Pass the IBM IBM Certified Administrator - Cloud Pak for Integration V2021.2 C1000-130 Questions and answers with CertsForce

In IBM Cloud Pak for Integration (CP4I) v2021.2, which runs on OpenShift Container Platform (OCP), administrators can configure log forwarding to an external log aggregator (e.g., Elasticsearch, Splunk, or Loki).

OCP uses Fluentd as the log collector, and when log forwarding fails due to the external logging aggregator becoming unavailable, the following happens:

Fluentd buffers the logs in memory (up to a defined limit).

If the buffer reaches its maximum size, OCP follows its default log management policy:

Older logs are rotated and deleted to make space for new logs.

This prevents excessive storage consumption on the OpenShift cluster.

This behavior ensures that the logging system does not stop functioning but rather manages storage efficiently by deleting older logs once the buffer is full.

Log rotation is a default behavior in OCP when storage limits are reached.

If logs cannot be forwarded and the buffer is full, OCP deletes old logs to continue operations.

This is a standard logging mechanism to prevent resource exhaustion.

Why Answer A is Correct?

B. OCP stores the logs in a temporary PVC. → Incorrect

OCP does not automatically store logs in a Persistent Volume Claim (PVC).

Logs are buffered in memory and not redirected to PVC storage unless explicitly configured.

C. OCP extends the buffer size and resumes log collection. → Incorrect

The buffer size is fixed and does not dynamically expand.

Instead of increasing the buffer, older logs are rotated out when the limit is reached.

D. The Fluentd daemon is forced to stop. → Incorrect

Fluentd does not stop when the external log aggregator is down.

It continues collecting logs, buffering them until the limit is reached, and then follows log rotation policies.

Explanation of Incorrect Answers:

IBM Cloud Pak for Integration Logging and Monitoring

OpenShift Logging Overview

Fluentd Log Forwarding in OpenShift

OpenShift Log Rotation and Retention Policy

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In IBM Cloud Pak for Integration (CP4I) v2021.2, when new IBM MQ (Message Queue) containers are deployed, sensitive data such as passwords, credentials, and encryption keys must be securely injected into the container environment.

The correct Kubernetes object for storing and injecting sensitive data is a Secret.

Kubernetes Secrets securely store sensitive data

Secrets allow IBM MQ containers to retrieve authentication credentials (e.g., admin passwords, TLS certificates, and API keys) without exposing them in environment variables or config maps.

Unlike ConfigMaps, Secrets are encrypted and access-controlled, ensuring security compliance.

Used by IBM MQ Operator

When deploying IBM MQ in OpenShift/Kubernetes, the MQ operator references Secrets to inject necessary credentials into MQ containers.

Example:

Why is "Secret" the correct answer?apiVersion: v1

kind: Secret

metadata:

name: mq-secret

type: Opaque

data:

mq-password: bXlxYXNzd29yZA==

The MQ container can then access this mq-password securely.

Prevents hardcoding sensitive data

Instead of storing passwords directly in deployment files, using Secrets enhances security and compliance with enterprise security standards.

Why are the other options incorrect?❌ A. Replicator

The Replicator is responsible for synchronizing and replicating messages across MQ queues but does not store sensitive credentials.

❌ B. MQRegistry

The MQRegistry is used for tracking queue manager details but does not manage sensitive data injection.

It mainly helps with queue manager registration and configuration.

❌ C. DeploymentConfig

A DeploymentConfig in OpenShift defines how pods should be deployed but does not handle sensitive data injection.

Instead, DeploymentConfig can reference a Secret, but it does not store sensitive information itself.

IBM MQ Security - Kubernetes Secrets

IBM Docs – Securely Managing MQ in Kubernetes

IBM Cloud Pak for Integration Knowledge Center

Covers how Secrets are used in MQ container deployments.

Red Hat OpenShift Documentation – Kubernetes Secrets

Secrets in Kubernetes

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In IBM Cloud Pak for Integration (CP4I) v2021.2, Foundational Services provide authentication and access control mechanisms, including Single Sign-On (SSO) integration. The two supported authentication types for SSO are:

OpenShift Authentication

IBM Cloud Pak for Integration leverages OpenShift authentication to integrate with existing identity providers.

