Free IBM C1000-130 Practice Exam with Questions & Answers | Set: 2

When configuring OpenShift Logging with Kibana to retrieve logs for Cloud Pak for Integration (CP4I) applications, the correct index pattern to use is applications*.

Here’s why:

IBM Cloud Pak for Integration (CP4I) applications running on OpenShift generate logs that are stored in the Elasticsearch logging stack.

The standard OpenShift logging format organizes logs into different indices based on their source type.

The applications* index pattern is used to capture logs for applications deployed on OpenShift, including CP4I components.

Analysis of the options:

Option A (Incorrect – cp4i-*): There is no specific index pattern named cp4i-* for retrieving CP4I logs in OpenShift Logging.

*Option B (Correct – applications)**: This is the correct index pattern used in Kibana to retrieve logs from OpenShift applications, including CP4I components.

Option C (Incorrect – torn-*): This is not a valid OpenShift logging index pattern.

Option D (Incorrect – app-*): This index does not exist in OpenShift logging by default.

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

IBM Cloud Pak for Integration Logging Guide

OpenShift Logging Documentation

Kibana and Elasticsearch Index Patterns in OpenShift

After successfully installing an OpenShift cluster, the most reliable way to confirm that the cluster is up and running is by checking the status of its nodes. This is done using the oc get nodes command.

The command oc get nodes lists all the nodes in the cluster and their current status.

If the installation is successful, the nodes should be in a "Ready" state, indicating that the cluster is functional and prepared for further configuration, including the installation of IBM Cloud Pak for Integration (CP4I).

Option A (Incorrect – which oc): This only verifies that the OpenShift CLI (oc) is installed on the local system, but it does not confirm the cluster installation.

Option B (Incorrect – Checking /.openshift_install.log): While the installation log may indicate a successful install, it does not confirm the operational status of the cluster.

Option C (Correct – oc get nodes): This command confirms that the cluster is running and provides a status check on all nodes. If the nodes are listed and marked as "Ready", it indicates that the OpenShift cluster is successfully installed.

Option D (Incorrect – OpenShift Admin Console Access): While the OpenShift Web Console can be accessed if the cluster is installed, this does not guarantee that the cluster is fully operational. The most definitive check is through the oc get nodes command.

Analysis of the Options:

IBM Cloud Pak for Integration Installation Guide

Red Hat OpenShift Documentation – Cluster Installation

Verifying OpenShift Cluster Readiness (oc get nodes)

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

In IBM Cloud Pak for Integration (CP4I) v2021.2, App Connect Designer is a low-code integration tool that enables users to design and deploy integrations between applications and services. It runs as a containerized service within OpenShift.

OpenShift supports multi-instance deployments, allowing users to create multiple instances of App Connect Designer within the same namespace.

This flexibility enables organizations to run separate designer instances for different projects, teams, or environments within the same namespace.

Each instance operates independently, and users can configure them with different settings and access controls.

Why Option C is Correct:

Explanation of Incorrect Answers:

In IBM Cloud Pak for Integration (CP4I), the Operations Dashboard provides visibility into API and application performance by collecting and analyzing tracing data. The Sampling Policy is a configurable setting that determines the percentage of traces that are sampled, collected, and stored for analysis.

Tracing all requests can be resource-intensive, so a sampling policy allows administrators to control how much trace data is captured, balancing observability with system performance.

Sampling can be random (e.g., capture 10% of requests) or rule-based (e.g., capture only slow or error-prone transactions).

Administrators can configure trace sampling rates based on workload needs.

A higher sampling rate captures more traces, useful for debugging but may increase storage and processing overhead.

A lower sampling rate reduces storage but might miss some performance insights.

How the Sampling Policy Works:

A. Sampling policy (Correct) ✅

The sampling policy is the correct setting that defines how traces are collected and stored in the Operations Dashboard.

B. Sampling context (Incorrect) ❌

No such configuration exists in CP4I. The term "context" is generally used for metadata about a trace, not for controlling sampling rates.

