Newly Released IBM C1000-130 Exam PDF

The command executed is:

sh

CopyEdit

oc get po

This command lists the pods running in an OpenShift (OCP) cluster where IBM API Connect is deployed.

Most API Connect management components (apic-dev-mgmt-xxx) are in a Running state, which indicates that the core API Connect system is operational.

The apic-dev-mgmt-turnstile pod is in a CrashLoopBackOff state, with 301 restarts, indicating that this component has repeatedly failed to start properly.

The Turnstile pod is a critical component of the IBM API Connect Developer Portal.

It manages authentication and access control for the Developer Portal, ensuring that API consumers can access the portal and manage API subscriptions.

When Turnstile is failing, the Developer Portal becomes unresponsive because authentication requests cannot be processed.

Key Observations from the Output:Understanding the Turnstile Component:

Since the Turnstile pod is failing, the Developer Portal will not function properly, preventing users from accessing API documentation and managing API subscriptions.

API providers and consumers will not be able to log in or interact with the Developer Portal.

Why Answer B is Correct?

A. The Analytics subsystem cannot retain historical data. → Incorrect

The Analytics-related pods (e.g., apic-dev-analytics-xxx) are in a Running state.

If the Analytics component were failing, metrics collection and historical API call data would be impacted, but this is not indicated in the output.

C. Automated API behavior testing has failed. → Incorrect

There is no evidence in the pod list that API testing-related components (such as test clients or monitoring tools) have failed.

D. New API calls will be rejected by the gateway service. → Incorrect

The gateway service is not shown as failing in the provided output.

API traffic flows through the Gateway pods (typically apic-gateway-xxx), and they appear to be running fine.

If gateway-related pods were failing, API call processing would be affected, but that is not the case here.

Explanation of Incorrect Answers:

IBM API Connect Deployment on OpenShift

Troubleshooting Developer Portal Issues

Understanding API Connect Components

OpenShift Troubleshooting Pods

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:

In IBM Cloud Pak for Integration (CP4I) v2021.2, which runs on Red Hat OpenShift, logging is managed through the OpenShift Logging Operator. This operator is responsible for collecting, storing, and forwarding logs within the cluster.

The OpenShift Logging Operator monitors a specific Custom Resource (CR) named ClusterLogging, which defines the logging stack configuration.

The ClusterLogging CR is used to configure and manage the cluster-wide logging stack, including components like:

Fluentd (Log collection and forwarding)

Elasticsearch (Log storage and indexing)

Kibana (Log visualization)

Administrators define log collection, storage, and forwarding settings using this CR.

How the ClusterLogging Custom Resource Works:Example of a ClusterLogging CR Definition:apiVersion: logging.openshift.io/v1

kind: ClusterLogging

metadata:

name: instance

namespace: openshift-logging

spec:

managementState: Managed

logStore:

type: elasticsearch

retentionPolicy:

application:

maxAge: 7d

collection:

type: fluentd

This configuration sets up an Elasticsearch-based log store with Fluentd as the log collector.

The OpenShift Logging Operator monitors the ClusterLogging CR to manage logging settings.

It defines how logs are collected, stored, and forwarded across the cluster.

IBM Cloud Pak for Integration uses this CR when integrating OpenShift’s logging system.

Why Answer A (ClusterLogging) is Correct?

B. DefaultLogging → Incorrect

There is no such resource named DefaultLogging in OpenShift.

The correct resource is ClusterLogging.

C. ElasticsearchLog → Incorrect

Elasticsearch is the default log store, but it is managed within ClusterLogging, not as a separate CR.

D. LoggingResource → Incorrect

This is not an actual OpenShift CR related to logging.

Explanation of Incorrect Answers:

OpenShift Logging Overview

Configuring OpenShift Cluster Logging

IBM Cloud Pak for Integration - Logging and Monitoring

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: