The best practice for ensuring application high availability (HA) is to run multiple replicas (pods) of the application and distribute them across different worker nodes. This strategy mitigates the risk of a single point of failure. If one worker node becomes unavailable due to hardware failure or maintenance, the application instances running on other healthy worker nodes can continue to serve traffic, ensuring service continuity. This is typically managed by a Kubernetes Deployment or a Red Hat OpenShift DeploymentConfig, which works with the scheduler to enforce this distribution.

B. Use multiple pods across different master nodes.

Application workloads should not be scheduled on master (control plane) nodes. These nodes are reserved for running essential cluster management services, and adding application pods can compromise cluster stability and security.

C. Use multiple small pods on a master node.

This is incorrect for two reasons: it violates the principle of not running applications on master nodes, and it creates a single point of failure by placing all pods on one node.

D. Use multiple pods across both worker and master nodes.

While this includes the correct practice of using worker nodes, it also includes the incorrect and risky practice of using master nodes for application workloads, making it a flawed HA strategy.

1. IBM Cloud Documentation - High availability for your cluster: "To protect your app from a zone failure

you must have multiple worker nodes in different zones in your cluster and deploy multiple replicas of your app... When you have multiple app pods

they are spread across worker nodes in different zones." This document explicitly states that spreading app pods (replicas) across different worker nodes is the key to high availability.

Source: IBM Cloud Docs

"High availability for your cluster"

Section: "Single zone clusters".

2. Kubernetes Documentation - Concepts > Architecture > Nodes: "The worker nodes in a cluster are the machines (VMs

physical servers

etc) that run your containerized applications... The control plane manages the worker nodes and the Pods in the cluster." This official documentation establishes the fundamental architectural separation where applications run on worker nodes

not control plane (master) nodes.

Source: Kubernetes Documentation

"Components of Kubernetes"

Section: "Worker Nodes".

3. Red Hat OpenShift Container Platform Documentation - About high availability: "For application high availability

you should have multiple replicas of a pod running. If you have multiple replicas of a pod running on different nodes and a node fails

the pods on the failed node are recreated on other nodes." This directly supports the principle of using multiple pods on different nodes for application HA.

Source: Red Hat OpenShift Container Platform 4.14 Documentation

"About high availability"

Section: "Application high availability".

Container Application Software for Enterprises (CASE) is a specification that defines a file structure for packaging, managing, and unpacking containerized applications. A CASE file acts as a package containing all the necessary configuration and metadata for an application, including its dependencies, Helm charts, and container image references. This structure is crucial for simplifying and automating the deployment of applications, particularly in offline or air-gapped environments, by ensuring all required components are bundled together in a consistent, discoverable format.

B. CASE is the specification for the package itself, not the command-line syntax used for mirroring operations like oc-mirror.

C. CASE does not define naming conventions for any Kubernetes or OpenShift resources, including namespaces. Naming conventions are typically a matter of organizational policy.

D. CASE is a packaging and metadata specification for deployment, not a runtime authentication standard like OpenID Connect (OIDC) or SAML.

1. IBM Documentation

IBM Cloud Paks

Getting started with CASE: "A CASE is a specification that defines a file structure for packaging

managing

and unpacking containerized applications. The CASE that you download is a .tgz file that contains

among other things

charts

images

and configuration files." (Section: "Getting started with CASE")

2. IBM Documentation

IBM Cloud Pak for Business Automation 23.0.2

Preparing for an offline installation: "A CASE (Container Application Software for Enterprises) file is a well-defined file structure that specifies the composition of a packaged containerized application

and lists the dependent containerized applications." (Section: "Preparing a bastion host")

3. IBM/case on GitHub

The CASE specification: "A CASE is a defined file structure that provides packaging and definition of a containerized application. It provides metadata about the application and its components that can be consumed by automation tooling to deploy the application into a target Red Hat OpenShift cluster." (Source: README.md

Introduction section)

In a containerized environment managed by Kubernetes or OpenShift, the Operator pattern is used to automate the deployment and lifecycle management of complex applications like IBM Cloud Pak for Business Automation. The Operator is the primary controller that reads the Custom Resource (CR) YAML file and creates all the necessary underlying resources (Pods, Services, ConfigMaps, etc.). When troubleshooting a new deployment, the Operator's log is the first place to check, as it records the entire orchestration process, including any errors encountered while interpreting the CR, pulling images, or creating resources. This log provides the most direct insight into why a deployment might be failing at the infrastructure or orchestration level.