C. Tracing policy (Incorrect) ❌

While tracing policies define whether tracing is enabled, they do not directly configure trace sampling rates.

D. Trace context (Incorrect) ❌

Trace context refers to the metadata attached to traces (such as trace IDs), but it does not determine the percentage of traces sampled.

Analysis of the Options:

IBM API Connect and Operations Dashboard - Tracing Configuration

IBM Cloud Pak for Integration - Distributed Tracing Guide

OpenTelemetry and Sampling Policy for IBM Cloud Pak

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

When installing IBM Cloud Pak for Integration (CP4I) on an OpenShift cluster that lacks internet access, an air-gapped installation is required. This process involves mirroring container images from an IBM container registry to a portable registry that can be accessed by the disconnected OpenShift cluster.

To authenticate and mirror images, the administrator must:

Use the cloudctl case command to configure credentials, including the IBM entitlement key, before initiating the mirroring process.

Authenticate with the IBM Container Registry using the entitlement key.

Mirror the required images from IBM’s registry to a local registry that the disconnected OpenShift cluster can access.

B. export ENTITLEMENTKEY and cloudPakOfflineInstaller -mirror-images

The command cloudPakOfflineInstaller -mirror-images is not a valid IBM Cloud Pak installation step.

IBM requires the use of cloudctl case commands for air-gapped installations.

C. Adding the entitlement key to .airgap/registries

There is no documented requirement to store the entitlement key in SHOME/.airgap/registries.

IBM Cloud Pak for Integration does not use this file for authentication.

D. Adding the ibm-entitlement-key as a Docker secret

While secrets are used in OpenShift for image pulling, they are not directly involved in mirroring images for air-gapped installations.

The entitlement key is required at the mirroring step, not when deploying the images.

Why Other Options Are Incorrect:IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

IBM Documentation: Installing Cloud Pak for Integration in an Air-Gapped Environment

IBM Cloud Pak Entitlement Key and Image Mirroring

OpenShift Air-Gapped Installation Guide

In IBM Cloud Pak Foundational Services, the audit-syslog-service is responsible for receiving audit data and collecting application logs. This service ensures that security and compliance-related events are properly recorded and made available for analysis.

The audit-syslog-service is a key component of Cloud Pak's logging and monitoring framework, specifically designed to capture audit logs from various services.

It can forward logs to external SIEM (Security Information and Event Management) systems or centralized log collection tools for further analysis.

It helps organizations meet compliance and governance requirements by maintaining detailed audit trails.

Why is audit-syslog-service the correct answer?

A. logging service (Incorrect)

While Cloud Pak Foundational Services include a logging service, it is primarily for general application logging and does not specifically handle audit data collection.

C. systemd journal (Incorrect)

systemd journal is the default system log manager on Linux but is not the dedicated service for handling Cloud Pak audit logs.

D. fluentd service (Incorrect)

Fluentd is a log forwarding agent used for collecting and transporting logs, but it does not directly receive audit data in Cloud Pak Foundational Services. It can be used in combination with audit-syslog-service for log aggregation.

Analysis of the Incorrect Options:

IBM Cloud Pak Foundational Services - Audit Logging

IBM Cloud Pak for Integration Logging and Monitoring

Configuring Audit Log Forwarding in IBM Cloud Pak

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

In IBM API Connect, which is part of IBM Cloud Pak for Integration (CP4I), the Management subsystem requires block storage with ReadWriteOnce (RWO) access mode.

The API Connect Management subsystem handles API lifecycle management, analytics, and policy enforcement.

It requires high-performance, low-latency storage, which is best provided by block storage.

The RWO (ReadWriteOnce) access mode ensures that each persistent volume (PV) is mounted by only one node at a time, preventing data corruption in a clustered environment.

IBM Cloud Block Storage

AWS EBS (Elastic Block Store)

Azure Managed Disks

VMware vSAN

Why "RWO Block Storage" is Required?Common Block Storage Options for API Connect on OpenShift:

Why the Other Options Are Incorrect?Option

Explanation

Correct?

