Known issues

Cloud Composer 1 | Cloud Composer 2 | Cloud Composer 3

This page lists known Cloud Composer issues. Some fixes for these issues are in-progress, and will be available in future versions.

Some issues affect older versions, and can be fixed by upgrading your environment.

Non-RFC 1918 address ranges are partially supported for Pods and Services

Cloud Composer depends on GKE to deliver support for non-RFC 1918 addresses for Pods and Services. Currently, only the following list of Non-RFC 1918 ranges is supported in Cloud Composer:

• 100.64.0.0/10
• 192.0.0.0/24
• 192.0.2.0/24
• 192.88.99.0/24
• 198.18.0.0/15
• 198.51.100.0/24
• 203.0.113.0/24
• 240.0.0.0/4

Airflow UI does not show tasks logs when DAG Serialization is on in Composer 1.10.2 and Composer 1.10.3

Enabling DAG serialization in environments using Composer versions 1.10.2 and 1.10.3 prevents logs from showing in the Airflow web server. Upgrade to version 1.10.4 (or later) to fix this issue.

Intermittent Task Failure during Scheduling in Cloud Composer

The issue is seen in a Airflow Scheduler for the task instance during the execution of task. However, the logs do not explain the cause of task failure and Airflow Worker and Airflow Scheduler looked relatively healthy.

The error message on Airflow Scheduler may look like the following error:

Executor reports task instance <TaskInstance: xx.xxxx scheduled__2022-04-21T06:00:00+00:00 [queued]> finished (failed) although the task says its queued. (Info: None) Was the task killed externally?

Or there might be some error on Airflow Worker similar to following error:

Log file is not found: gs://$BUCKET_NAME/logs/$DAG_NAME/$TASK_NAME/2023-01-25T05:01:17.044759+00:00/1.log.
The task might not have been executed or worker executing it might have finished abnormally (e.g. was evicted).

To ensure robustness against such errors stemming from a longstanding issue in Airflow, it is strongly advised to proactively implement appropriate retry strategies at both the task and DAG levels. By incorporating these measures, the system can effectively mitigate the impact of these errors, thereby enhancing the overall reliability and resilience of the workflow.

GKE Workload Identity is not supported

This issue applies only to Cloud Composer 1 environments. Cloud Composer 2 environments use Workload Identity.

You cannot turn on Workload Identity for Cloud Composer environment clusters. As a result, you may see the WORKLOAD_IDENTITY_DISABLED finding in Security Command Center.

Environment labels added during an update are not fully propagated

Updated environment labels are not applied to Compute Engine VMs. As a workaround, those labels can be applied manually.

GKE upgrades in the context of CVE-2020-14386 problem

We are working on addressing the CVE-2020-14386 vulnerability for all Cloud Composer environments. As part of the fix, all existing Cloud Composer's GKE clusters will get updated to a newer version.

Customers that decide to address the vulnerability immediately, can upgrade Composer GKE Cluster by following these instructions with the following considerations:

Step 1. If you're running a Cloud Composer version earlier than 1.7.2 then upgrade to a newer version of Cloud Composer. If you already have version 1.7.2 or later, please, go to the next point.

Step 2. Upgrade GKE cluster (master and nodes) to the latest 1.15 patch version containing the fix for this vulnerability.

Airflow tasks logs are unavailable in the Airflow web server after upgrading from Airflow 1.9.0 to Airflow 1.10.x

Airflow 1.10.x introduced backwards-incompatible changes to the naming convention for log files. Zone information is now added to the log names for Airflow tasks.

