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Datadog output plugin malforming the JSON payload when dd_tags
is defined.
#10113
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Do you mean you manually changed the config map? You will need to trigger a hot reload or restart FB pods to pick it up. If you did it via helm then it will auto-roll the pods as it uses a checksum annotation. |
I do a |
Hi all, thanks for reporting this! We looked into this and found that there's a bug with how config option In the meantime, if you want the logs to ingest properly, removing the |
Thanks for picking up @mwdd146980 |
Hi all, thanks for your patience on this. The fix for this has been merged and is scheduled for version 4.0. We are also working on backporting the fix to version 3.2. |
Thanks @patrick-stephens and @mwdd146980! |
Update: fix has gone live on 4.0.0 Release Fluent Bit 4.0.0 · fluent/fluent-bit, backport to 3.2 still pending |
Bug Report
Describe the bug
Messages forwarded from a Kubernetes cluster to Datadog via the Datadog output plugin with
dd_tags
specified result in a malformed JSON payload. The Datadog tags are not applied to the messages forwarded from the Datadog output, and Datadog receives otherwise unidentified messages with a body of the key (ddtags
) and another with the body of the value (env:stage,region:au
).Datadog Live Tail:
Example JSON payload -
"ddtags"
and"env:stage,region:au"
are not part of the message object:To Reproduce
Helm install fluent-bit:
helm upgrade --install fluent-bit -n fluent-bit --create-namespace fluent/fluent-bit
Apply the following
fluent-bit.conf
:I updated the
kubernetes
filter and added thedatadog
output in the K8sConfigMap
after installation. Or the config could be applied at installation time via Helm values.Expected behavior
The log messages are forwarded to Datadog with the
ddtags
attribute set to the specifiedkey:value
pairs.Example JSON payload -
ddtags
is a key in the message object and set to the valueenv:stage,region:au
:Your Environment
Additional context
This issue is preventing us from fully on-boarding our K8s clusters into Datadog, compromising our ability to properly monitor the workloads running on the cluster.
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