BusinessConnect Container Edition configuration/scalability on Kubernetes clusters

BusinessConnect Container Edition configuration/scalability on Kubernetes clusters

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Article ID: KB0071042

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Updated On:

Products Versions
TIBCO BusinessConnect Container Edition all versions

Description

Here are some common questions when installing and configuring BusinessConnect Container Edition:
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- Do you have any suggestions about the resource (CPU/limit) requests and limits of the different bc components?

- Should all "BC" components run as replica sets or would it make sense for some to run as stateful sets?

- Regarding scaling of pod replicas, should we run at least two containers per pod?
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Environment

All Environments

Resolution

1) Do you have any suggestions about the resource (CPU/limit) requests and limits of the different bc components?

=> Currently, the default CPU and memory for each BusinessConnect Container Edition(BCCE)/TIBCO Auditsafe(TAS) container are used. These default values are:
Resources:
Requests:
memory: "128Mi"
CPU: "500m"
Limits:
Memory: "512Mi"
CPU: "1000m"


We suggest that users use these default values as they make the most efficient use of the resources of the worker nodes, and scale up the number of replicas if one component(server) is too busy to handle more requests.

2) Should all "BC" components run as replica sets or would it make sense for some to run as stateful sets?

=> We recommend that each component(server) run with at least two replicas, so when one pod stops due to an issue, another pod can take over. At least two worker nodes should be in the Kubernetes cluster. When one worker node encounters an issue, another worker node can take over at that moment.
  
3) Regarding scaling of pod replicas, should we run at least two containers per pod?

=> Running one BC component container in one pod is easiest to monitor and manage. If an issue arises in the BC component container, the pod can be killed, and the new one will be automatically started.

Issue/Introduction

BCCE configuration/scalability on kubernetes clusters