Airflow 1.9.0 stores and expects the log names to be in the following format: BUCKET/logs/DAG/2020-03-30T10:29:06/1.log Airflow 1.10.x stores and expects the log names to be in the following format: BUCKET/logs/DAG/2020-03-30T10:29:06+00:00/1.log

As a result, if you upgrade from Airflow 1.9.0 to Airflow 1.10.x and would like to read the log for a task executed with Airflow 1.9.0, the Airflow Web server will show the following error message: Unable to read remote log from BUCKET/logs/DAG/2020-03-30T10:29:06+00:00/1.log

Workaround: Rename the logs generated by Airflow 1.9.0 in the Cloud Storage bucket using the format: BUCKET/logs/DAG/2020-03-30T10:29:06+00:00/1.log

Cannot create Cloud Composer environments with the organization policy constraints/compute.disableSerialPortLogging enforced

Cloud Composer environment creation will fail if constraints/compute.disableSerialPortLogging is enforced on the target project.

Note: This issue only occurs for clusters created before the Cloud Composer November 9th 2020 release. Cloud Composer environments created after November 9th 2020 have all GKE cluster nodes created with serial-logging-enable=false which prevents this issue from occurring.

Diagnosis

To determine if you're impacted by this issue, follow this procedure:

Go the GKE menu in Google Cloud console. Visit the GKE menu

Then, select your newly created cluster. Check for the following error:

Not all instances running in IGM after 123.45s.
Expect <number of desired instances in IGM>. Current errors:

Constraint constraints/compute.disableSerialPortLogging violated for
project <target project number>.

Workarounds:

1. Disable the organization policy on the project where the Cloud Composer environment will be created.

   An organization policy can always be disabled at the project level even if the parent resources (organization or folder) has it enabled. See the Customizing policies for boolean constraints page for more details.

2. Use exclusion filters

   Using an exclusion filter for serial port logs. accomplishes the same goal as the disabling the org policy, as there will be serial console logs in Logging. For more details, see the Exclusion filters page.

Usage of Deployment Manager to manage Google Cloud resources protected by VPC Service Controls

Composer uses Deployment Manager to create components of Cloud Composer environments.

In December 2020, you may have received information that you may need to perform additional VPC Service Controls configuration to be able to use Deployment Manager to manage resources protected by VPC Service Controls.

We would like to clarify that no action is required on your side if you are using Composer and you are not using Deployment Manager directly to manage Google Cloud resources mentioned in the Deployment Manager's announcement.

Cannot delete an environment after its GKE cluster is deleted

If you delete your environment's cluster before the environment itself, then attempts to delete your environment result in the following error:

 Got error "" during CP_DEPLOYMENT_DELETING [Rerunning Task. ]

To delete an environment when its GKE cluster is already deleted:

1. Open the Deployment Manager page in the Google Cloud console.

   Open the Deployment Manager page

2. Find all deployments marked with labels:

   • goog-composer-environment:<environment-name>
   • goog-composer-location:<environment-location>.

   You should see two deployments that are marked with the described labels:

   • A deployment named <environment-location>-<environment-name-prefix>-<hash>-sd
   • A deployment named addons-<uuid>

3. Manually delete resources that are still listed in these two deployments and exist in the project (for example, Pub/Sub topics and subscriptions). To do so:

   1. Select the deployments.

   2. Click Delete.

   3. Select the Delete 2 deployments and all resources created by them, such as VMs, load balancers and disks option and click Delete all.

   The deletion operation fails, but the leftover resources are deleted.

4. Delete the deployments using one of these options:

   • In Google Cloud console, select both deployments again. Click Delete, then select the Delete 2 deployments, but keep resources created by them option.

   • Run a gcloud command to delete the deployments with the ABANDON policy:

     gcloud deployment-manager deployments delete addons-<uuid> \
         --delete-policy=ABANDON
     
     gcloud deployment-manager deployments delete <location>-<env-name-prefix>-<hash>-sd \
         --delete-policy=ABANDON
     

5. Delete your Cloud Composer environment.

Deployment Manager displays information about an unsupported feature

You might see the following warning in the Deployment Manager tab:

The deployment uses actions, which are an unsupported feature. We recommend
that you avoid using actions.