OpenShift authentication supports OAuth-based authentication, allowing users to sign in using an OpenShift identity provider, such as LDAP, OIDC, or SAML.

This method enables seamless user access without requiring additional login credentials.

Enterprise SAML (Security Assertion Markup Language)

SAML authentication allows integration with enterprise identity providers (IdPs) such as IBM Security Verify, Okta, Microsoft Active Directory Federation Services (ADFS), and other SAML 2.0-compatible IdPs.

It provides federated identity management for SSO across enterprise applications, ensuring secure access to Cloud Pak services.

A. Basic Authentication – Incorrect

Basic authentication (username and password) is not used for Single Sign-On (SSO). SSO mechanisms require identity federation through OpenID Connect (OIDC) or SAML.

C. PublicKey – Incorrect

PublicKey authentication (such as SSH key-based authentication) is used for system-level access, not for SSO in Foundational Services.

E. Local User Registry – Incorrect

While local user registries can store credentials, they do not provide SSO capabilities. SSO requires federated identity providers like OpenShift authentication or SAML-based IdPs.

Why the other options are incorrect:

IBM Cloud Pak Foundational Services Authentication Guide

OpenShift Authentication and Identity Providers

IBM Cloud Pak for Integration SSO Configuration

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In IBM Cloud Pak for Integration (CP4I) v2021.2, profiles define the resource allocation and configuration settings for deployed services. When creating a second medium-size profile, the system will allocate the resources according to the medium-size specifications, without affecting the first profile.

IBM Cloud Pak for Integration supports multiple profiles, each with its own resource allocation.

When a second medium-size profile is created, it is independently assigned the medium-size configuration without modifying the existing profiles.

This allows multiple services to run with similar resource constraints but remain separately managed.

Why Option B is Correct:

A. The first profile will be replaced by the second profile. → ❌ Incorrect

Creating a new profile does not replace an existing profile; each profile is independent.

C. The first profile will be re-configured with a medium size. → ❌ Incorrect

The first profile remains unchanged. A second profile does not modify or reconfigure an existing one.

D. The second profile will be configured with a large size. → ❌ Incorrect

The second profile will retain the specified medium size and will not be automatically upgraded to a large size.

Explanation of Incorrect Answers:

IBM Cloud Pak for Integration Sizing and Profiles

Managing Profiles in IBM Cloud Pak for Integration

OpenShift Resource Allocation for CP4I

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In IBM Cloud Pak for Integration (CP4I) v2021.2, which runs on Red Hat OpenShift, logging is a critical component for monitoring cluster and application activities. To enable OpenShift Logging, two key operators must be installed:

OpenShift Logging Operator (B)

This operator is responsible for managing the logging stack in OpenShift.

It helps configure and deploy logging components like Fluentd, Kibana, and Elasticsearch within the OpenShift cluster.

It provides a unified way to collect and visualize logs across different workloads.

OpenShift Elasticsearch Operator (E)

This operator manages the Elasticsearch cluster, which is the central data store for log aggregation in OpenShift.

Elasticsearch stores logs collected from cluster nodes and applications, making them searchable and analyzable via Kibana.

Without this operator, OpenShift Logging cannot function, as it depends on Elasticsearch for log storage.

A. OpenShift Console Operator → Incorrect

The OpenShift Console Operator manages the web UI of OpenShift but has no role in logging.

It does not collect, store, or manage logs.

C. OpenShift Log Collector → Incorrect

There is no official OpenShift component or operator named "OpenShift Log Collector."

Log collection is handled by Fluentd, which is managed by the OpenShift Logging Operator.

D. OpenShift Centralized Logging Operator → Incorrect

This is not a valid OpenShift operator.

The correct operator for centralized logging is OpenShift Logging Operator.

