Pada 15 September 2026, semua lingkungan Cloud Composer 1 dan Cloud Composer 2 versi 2.0.x akan mencapai akhir masa pakainya yang direncanakan, dan Anda tidak akan dapat menggunakannya. Sebaiknya rencanakan migrasi ke Cloud Composer 3.
Di daftar lingkungan, klik nama lingkungan Anda.
Halaman Environment details akan terbuka.
Buka tab Logs dan periksa bagian Airflow logs>Scheduler.
Untuk rentang waktu tertentu, periksa pod pekerja KubernetesExecutor yang
menjalankan tugas. Jika pod tidak ada lagi, lewati langkah ini. Pod
memiliki awalan airflow-k8s-worker dan DAG atau nama tugas dalam namanya.
Cari masalah yang dilaporkan seperti tugas yang gagal atau tugas yang tidak dapat dijadwalkan.
Skenario pemecahan masalah umum untuk KubernetesExecutor
Bagian ini mencantumkan skenario pemecahan masalah umum yang mungkin Anda alami dengan KubernetesExecutor.
Tugas akan mencapai status Running, lalu gagal selama eksekusi.
Gejala:
Ada log untuk tugas di UI Airflow dan di tab Logs di bagian Workers.
Solusi: Log tugas menunjukkan masalahnya.
Instance tugas akan mencapai status queued, lalu ditandai sebagai UP_FOR_RETRY atau FAILED setelah beberapa waktu.
Gejala:
Tidak ada log untuk tugas di UI Airflow dan di tab Logs di bagian Workers.
Ada log di tab Logs di bagian Scheduler dengan pesan bahwa tugas ditandai sebagai UP_FOR_RETRY atau FAILED.
Solusi:
Periksa log penjadwal untuk mengetahui detail masalah.
Penyebab yang mungkin:
Jika log penjadwal berisi pesan Adopted tasks were still pending after..., diikuti dengan instance tugas yang dicetak, pastikan CeleryKubernetesExecutor diaktifkan di lingkungan Anda.
Instance tugas mencapai status Queued dan langsung ditandai sebagai UP_FOR_RETRY atau FAILED
Gejala:
Tidak ada log untuk tugas di UI Airflow dan di tab Logs di
bagian Workers.
Log penjadwal di tab Logs di bagian Scheduler memiliki pesan Pod creation failed with reason ... Failing task, dan pesan bahwa tugas ditandai sebagai UP_FOR_RETRY atau FAILED.
Solusi:
Periksa log penjadwal untuk mengetahui respons dan alasan kegagalan yang tepat.
Kemungkinan penyebab:
Jika pesan errornya adalah quantities must match the regular expression ..., kemungkinan besar masalahnya disebabkan oleh nilai kustom yang ditetapkan untuk resource k8s (permintaan/batas) pod pekerja tugas.
Tugas KubernetesExecutor gagal tanpa log saat sejumlah besar tugas dijalankan
Saat lingkungan Anda menjalankan sejumlah besar tugas
dengan KubernetesExecutor atau KubernetesPodOperator secara bersamaan, Cloud Composer 3 tidak akan menerima tugas baru hingga beberapa
tugas yang ada selesai. Tugas tambahan ditandai sebagai gagal, dan Airflow
akan mencobanya lagi nanti, jika Anda menentukan percobaan ulang untuk tugas (Airflow melakukannya secara
default).
Gejala: Tugas yang dijalankan dengan KubernetesExecutor atau KubernetesPodOperator gagal tanpa log tugas di UI Airflow atau UI DAG. Di
log penjadwal, Anda dapat melihat pesan error yang mirip
dengan berikut ini:
Sesuaikan jadwal operasi DAG sehingga tugas didistribusikan secara lebih merata dari waktu ke waktu.
Kurangi jumlah tugas dengan menggabungkan tugas-tugas kecil.
Solusi:
Jika Anda ingin tugas tetap dalam status terjadwal hingga lingkungan dapat
menjalankannya, Anda dapat menentukan kumpulan Airflow dengan
jumlah slot terbatas di UI Airflow, lalu mengaitkan semua
tugas berbasis penampung dengan kumpulan ini. Sebaiknya tetapkan jumlah slot
dalam kumpulan ke 50 atau kurang. Tugas tambahan akan tetap dalam status terjadwal hingga
kumpulan Airflow memiliki slot kosong untuk menjalankannya. Jika Anda menggunakan solusi ini tanpa menerapkan kemungkinan solusi, Anda masih dapat mengalami antrean tugas yang besar di kumpulan Airflow.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-29 UTC."],[[["\u003cp\u003eThis page provides troubleshooting guidance for tasks run by KubernetesExecutor in Cloud Composer 3, outlining a step-by-step approach to identify and resolve issues.\u003c/p\u003e\n"],["\u003cp\u003eA common issue addressed is when tasks get stuck in the \u003ccode\u003equeued\u003c/code\u003e state and are then marked as \u003ccode\u003eUP_FOR_RETRY\u003c/code\u003e or \u003ccode\u003eFAILED\u003c/code\u003e, often with no logs, and the solution involves inspecting scheduler logs.\u003c/p\u003e\n"],["\u003cp\u003eAnother issue covered is when tasks fail immediately after entering the \u003ccode\u003eQueued\u003c/code\u003e state, in which case checking scheduler logs for error messages is key to discovering the solution.\u003c/p\u003e\n"],["\u003cp\u003eThe document covers issues that might occur when a large amount of tasks are executed concurrently, leading to tasks failing without logs, with solutions such as adjusting DAG schedules and using Airflow pools.\u003c/p\u003e\n"],["\u003cp\u003eThe page indicates that when tasks get to the running state, and then fail, the solution is found in the task logs, either in the Airflow UI, or in the "Workers" section of the logs tab.\u003c/p\u003e\n"]]],[],null,["\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\n**Cloud Composer 3** \\| Cloud Composer 2 \\| Cloud Composer 1\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nThis page describes how to troubleshoot issues with\n[tasks run by KubernetesExecutor](/composer/docs/composer-3/use-celery-kubernetes-executor) and provides solutions for common\nissues.\n\nGeneral approach to troubleshooting KubernetesExecutor\n\nTo troubleshoot issues with a task executed with KubernetesExecutor, do\nthe following actions in the listed order:\n\n1. Check logs of the task in the [DAG UI](/composer/docs/composer-3/view-dags#runs-history) or\n [Airflow UI](/composer/docs/composer-3/access-airflow-web-interface).\n\n2. Check scheduler logs in Google Cloud console:\n\n 1. In Google Cloud console, go to the **Environments** page.\n\n [Go to Environments](https://console.cloud.google.com/composer/environments)\n 2. In the list of environments, click the name of your environment.\n The **Environment details** page opens.\n\n 3. Go to the **Logs** tab and check the **Airflow logs** \\\u003e\n **Scheduler** section.\n\n 4. For a given time range, inspect the KubernetesExecutor worker pod that was\n running the task. If the pod no longer exists, skip this step. The pod\n has the `airflow-k8s-worker` prefix and a DAG or a task name in its name.\n Look for any reported issues such as a failed task or the task being\n unschedulable.\n\nCommon troubleshooting scenarios for KubernetesExecutor\n\nThis section lists common troublehooting scenarions that you might encounter with KubernetesExecutor.\n\nThe task gets to the `Running` state, then fails during the execution.\n\nSymptoms:\n\n- There are logs for the task in Airflow UI and on the **Logs** tab in the **Workers** section.\n\nSolution: The task logs indicate the problem.\n\nTask instance gets to the `queued` state, then it is marked as `UP_FOR_RETRY` or `FAILED` after some time.\n\nSymptoms:\n\n- There are no logs for task in Airflow UI and on the **Logs** tab in the **Workers** section.\n- There are logs on the **Logs** tab in the **Scheduler** section with a message that the task is marked as `UP_FOR_RETRY` or `FAILED`.\n\nSolution:\n\n- Inspect scheduler logs for any details of the issue.\n\nPossible causes:\n\n- If the scheduler logs contain the `Adopted tasks were still pending after...` message followed by the printed task instance, check that CeleryKubernetesExecutor is enabled in your environment.\n\nThe task instance gets to the `Queued` state and is immediately marked as `UP_FOR_RETRY` or `FAILED`\n\nSymptoms:\n\n- There are no logs for the task in Airflow UI and on the **Logs** tab in the **Workers** section.\n- The scheduler logs on the **Logs** tab in the **Scheduler** section has the `Pod creation failed with reason ... Failing task` message, and the message that the task is marked as `UP_FOR_RETRY` or `FAILED`.\n\nSolution:\n\n- Check scheduler logs for the exact response and failure reason.\n\nPossible reason:\n\nIf the error message is `quantities must match the regular expression ...`,\nthen the issue is most-likely caused by a custom values set for k8s\nresources (requests/limits) of task worker pods.\n\nKubernetesExecutor tasks fail without logs when a large number of tasks is executed\n\nWhen your environment executes a large number of tasks\n[with KubernetesExecutor](/composer/docs/composer-3/use-celery-kubernetes-executor) or [KubernetesPodOperator](/composer/docs/composer-3/use-kubernetes-pod-operator) at the same\ntime, Cloud Composer 3 doesn't accept new tasks until some of the\nexisting tasks are finished. Extra tasks are marked as failed, and Airflow\nretries them later, if you define retries for the tasks (Airflow does this by\ndefault).\n\n**Symptom:** Tasks executed with KubernetesExecutor or KubernetesPodOperator\nfail without task logs in Airflow UI or DAG UI. In the\n[scheduler's logs](/composer/docs/composer-3/view-logs#streaming), you can see error messages similar\nto the following: \n\n pods \\\"airflow-k8s-worker-*\\\" is forbidden: exceeded quota: k8s-resources-quota,\n requested: pods=1, used: pods=*, limited: pods=*\",\"reason\":\"Forbidden\"\n\n**Possible solutions:**\n\n- Adjust the DAG run schedule so that tasks are distributed more evenly over time.\n- Reduce the number of tasks by consolidating small tasks.\n\n**Workaround:**\n\nIf you prefer tasks to stay in the scheduled state until your environment can\nexecute them, you can define an [Airflow pool](https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/pools.html) with the\nlimited number of slots in the Airflow UI and then associate all\ncontainer-based tasks with this pool. We recommend to set the number of slots\nin the pool to 50 or less. Extra tasks will stay in the scheduled state until\nthe Airflow pool has a free slot to execute them. If you use this workaround\nwithout applying possible solutions, you can still experience a large queue of\ntasks in the Airflow pool.\n\nWhat's next\n\n- [Use CeleryKubernetesExecutor](/composer/docs/composer-3/use-celery-kubernetes-executor)\n- [Use KubernetesPodOperator](/composer/docs/composer-3/use-kubernetes-pod-operator)\n- [Troubleshooting scheduling](/composer/docs/composer-3/troubleshooting-scheduling)\n- [Troubleshooting DAGs](/composer/docs/composer-3/troubleshooting-dags)"]]