For Deployment Manager's deployments owned by Cloud Composer, you can ignore this warning.

Warnings about duplicate entries of 'echo' task belonging to the 'echo-airflow_monitoring' DAG

You might see the following entry in the Airflow logs:

in _query db.query(q) File "/opt/python3.6/lib/python3.6/site-packages/MySQLdb/
connections.py", line 280, in query _mysql.connection.query(self, query)
_mysql_exceptions.IntegrityError: (1062, "Duplicate entry
'echo-airflow_monitoring-2020-10-20 15:59:40.000000' for key 'PRIMARY'")

You can ignore these log entries, because this error doesn't impact Airflow DAG and task processing.

We work on improving Cloud Composer service to remove these warnings from Airflow logs.

Environment creation fails in projects with Identity-Aware Proxy APIs added to the VPC Service Controls perimeter

Note: This issue affects all versions of Cloud Composer 1 and versions 2.0.* of Cloud Composer 2.

In projects with VPC Service Controls enabled, the [e-mail] account requires explicit access in your security perimeter to create environments.

To create environments, you can use one of the following solutions:

• Do not add Cloud Identity-Aware Proxy API and Identity-Aware Proxy TCP API to the security perimeter.

• Add the [e-mail] service account as the member of your security perimeter by using the following configuration in the YAML conditions file:

   - members:
      - serviceAccount:[e-mail]
  

Cloud Composer 1 environment creation fails when the compute.requireOsLogin policy is enabled

If compute.requireOsLogin policy is set to true in your project, then Cloud Composer 1 v1 environment creation operations fails.

To create Cloud Composer 1 environments, disable this policy in your project.

For more information about this organizational policy, see Organization policy constraints.

Cloud Composer environment creation or upgrade fails when the compute.vmExternalIpAccess is disabled

Cloud Composer-owned GKE clusters configured in the Public IP mode require external connectivity for their VMs. Because of this, the compute.vmExternalIpAccess policy cannot forbid the creation of VMs with external IP addresses. For more information about this organizational policy, see Organization policy constraints.

Note: This remark applies to Cloud Composer 1 and Cloud Composer 2.

Cloud Composer environment creation fails when the compute.vmCanIpForward policy is disabled

Cloud Composer 1 environments created in the non-VPC-Native (using alias IP) mode require this policy to allow the creation of VMs with the enabled "IP Forwarding" feature. For more information about this organizational policy, see Organization policy constraints.

Note: This remark applies only to Cloud Composer 1.

First DAG run for an uploaded DAG file has several failed tasks

When you upload a DAG file, sometimes the first few tasks from the first DAG run for it fail with the Unable to read remote log... error. This problem happens because the DAG file is synchronized between your environment's bucket, Airflow workers, and Airflow schedulers of your environment. These synchronizations are done independently. If the scheduler gets the DAG file and schedules it to be executed by a worker, and if the worker does not have the DAG file yet, then the task execution fails.

As a workaround, Airflow 2 environments in Cloud Composer 1.17.0-preview.9 and later versions are configured to perform two retries for a failed task by default. If a task fails, it is retried twice with 5 minute intervals.

To use the workaround for this problem in Airflow 1, override the core-default_task_retries Airflow configuration option and set it to a number greater than or equal to 2.

Task fails with 'OSError: [Errno 5] Input/output error' in Airflow 1.10.15 or earlier versions

A bug in Airflow 1 versions causes tasks to be put to the Redis queue twice in some rare cases.

Sometimes it can lead to a race condition on the log file, and a subsequent task failure. Tasks fail with OSError: [Errno 5] Input/output error in Cloud Logging and Task is in the 'running' state which is not a valid state for execution. in the task attempt log.

This bug is fixed in Airflow 2. If you encounter this issue in Airflow 1 in a long-running task, increase the value of the [celery_broker_transport_options]visibility_timeout Airflow configuration option (the default value is 604800 for Composer 1.17.0, 21600 for older environments). For short-running tasks, consider adding additional retries to the affected tasks or migrating your environment to Airflow 2.

Dataproc/Dataflow operators fail with Negsignal.SIGSEGV

This is an intermittent issue of grcpio library, when used from a Celery worker. This issue affects Airflow 1.10.14 and later versions.

The workaround is to change the grpcio polling strategy by adding the following environment variable to your environment: GRPC_POLL_STRATEGY=epoll1. This workaround is already applied in Cloud Composer 1.17.1 and later versions.

Announcements about the removal of support for deprecated Beta APIs from GKE versions

Cloud Composer manages underlying Cloud Composer-owned GKE clusters. Unless you explicitly use such APIs in your DAGs and your code, you can ignore announcements about GKE API deprecations. Cloud Composer takes care of any migrations, if necessary.

GKE upgrades in the context of CVE-2021-25741 security issue

All existing Cloud Composer's GKE clusters will be auto-upgraded to newer GKE versions with a fix for the issues described in CVE-2021-25741.

If you want to address this vulnerability immediately, upgrade the GKE cluster of your environment by following the instructions for upgrading a cluster,

• If you have a Cloud Composer 1 environment and GKE version 1.18.x or earlier then upgrade to 1.18.20-gke.4501.

• If you have a Cloud Composer 1 environment and GKE version 1.19.x then upgrade to 1.19.14-gke.301.

• If you have a Cloud Composer 2 environment and GKE version 1.21.x then upgrade to 1.21.4-gke.301.

Cloud Composer should not be impacted by Apache Log4j 2 Vulnerability (CVE-2021-44228)

In response to Apache Log4j 2 Vulnerability (CVE-2021-44228), Cloud Composer has conducted a detailed investigation and we believe that Cloud Composer is not vulnerable to this exploit.

Airflow workers or schedulers might experience issues when accessing the environment's Cloud Storage bucket

Cloud Composer uses gcsfuse to access the /data folder in the environment's bucket and to save Airflow task logs to the /logs directory (if enabled). If gcsfuse is overloaded or the environment's bucket is unavailable, you might experience Airflow task instance failures and see Transport endpoint is not connected errors in Airflow logs.

Solutions:

• Disable saving logs to the environment's bucket. This option is already disabled by default if an environment is created using Cloud Composer 2.8.0 or later versions.
• Upgrade to Cloud Composer 2.8.0 or later version.
• Reduce [celery]worker_concurrency and increase number of Airflow workers instead.
• Reduce the amount of logs produced in DAG's code.
• Follow recommendations and best practices for implementing DAGs and enable task retries.

Airflow UI might sometimes not re-load a plugin once it is changed

If a plugin consists of many files that import other modules, then the Airflow UI might not be able to recognize the fact that a plugin should be re-loaded. In such a case, one needs to trigger a restart of the Airflow webserver. You can do that by adding an environment variable or via installation or uninstallation of PYPI dependencies. You can also restart the Airflow web server.

Intermittent issues when communicating to Airflow Metadata Database

This known issue applies only to Cloud Composer 1.

Some older Cloud Composer 1 environments (1.16.3 or earlier) created before August 12, 2021 might experience transient issues related to communication to Airflow Metadata DBs.

If you experience this issue then in the Airflow tasks logs you will see the following error message:

"Can't connect to MySQL server on 'airflow-sqlproxy-service.default.svc.cluster.local' (104)"

Cloud Composer team works on resolving this problem. In the meantime, if you believe that you are highly impacted by this issue you can do the following to eliminate it:

1. In Google Cloud console, go to the Environment Configuration page of the impacted Cloud Composer environments.
2. Follow the view cluster details link to navigate to the environment's underlying GKE cluster.

3. Navigate to the Nodes tab and click on the default-pool visible in Node Pools section.

   

   Figure 1. default-pool in the list of Node pools (click to enlarge)

4. Click Edit at the top of the page.

5. Change the image type to be Container-Optimized OS with containerd and save the configuration as shown below.

   

   Figure 2. Change Node Pool image type from Docker to containerd (click to enlarge)

6. Once the change is submitted, your default-pool node pool will be reconfigured to use containerd as its container runtime. Some of your Airflow tasks might fail while the node pool is reconfiguring. If those tasks have retries configured, they will be re-run by Airflow once the operation on the node pool has completed.

The environment's cluster has workloads in the Unschedulable state

This known issue applies only to Cloud Composer 2.

In Cloud Composer 2, after an environment is created, several workloads in the environment's cluster remain in the Unschedulable state.

When an environment scales up, new worker pods are created and Kubernetes tries to run them. If there are no free resources available to run them, the worker pods are marked as Unschedulable.

In this situation, the Cluster Autoscaler adds more nodes, which takes a couple of minutes. Until it is done, the pods stay in the Unschedulable state and do not run any tasks.

Unschedulable DaemonSet workloads named composer-gcsfuse and composer-fluentd that are not able to start on nodes where Airflow components are not present do not affect your environment.

If this problem persist for a long time (over 1 hour) then you can check Cluster Autoscaler logs. You can find them in Logs Viewer with the following filter:

resource.type="k8s_cluster"
logName="projects/<project-name>/logs/container.googleapis.com%2Fcluster-autoscaler-visibility"
resource.labels.cluster_name="<cluster-name>"

It contains information about decisions made by the Cluster Autoscaler: expand any noDecisionStatus to see the reason why the cluster cannot be scaled up or down.

Error 504 when accessing the Airflow UI

You can get the 504 Gateway Timeout error when accessing the Airflow UI. This error can have several causes:

• Transient communication issue. In this case, attempt to access the Airflow UI later. You can also restart the Airflow web server.
• (Cloud Composer 2 only) Connectivity issue. If Airflow UI is permanently unavailable, and timeout or 504 errors are generated, make sure that your environment can access *.composer.cloud.google.com. If you use Private Google Access and send traffic over private.googleapis.com Virtual IPs, or VPC Service Controls and send traffic over restricted.googleapis.com Virtual IPs, make sure that your Cloud DNS is configured also for *.composer.cloud.google.com domain names.
• Unresponsive Airflow web server. If the error 504 persists, but you can still access the Airflow UI at certain times, then the Airflow web server might be unresponsive because it's overwhelmed. Attempt to increase the scale and performance parameters of the web server.

Error 502 when accessing Airflow UI

The error 502 Internal server exception indicates that Airflow UI cannot serve incoming requests. This error can have several causes:

• Transient communication issue. Try to access Airflow UI later.

• Failure to start the web server. In order to start, the web server requires configuration files to be synchronized first. Check web server logs for log entries that look similar to: GCS sync exited with 1: gcloud storage cp gs://<bucket-name>/airflow.cfg /home/airflow/gcs/airflow.cfg.tmp or GCS sync exited with 1: gcloud storage cp gs://<bucket-name>/env_var.json.cfg /home/airflow/gcs/env_var.json.tmp. If you see these errors, check if files mentioned in error messages are still present in the environment's bucket.

  In case of their accidental removal (for example, because a retention policy was configured), you can restore them:

  1. Set a new environment variable in your environment. You can use use any variable name and value.

  2. Override an Airflow configuration option. You can use a non-existent Airflow configuration option.

Airflow UI in Airflow 2.2.3 or earlier versions is vulnerable to CVE-2021-45229

As pointed out in CVE-2021-45229, the "Trigger DAG with config" screen was susceptible to XSS attacks through the origin query argument.

Recommendation: Upgrade to the latest Cloud Composer version that supports Airflow 2.2.5.

Workers require more memory than in previous Airflow versions

Symptoms:

• In your Cloud Composer 2 environment, all environment's cluster workloads of Airflow workers are in the CrashLoopBackOff status and don't execute tasks. You can also see OOMKilling warnings that are generated if you are impacted by this issue.

• This issue can prevent environment upgrades.

Cause:

• If you use a custom value for the [celery]worker_concurrency Airflow configuration option and custom memory settings for Airflow workers, you might experience this issue when resource consumption approaches the limit.
• Airflow worker memory requirements in Airflow 2.6.3 with Python 3.11 are 10% higher compared to workers in earlier versions.
• Airflow worker memory requirements in Airflow 2.3 and later versions are 30% higher compared to workers in Airflow 2.2 or Airflow 2.1.

Solutions:

• Remove the override for worker_concurrency, so that Cloud Composer calculates this value automatically.
• If you use a custom value for worker_concurrency, set it to a lower value. You can use the automatically calculated value as a starting point.
• As an alternative, you can increase the amount of memory available to Airflow workers.
• If you can't upgrade your environment to a later version because of this issue, then apply one of the proposed solutions before upgrading.

DAG triggering via private networks using Cloud Run functions

Triggering DAGs with Cloud Run functions via private networks with the use of VPC Connector is not supported by Cloud Composer.

Recommendation: Use Cloud Run functions to publish messages on Pub/Sub. Such events can actuate Pub/Sub Sensors to trigger Airflow DAGs or implement an approach based on deferrable operators.

Problem with gcloud composer commands in 410.0.0 version

In the 410.0.0 version of gcloud, the following Cloud Composer commands:

• gcloud composer environments run
• gcloud composer environments list-packages

return a non-zero error code and display this error message:

  (ERROR: gcloud crashed (TypeError): 'NoneType' object is not callable)

This behaviour occurs in addition to regular output produced by the gcloud commands and doesn't impact their functionality.

If this issue doesn't affect your operations, you can continue using the 410.0.0 version and ignore the incorrect error message. If you need to use 410.0.0 version and you use gcloud command in a programmatic way then, please, implement additional logic to ignore non-zero error code and info about the error stacktrace in the output. You can also take a look at the Solution section for any other workarounds.

Solution

• Refrain from upgrading to the 410.0.0 version. Use the 409.0.0 version or earlier.
• If already upgraded, please downgrade to a previous version (for example 409.0.0). For more information, see Using versioned archives.

Empty folders in Scheduler and Workers

Cloud Composer does not actively remove empty folders from Airflow workers and schedulers. Such entities might be created as a result of the environment bucket synchronization process when these folders existed in the bucket and were eventually removed.

Recommendation: Adjust your DAGs so they are prepared to skip such empty folders.

Such entities are eventually removed from local storages of Airflow schedulers and workers when these components are restarted (e.g., as a result of scaling down or maintenance operations in Cloud Composer cluster).

Support for Kerberos

Cloud Composer does not support Airflow Kerberos configuration yet.

Support for compute classes in Cloud Composer 2

Cloud Composer 2 supports only general-purpose compute class. It means that running Pods that request other compute classes (such as Balanced or Scale-Out) is not possible.

The general-purpose class allows for running Pods requesting up to 110 GB of memory and up to 30 CPU (as described in Compute Class Max Requests.

If you want to use ARM-based architecture or require more CPU and Memory, then you must use a different compute class, which is not supported within Cloud Composer 2 clusters.

Recommendation: Use GKEStartPodOperator to run Kubernetes Pods on a different cluster that supports the selected compute class. If you run custom Pods requiring a different compute class, then they also must run on a non-Cloud Composer 2 cluster.

Support for Google Campaign Manager 360 Operators

Google Campaign Manager Operators in Cloud Composer versions earlier than 2.1.13 are based on the Campaign Manager 360 v3.5 API that is deprecated and its sunset date is May 1, 2023.

If you use Google Campaign Manager operators, then upgrade your environment to Cloud Composer version 2.1.13 or later.