Explanation of Incorrect Answers:

OpenShift Logging Overview

OpenShift Logging Operator Documentation

OpenShift Elasticsearch Operator Documentation

IBM Cloud Pak for Integration Logging Configuration

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In IBM Cloud Pak for Integration (CP4I) v2021.2, App Connect Enterprise (ACE) Dashboard requires persistent storage to maintain configurations, logs, and runtime data. The supported storage type for the ACE Dashboard instance is file storage because:

It supports ReadWriteMany (RWX) access mode, allowing multiple pods to access shared data.

It ensures data persistence across restarts and upgrades, which is essential for managing ACE integrations.

It is compatible with NFS, IBM Spectrum Scale, and OpenShift Container Storage (OCS), all of which provide file system-based storage.

A. Ephemeral storage – Incorrect

Ephemeral storage is temporary and data is lost when the pod restarts or gets rescheduled.

ACE Dashboard needs persistent storage to retain configuration and logs.

B. Flash storage – Incorrect

Flash storage refers to SSD-based storage and is not specifically required for the ACE Dashboard.

While flash storage can be used for better performance, ACE requires file-based persistence, which is different from flash storage.

D. Raw block storage – Incorrect

Block storage is low-level storage that is used for databases and applications requiring high-performance IOPS.

ACE Dashboard needs a shared file system, which block storage does not provide.

Why the other options are incorrect:

IBM App Connect Enterprise (ACE) Storage Requirements

IBM Cloud Pak for Integration Persistent Storage Guide

OpenShift Persistent Volume Types

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In Red Hat OpenShift GitOps, which is based on ArgoCD, the deployment process is centered around Git repositories. The framework typically uses at least two repositories:

Application Repository – Contains the source code, manifests, and configurations for the application itself.

Environment Configuration Repository (Correct Answer) – Stores Kubernetes/OpenShift manifests, Helm charts, Kustomize overlays, or other deployment configurations for different environments (e.g., Dev, Test, Prod).

This separation of concerns ensures that:

Developers manage application code separately from infrastructure and deployment settings.

GitOps principles are applied, enabling automated deployments based on repository changes.

The Environment Configuration Repository serves as the single source of truth for deployment configurations.

Why the Other Options Are Incorrect?Option

Explanation

Correct?

A. Nexus

❌ Incorrect – Nexus is a repository manager for storing binaries, artifacts, and dependencies (e.g., Docker images, JAR files), but it is not a GitOps repository.

❌

B. Ansible configuration

❌ Incorrect – While Ansible can manage infrastructure automation, OpenShift GitOps primarily uses Kubernetes manifests, Helm, or Kustomize for deployment configurations.

❌

D. Maven

❌ Incorrect – Maven is a build automation tool for Java applications, not a repository type used in GitOps workflows.

❌

Final Answer:✅ C. Environment configuration

Red Hat OpenShift GitOps Documentation

IBM Cloud Pak for Integration and OpenShift GitOps

ArgoCD Best Practices for GitOps

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

OpenShift Pipelines are based on Tekton, an open-source framework for building Continuous Integration/Continuous Deployment (CI/CD) pipelines natively in Kubernetes.

Tekton provides Kubernetes-native CI/CD functionality by defining pipeline resources as custom resources (CRDs) in OpenShift. This allows for scalable, cloud-native automation of software delivery.

Kubernetes-Native: Unlike Jenkins, which requires external servers or agents, Tekton runs natively in OpenShift/Kubernetes.

Serverless & Declarative: Pipelines are defined using YAML configurations, and execution is event-driven.

Reusable & Extensible: Developers can define Tasks, Pipelines, and Workspaces to create modular workflows.

Integration with GitOps: OpenShift Pipelines support Argo CD for GitOps-based deployment strategies.

Why Tekton is Used in OpenShift Pipelines?Example of a Tekton Pipeline Definition in OpenShift:apiVersion: tekton.dev/v1beta1

kind: Pipeline

metadata:

name: example-pipeline

spec:

tasks:

- name: echo-hello

taskSpec:

steps:

- name: echo

image: ubuntu

script: |

#!/bin/sh

echo "Hello, OpenShift Pipelines!"

A. Travis → ❌ Incorrect

Travis CI is a cloud-based CI/CD service primarily used for GitHub projects, but it is not used in OpenShift Pipelines.

B. Jenkins → ❌ Incorrect

OpenShift previously supported Jenkins-based CI/CD, but OpenShift Pipelines (Tekton) is now the recommended Kubernetes-native alternative.

Jenkins requires additional agents and servers, whereas Tekton runs serverless in OpenShift.

D. Argo CD → ❌ Incorrect

Argo CD is used for GitOps-based deployments, but it is not the underlying technology of OpenShift Pipelines.

Tekton and Argo CD can work together, but Argo CD alone does not handle CI/CD pipelines.

Explanation of Incorrect Answers:

IBM Cloud Pak for Integration CI/CD Pipelines

Red Hat OpenShift Pipelines (Tekton)

Tekton Pipelines Documentation

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

High availability (HA) in IBM Cloud Pak for Integration (CP4I) v2021.2 is crucial to ensure continuous service availability and reliability. Different components use different HA mechanisms, and the correct options are B and C.

B. Queue Manager (MQ) uses Replicated Data Queue Manager (RDQM).

IBM MQ supports HA through Replicated Data Queue Manager (RDQM), which uses synchronous data replication across nodes.

This ensures failover to another node without data loss if the primary node goes down.

RDQM is an efficient HA solution for MQ in CP4I.

C. API management uses a quorum mechanism where components are deployed on a minimum of three failure domains.

API Connect in CP4I follows a quorum-based HA model, meaning that the deployment is designed to function across at least three failure domains (availability zones).

This ensures resilience and prevents split-brain scenarios in case of node failures.

Correct Answers Explanation:

A. DataPower gateway uses a Quorum mechanism where a global load balancer uses a quorum algorithm to choose the active instance. → Incorrect

DataPower typically operates in Active/Standby mode rather than a quorum-based model.

It can be deployed behind a global load balancer, but the quorum algorithm is not used to determine the active instance.

D. Platform Navigator uses an Active/Active deployment, where the primary handles all the traffic and in case of failure of the primary, the load balancer will then route the traffic to the secondary. → Incorrect

Platform Navigator does not follow a traditional Active/Active deployment.

It is typically deployed as a highly available microservice on OpenShift, distributing workloads across nodes.

E. AppConnect can use a mix of mechanisms - like failover for stateful workloads and active/active deployments for stateless workloads. → Incorrect

While AppConnect can be deployed in Active/Active mode, it does not necessarily mix failover and active/active mechanisms explicitly for HA purposes.

Incorrect Answers Explanation:

IBM MQ High Availability and RDQM

IBM API Connect High Availability

IBM DataPower Gateway HA Deployment

IBM Cloud Pak for Integration Documentation

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

IBM provides a publicly available document that lists the known issues, limitations, and restrictions for each release of IBM Cloud Pak for Integration (CP4I). This document is called "IBM Cloud Pak for Integration - Known Limitations."

It details any functional restrictions, unresolved issues, and workarounds applicable to the current and previous versions of CP4I.

This document helps administrators and developers understand current limitations before deploying or upgrading CP4I components.

It is updated regularly as IBM identifies new issues or resolves existing ones.

A. IBM Cloud Pak for Integration - Q&A (Incorrect)

A Q&A section typically contains frequently asked questions (FAQs) but does not specifically focus on known issues or limitations.

C. IBM Cloud Pak for Integration - Known Problems (Incorrect)

IBM does not maintain a document explicitly titled "Known Problems." Instead, known issues are included under "Known Limitations."

D. IBM Cloud Pak for Integration - Latest News (Incorrect)

The "Latest News" section typically covers new features, updates, and release announcements, but it does not provide a dedicated list of limitations or unresolved issues.

Analysis of Incorrect Options:

IBM Cloud Pak for Integration - Known Limitations

IBM Cloud Pak for Integration Documentation

IBM Support - Fixes and Known Issues

IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References: