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error in onpremisse airbyte: ```2026-03-25 20:03:3...
# replication-ask-ai
r
error in onpremisse airbyte:
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2026-03-25 20:03:36 platform ERROR Failing job: 160052, reason: Job failed after too many retries for connection 026321d6-b772-4ba6-aec2-e15c9ab5b7c2
2026-03-25 21:03:31 platform ERROR Pipeline Exception: io.airbyte.workload.launcher.pipeline.stages.model.StageError: io.airbyte.workers.exception.ResourceConstraintException: Unable to start the CHECK pod. This may be due to insufficient system resources. Please check available resources and try again.
message: io.airbyte.workers.exception.ResourceConstraintException: Unable to start the CHECK pod. This may be due to insufficient system resources. Please check available resources and try again.
stackTrace: [Ljava.lang.StackTraceElement;@63a07173
k
The error 
ResourceConstraintException: Unable to start the CHECK pod
indicates that your Kubernetes cluster has insufficient resources to schedule the connector check pod. Root Cause When Airbyte spawns pods for operations like Check, Discover, or Sync, it uses specific resource configurations. If these aren't explicitly set, Kubernetes falls back to the cluster's default 
LimitRange
, which may be too low — causing OOM or scheduling failures. [OOM issue] How to Fix Option 1: Set instance-wide resource limits in values.yaml Add or modify the following in your Helm `values.yaml`:
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global:
  jobs:
    resources:
      limits:
        cpu: "4"
        memory: "8Gi"
      requests:
        cpu: "2"
        memory: "4Gi"
[Configuring Connector Resources] Option 2: Set environment variables directly You can alternatively configure these environment variables: • 
JOB_MAIN_CONTAINER_CPU_REQUEST
• 
JOB_MAIN_CONTAINER_CPU_LIMIT
• 
JOB_MAIN_CONTAINER_MEMORY_REQUEST
• 
JOB_MAIN_CONTAINER_MEMORY_LIMIT
[Configuring Connector Resources] Option 3: Check Kubernetes scheduling events Run the following to see if there are 
FailedScheduling
events:
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kubectl get events -n airbyte --sort-by=.lastTimestamp
This will help confirm whether the issue is CPU/memory insufficiency or something else (e.g., node architecture mismatch). [pod scheduling issue] Important Note There is a known nuance: the 
jobs.resources
values in 
values.yaml
apply to sync jobs, but Check/Discover operations may use different environment variables. If your cluster has a restrictive 
LimitRange
, pods for Check operations may still be constrained. Make sure your cluster nodes have enough allocatable resources to satisfy the requests you configure. [OOM issue] 👍 0 button 👎 0 button ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
r
@kapa.ai how to connect with airbyte database?
k
Based on the context of your on-premises Airbyte deployment, here's how to connect Airbyte to an external PostgreSQL database using the Helm chart: Step 1: Create a Kubernetes Secret
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apiVersion: v1
kind: Secret
metadata:
  name: airbyte-config-secrets
type: Opaque
stringData:
  database-user: your_db_user
  database-password: your_db_password
[External DB] Step 2: Configure values.yaml Helm chart V1:
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postgresql:
  enabled: false

global:
  database:
    type: external
    secretName: "airbyte-config-secrets"
    host: "your-db-host"
    port: "5432"
    database: "your_db_name"
    userSecretKey: "database-user"
    passwordSecretKey: "database-password"
Helm chart V2 (note: 
database
key is renamed to 
name
):
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postgresql:
  enabled: false

global:
  database:
    type: external
    secretName: "airbyte-config-secrets"
    host: "your-db-host"
    port: 5432
    name: "your_db_name"
    userSecretKey: "database-user"
    passwordSecretKey: "database-password"
[External DB] Key Points • 
postgresql.enabled: false
 disables the internal bundled Postgres instance. • The database password must be stored in the Kubernetes secret (
airbyte-config-secrets
) — it cannot be set directly in 
values.yaml
. • In Helm chart V2, the database name key changed from 
database
to 
name
. [Enterprise DB config] > Airbyte only supports PostgreSQL as its internal metadata database. AWS RDS or GCP Cloud SQL are recommended for production deployments. 👍 0 button 👎 0 button ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
r
@kapa.ai
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kubectl: command not found
k
The error 
kubectl: command not found
means 
kubectl
is not installed on your system. You need to install it to interact with your Airbyte Kubernetes cluster. Install kubectl Follow the official installation instructions for your OS: https://kubernetes.io/docs/tasks/tools/ [Enterprise Guide] Configure kubectl for abctl (local deployments) If you're using 
abctl
(local deployment), once 
kubectl
is installed, configure it to point to your Airbyte cluster using either: Option 1 — via kind:
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kind export kubeconfig -n airbyte-abctl
Option 2 — via kubeconfig flag:
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kubectl --kubeconfig ~/.airbyte/abctl/abctl.kubeconfig --namespace airbyte-abctl get pods
[Troubleshoot abctl; Developing Locally] After that, you can verify your pods are running with:
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kubectl get pods -n airbyte-abctl
👍 0 button 👎 0 button ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
r
@kapa.ai using this command with abctl:
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kubectl get events -n airbyte --sort-by=.lastTimestamp
k
When using 
abctl
for a local Airbyte deployment, the Kubernetes namespace is 
airbyte-abctl
, not 
airbyte
. So the correct command would be:
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kubectl --kubeconfig ~/.airbyte/abctl/abctl.kubeconfig get events -n airbyte-abctl --sort-by=.lastTimestamp
Or, if you've already exported the kubeconfig via `kind export kubeconfig -n airbyte-abctl`:
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kubectl get events -n airbyte-abctl --sort-by=.lastTimestamp
[Troubleshoot abctl; Developing Locally] 👍 0 button 👎 0 button ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.
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