at GKE 1.24.x and later were affected.

   Log flood

   Trigger

   Google rolled out a new version of the GKE component that processes logs (preliminary analysis).

   Root cause

   Faulty deployment

   Component

   Telemetry agent

   Contributing factor

   –

   Remediation

   • gave customers a workaround: request a Logging API quota increase, or apply a log exclusion for the fluentbit-gke messages
   • rolled out a fix gradually to the affected clusters between 10 and 18 July 2023

   Lessons

   Log messages written by a managed logging agent count against the customer's own Logging API write quota and logging bill, so a faulty agent release can drop a customer's other logs. A log exclusion on the agent's container name and the message patterns keeps the noise out of storage until a fix arrives.

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