A. NFS

❌ Incorrect – Network File System (NFS) is a shared file storage (RWX) and does not provide the low-latency performance needed for the Management subsystem.

❌

B. RWX block storage

❌ Incorrect – RWX (ReadWriteMany) block storage is not supported because it allows multiple nodes to mount the volume simultaneously, leading to data inconsistency for API Connect.

❌

D. GlusterFS

❌ Incorrect – GlusterFS is a distributed file system, which is not recommended for API Connect’s stateful, performance-sensitive components.

❌

Final Answer:✅ C. RWO block storage

IBM API Connect System Requirements

IBM Cloud Pak for Integration Storage Recommendations

Red Hat OpenShift Storage Documentation

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

In IBM Cloud Pak for Integration (CP4I) v2021.2, Identity and Access Management (IAM) is part of Foundational Services, which provides authentication and authorization across different modules within CP4I.

When configuring IAM for single sign-on (SSO), the administrator must have administrator access to the IAM service. This is essential for:

Integrating external identity providers (IdPs) such as LDAP, SAML, or OIDC.

Managing user roles and access control policies across the Cloud Pak environment.

Configuring SSO settings for seamless authentication across all IBM Cloud Pak services.

IAM service administrators have full control over authentication and SSO settings.

They can configure and integrate identity providers for authentication.

This level of access is required to modify IAM settings in Cloud Pak for Integration.

Why Answer D (Access to IAM service as administrator) is Correct?

A. Access to the OpenShift Container Platform console as kubeadmin. → Incorrect

While kubeadmin is a cluster-wide OpenShift administrator, this role does not grant IAM administrative privileges in Cloud Pak Foundational Services.

IAM settings are managed within IBM Cloud Pak, not solely through OpenShift.

B. Access to IBM Cloud Pak for Integration as kubeadmin. → Incorrect

kubeadmin can manage OpenShift resources, but IAM requires specific access to the IAM service within Cloud Pak.

IAM administrators are responsible for configuring authentication, SSO, and identity providers.

C. Access to OpenShift cluster as root. → Incorrect

Root access is not relevant here because OpenShift does not use root users for administration.

IAM configurations are done within Cloud Pak, not at the OpenShift OS level.

Explanation of Incorrect Answers:

IBM Cloud Pak Foundational Services - IAM Configuration

Configuring Single Sign-On (SSO) in IBM Cloud Pak

IBM Cloud Pak for Integration Security Overview

OpenShift Authentication and Identity Management

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:

Starting with IBM Cloud Pak for Integration (CP4I) v2021.2, which uses IBM Common Services 3.6, there are two monitoring service modes available for tracking system health and performance:

OCP Monitoring (OpenShift Container Platform Monitoring) – This is the native OpenShift monitoring system that provides observability for the entire cluster, including nodes, pods, and application workloads. It uses Prometheus for metrics collection and Grafana for visualization.

CS Monitoring (Common Services Monitoring) – This is the IBM Cloud Pak for Integration-specific monitoring service, which provides additional observability features specifically for IBM Cloud Pak components. It integrates with OpenShift but focuses on Cloud Pak services and applications.

Option B (OpenShift Common Monitoring) is incorrect: While OpenShift has a Common Monitoring Stack, it is not a specific mode for IBM CP4I monitoring services. Instead, it is a subset of OCP Monitoring used for monitoring the OpenShift control plane.

Option C (CP4I Monitoring) is incorrect: There is no separate "CP4I Monitoring" service mode. CP4I relies on OpenShift's monitoring framework and IBM Common Services monitoring.

Option E (Grafana Monitoring) is incorrect: Grafana is a visualization tool, not a standalone monitoring service mode. It is used in conjunction with Prometheus in both OCP Monitoring and CS Monitoring.

IBM Cloud Pak for Integration Monitoring Documentation

IBM Common Services Monitoring Overview

OpenShift Monitoring Stack – Red Hat Documentation

Why the other options are incorrect:IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References: