[Questions] K8S Cluster Operator questions #14024
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Community Support Policy
RabbitMQ version used4.1.0 Erlang version used27.3.x Operating system (distribution) usedOpenShift (Red Hat Enterprise Linux CoreOS nodes) How is RabbitMQ deployed?Community Docker image rabbitmq-diagnostics status outputSee https://www.rabbitmq.com/docs/cli to learn how to use rabbitmq-diagnostics
Logs from node 1 (with sensitive values edited out)N/A – question is about the operator availability in OperatorHub, not runtime behavior Logs from node 2 (if applicable, with sensitive values edited out)N/A – question is about the OperatorHub versioning Logs from node 3 (if applicable, with sensitive values edited out)N/A – question is about the OperatorHub versioning rabbitmq.confInstalled RabbitMQ Cluster Operator from OperatorHub on OpenShift Steps to deploy RabbitMQ clusterInstalled RabbitMQ Cluster Operator from OperatorHub on OpenShift Steps to reproduce the behavior in questionGo to community-operators-prod See that latest version is 2.12.1 Go to cluster-operator releases See that latest release is v2.14.0 v2.14.0 is not available on OpenShift OperatorHu advanced.configN/A Application codeN/A Kubernetes deployment fileThis is how we deploy the operator on OpenShift (via OperatorHub UI or CLI)No custom YAML beyond CRDs and RabbitmqCluster creationWhat problem are you trying to solve?We would like to use features and fixes introduced in RabbitMQ Cluster Operator v2.14.0, but on OpenShift we’re currently limited to v2.12.1 via OperatorHub (as seen in community-operators-prod). Could you please advise if there are plans to submit v2.14.0 to OperatorHub? Thanks in advance! |
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Replies: 3 comments 3 replies
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Short answeryes, we plan to submit 2.13 and 2.14 to OperatorHub. Long answerWe stopped submitting the operators because our infrastructure, where we tested the operator on OKD (oss openshift), broke down to pieces. At the time, there were other pressing matters to look after. To be honest, I wasn't even sure if someone out there was still relying on OperatorHub for our operator 🙃 Given that RedHat makes a living of making OKD so impossible to deploy, that you end up in despair paying any lump sum for automation to install it (along with other fancy tools you may not even need/want), and that we are not willing to pay OCP licenses, the best compromise is installing OLM in a local Kubernetes (KinD), and validating that the operator deploys. This requires some work on our side, on the github workflows side of things. I appreciate you asking (offering?) community help, however, since the changes are required on the infrastructure side, I'm afraid this change must come from us. I'm hoping to get to this task in the next few days, or next week. |
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Thanks for the detailed explanation! Great to hear that versions 2.13 and 2.14 are planned for submission to OperatorHub. Please feel free to reach out if there's any way we can assist or provide feedback once the update is in progress. Thanks again! 🙏 |
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Hi, We are currently using VMware Tanzu in our organization and would like to confirm whether this includes support for RabbitMQ and the RabbitMQ Cluster Operator (including usage via OperatorHub on OpenShift). Could you please clarify the following: Does our Tanzu subscription automatically include support for RabbitMQ, including the Cluster Operator? If yes, what is the process to open a support case (e.g., via VMware Support Portal or another channel)? We're particularly interested in getting assistance or confirmation regarding the availability and maintenance of RabbitMQ versions on OperatorHub for OpenShift. Thanks in advance for your help! Best regards |
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Short answer
yes, we plan to submit 2.13 and 2.14 to OperatorHub.
Long answer
We stopped submitting the operators because our infrastructure, where we tested the operator on OKD (oss openshift), broke down to pieces. At the time, there were other pressing matters to look after. To be honest, I wasn't even sure if someone out there was still relying on OperatorHub for our operator 🙃
Given that RedHat makes a living of making OKD so impossible to deploy, that you end up in despair paying any lump sum for automation to install it (along with other fancy tools you may not even need/want), and that we are not willing to pay OCP licenses, the best compromise is installing OLM in a local Kuberne…