Support for Google Display and Video 360 Operators

Google Display and Video 360 Operators in Cloud Composer versions earlier than 2.1.13 are based on the Display and Video 360 v1.1 API that is deprecated and its sunset date is April 27, 2023.

If you use Google Display and Video 360 operators, then upgrade your environment to Cloud Composer version 2.1.13 or later. In addition to that, you might need to change your DAGs because because some of the Google Display and Video 360 operators are deprecated and replaced with new ones.

• GoogleDisplayVideo360CreateReportOperator is now deprecated. Instead, use GoogleDisplayVideo360CreateQueryOperator. This operator returns query_id instead of report_id.
• GoogleDisplayVideo360RunReportOperator is now deprecated. Instead, use GoogleDisplayVideo360RunQueryOperator. This operator returns query_id and report_id instead of only report_id, and requires query_id instead of report_id as a parameter.
• To check if a report is ready, use the new GoogleDisplayVideo360RunQuerySensor sensor that uses query_id and report_id parameters. The deprecated GoogleDisplayVideo360ReportSensor sensor required only report_id.
• GoogleDisplayVideo360DownloadReportV2Operator now requires both query_id and report_id parameters.
• In GoogleDisplayVideo360DeleteReportOperator there are no changes that can affect your DAGs.

Secondary Range name restrictions

Note: The gke-.*-(pods|services)-.* naming convention is reserved for auto-created GKE cluster secondary ranges. You can't use secondary range names in this format while creating Composer instances.

CVE-2023-29247 (Task instance details page in the UI is vulnerable to a stored XSS)

Airflow UI in Airflow versions from 2.0.x to 2.5.x is vulnerable to CVE-2023-29247.

Note: Cloud Composer version 2.4.2 fixes this issue in Airflow versions 2.4.3 and 2.5.3. We recommend to update your environment to Cloud Composer 2.4.2 or later version. This issue does not affect Airflow 2.6.x and later versions.

If you use an earlier version of Cloud Composer than 2.4.2 and suspect that your environment might be vulnerable to the exploit, please read the following description and possible solutions.

In Cloud Composer, access to the Airflow UI is protected with IAM and Airflow UI access control.

This means that in order to exploit the Airflow UI vulnerability, attackers first need to gain access to your project along with the necessary IAM permissions and roles.

Solution:

• Verify IAM permissions and roles in your project, including Cloud Composer roles assigned to individual users. Make sure that only approved users can access Airflow UI.

• Verify roles assigned to users through the Airflow UI access control mechanism (this is a separate mechanism that provides more granular access to Airflow UI). Make sure that only approved users can access Airflow UI and that all new users are registered with a proper role.

• Consider additional hardening with VPC Service Controls.

Cloud Composer 2 Composer environment's airflow monitoring DAG is not re-created after deletion

The airflow monitoring DAG is not automatically re-created if deleted by the user or moved from the bucket in composer environments with composer-2.1.4-airflow-2.4.3.

Solution:

• This has been fixed in later versions like composer-2.4.2-airflow-2.5.3. The suggested approach is to upgrade your environment to a newer version.
• An alternative or temporary workaround to an environment upgrade would be, to copy the airflow_monitoring DAG from another environment with the same version.

Note: Do not delete the monitoring DAG, it is used by Cloud Composer to monitor the health of your environment.

Upgrade operations might fail if Sentry is enabled

The upgrade operation for a Cloud Composer environment might fail if you configured Sentry in your environment and set the [sentry]sentry_on setting to true.

Solution:

• Turn off Sentry in your environment, perform the upgrade, and configure Sentry again.

It's not possible to reduce Cloud SQL storage

Cloud Composer uses Cloud SQL to run Airflow database. Over time, disk storage for the Cloud SQL instance might grow because the disk is scaled up to fit the data stored by Cloud SQL operations when Airflow database grows.

It's not possible to scale down the Cloud SQL disk size.