B. Liberty Log: This is an application server log from within the container. It is only useful for troubleshooting application-level issues after the container has successfully started.

C. YAMLlog: This is not a standard log file. YAML files are used for configuration definitions and do not produce their own logs.

D. p8servererror.log: This is a specific error log for the FileNet Content Platform Engine application. It is a secondary, application-specific log and is not relevant for general deployment issues.

1. IBM Cloud Pak for Business Automation Documentation

"Troubleshooting installation and upgrade issues." This official guide frequently directs administrators to check the operator logs as a primary step. It states

"If the operator is stuck in a Pending or Error state

describe the operator pod and check the events and logs." This confirms the operator log is central to diagnosing deployment problems. (IBM Documentation for Cloud Pak for Business Automation 21.0.3

Troubleshooting > Troubleshooting installation and upgrade issues).

2. IBM Cloud Pak for Business Automation Documentation

"Must-gather logs for troubleshooting." The documentation on gathering diagnostic data explicitly lists "Operator logs" as a key component to collect when reporting issues with a deployment

underscoring their importance in the troubleshooting process. (IBM Documentation for Cloud Pak for Business Automation 22.0.2

Troubleshooting > Contacting IBM Support > Must-gather logs for troubleshooting).

3. IBM Cloud Pak for Business Automation Documentation

"Troubleshooting the operator." This section provides direct guidance: "Check the logs for the operator pod to see whether there are any obvious errors. Replace with the name of the pod... oc logs -f". This command is a fundamental troubleshooting step for any deployment managed by the operator. (IBM Documentation for Cloud Pak for Business Automation 21.0.3

Troubleshooting > Troubleshooting the operator).

When security pods remain in Pending (unscheduled) state the most frequent cause is that the pod images cannot be pulled because the Resource Registry ConfigMap is wrongly set (for example, incorrect image-registry path or secret). IBM CP4BA installation troubleshooting guides explicitly direct administrators to verify and, if necessary, correct the Resource Registry before further action; once the registry is fixed, the scheduler can place the security pods.

B. Re-queueing by the reconcile loop will not fix a mis-configured registry; pods will stay Pending.

C. CPU/memory problems leave pods Pending with “insufficient resources”, not specifically the security pods issue called out in CP4BA docs.

D. JMS queues are unrelated to pod scheduling or image pull operations.

1. IBM Cloud Pak for Business Automation 22.0.1 Documentation – “Troubleshooting installation > Security pods not scheduled”

steps 1-3 (doc ID: cp4a-trbl-sec-pods)

2. IBM Cloud Pak Foundational Services 3.22 – “Offline install > Verifying the Resource Registry ConfigMap”

paragraph 2–3

3. Redbook: Malhoit et al.

“IBM Cloud Pak for Business Automation Installation and Deployment”

SG24-8482-00

Ch.14

p. 318-319

4. IBM Support Technote: “Security pods remain in Pending state after CP4BA install” (TS009908)

section ‘Cause’ para 1 and ‘Resolving the problem’ step 1

IBM Business Automation Insights (BAI) uses a configurable mechanism to protect sensitive personal data. This is achieved by defining anonymization or obfuscation rules in a JSON configuration file. These rules are applied by the Apache Flink processing jobs before the data is stored in Elasticsearch. The rules specify which data fields to anonymize and the method to use (e.g., masking, hashing). This process effectively removes the sensitive nature of the data from the stored events, ensuring compliance with privacy regulations like GDPR.

A. StoredlQ plugin: IBM StoredIQ is a separate product for data governance and eDiscovery, not a native component within Business Automation Insights responsible for data anonymization during event processing.

B. SI Encryption module: Encryption protects data at rest or in transit by making it unreadable without a key. It does not remove or anonymize the sensitive information itself, which is the core of the question.

C. Personal data discovery rules: These rules would be for identifying or classifying personal data. The actual process of removing or masking the identified data is handled by the anonymization rules.

1. IBM Documentation for IBM Cloud Pak for Business Automation. "Protecting personal data." This official document details the process of configuring Business Automation Insights to obfuscate sensitive data. It states

"You configure obfuscation by providing a JSON configuration with obfuscation rules... The Flink jobs that process events apply the obfuscation rules before storing the resulting data in Elasticsearch." This directly supports that anonymization (obfuscation) rules are the responsible component. (IBM Cloud Pak for Business Automation > Administering > Administering Business Automation Insights > Protecting personal data).