As a workaround, if you want to use the smallest Cloud SQL disk size, you can re-create Cloud Composer environments with snapshots.

Database Disk usage metric doesn't shrink after removing records from Cloud SQL

Relational databases, such as Postgres or MySQL, don't physically remove rows when they're deleted or updated. Instead, it marks them as "dead tuples" to maintain data consistency and avoid blocking concurrent transactions.

Both MySQL and Postgres implement mechanisms of reclaiming space after deleted records.

While it's possible to force the database to reclaim unused disk space, this is a resource hungry operation which additionally locks the database making Cloud Composer unavailable. Therefore it's recommended to rely on the building mechanisms for reclaiming the unused space.

Access blocked: Authorization Error

If this issue affects a user, the Access blocked: Authorization Error dialog contains the Error 400: admin_policy_enforced message.

If the API Controls > Unconfigured third-party apps > Don't allow users to access any third-party apps option is enabled in Google Workspace and the Apache Airflow in Cloud Composer app is not explicitly allowed, users are not able to access the Airflow UI unless they explicitly allow the application.

To allow access, perform steps provided in Allow access to Airflow UI in Google Workspace.

Task instances that succeeded in the past marked as FAILED

In some circumstances and rare scenarios, Airflow task instances that succeeded in the past can be marked as FAILED.

If it happens, usually it was either triggered by an environment update or upgrade operation, or by GKE maintenance.

Note: the issue itself doesn't indicate any problem in the environment and it doesn't cause any actual failures in task execution.

The issue is fixed in Cloud Composer version 2.6.5 or later.

Airflow components have problems when communicating to other parts of Cloud Composer configuration

In very rare cases, the slowness of communication to Compute Engine Metadata server might lead to Airflow components not working optimally. For example, the Airflow scheduler might be restarted, Airflow tasks might need to be re-tried or task startup time might be longer.

Symptoms:

The following errors appear in Airflow components' logs (such as Airflow schedulers, workers or the web server):

Authentication failed using Compute Engine authentication due to unavailable metadata server

Compute Engine Metadata server unavailable on attempt 1 of 3. Reason: timed out
...
Compute Engine Metadata server unavailable on attempt 2 of 3. Reason: timed out
...
Compute Engine Metadata server unavailable on attempt 3 of 3. Reason: timed out

Solution:

Set the following environment variable: GCE_METADATA_TIMEOUT=30.

The /data folder is not available in Airflow web server

In Cloud Composer 2, the Airflow web server is meant to be mostly read-only component and Cloud Composer does not synchronize the data/ folder to this component.

Sometimes, you might want to share common files between all Airflow components, including the Airflow web server.

Solution:

• Wrap the files to be shared with the web server into a PYPI module and install it as a regular PYPI package. After the PYPI module is installed in the environment, the files are added to the images of Airflow components and are available to them.

• Add files to the plugins/ folder. This folder is synchronized to the Airflow web server.

Non-continuous DAG parse times and DAG bag size diagrams in monitoring

Non-continuous DAG parse times and DAG bag size diagrams on the monitoring dashboard indicate problems with long DAG parse times (more than 5 minutes).

Figure 3. Non-continuous DAG parse times and DAG bag size graphs (click to enlarge)

Solution: We recommend keeping total DAG parse time under 5 minutes. To reduce DAG parsing time, follow DAG writing guidelines.

Task logs appear with delays

This known issue applies to Cloud Composer 3.

Symptom:

• In Cloud Composer 3, Airflow task logs do not appear immediately and are delayed for a few minutes.

Cause:

If your environment runs a large number of tasks at the same time, task logs can be delayed because the environment's infrastructure size is not enough to process all logs fast enough.

Solutions:

• Consider increasing the environment's infrastructure size to increase performance.
• Distribute DAG runs over time, so that tasks are not executed at the same time.

What's next

• Troubleshooting environment creation
• Troubleshooting DAGs
• Troubleshooting Airflow scheduler issues