Get C1000-130 Dumps : Verified IBM Cloud Pak for Integration V2021.2 Administration

The monitoring component of IBM Cloud Pak for Integration (CP4I) v2021.2 is built on Prometheus and Grafana. These tools are widely used for monitoring and visualization in Kubernetes-based environments like OpenShift.

Prometheus – A time-series database designed for monitoring and alerting. It collects metrics from different services and components running within CP4I, enabling real-time observability.

Grafana – A visualization tool that integrates with Prometheus to create dashboards for monitoring system performance, resource utilization, and application health.

A. Jaeger ? Incorrect. Jaeger is used for distributed tracing, not core monitoring.

D. Logstash ? Incorrect. Logstash is used for log processing and forwarding, primarily in ELK stacks.

E. Kibana ? Incorrect. Kibana is a visualization tool but is not the primary monitoring tool in CP4I; Grafana is used instead.

IBM Cloud Pak for Integration Monitoring Documentation

Prometheus Official Documentation

Grafana Official Documentation

Explanation of Other Options:IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:

In an air-gapped environment, the OpenShift cluster does not have direct internet access, which means that new software images, such as IBM API Connect, must be manually mirrored from an external source.

The correct approach for installing a new API Connect capability in an air-gapped OpenShift environment is to:

Use a laptop or a bastion host that does have internet access to pull required container images from IBM’s entitled software registry.

Leverage Container Application Software for Enterprises (CASE) files to download and transfer images to the private OpenShift registry.

Mirror images into the OpenShift cluster by using OpenShift’s built-in image mirror utilities (oc mirror).

This method ensures that all required container images are available locally within the air-gapped environment.

Why the Other Options Are Incorrect?Option

Explanation

Correct?

B. An OVA form-factor of the Cloud Pak for Integration is recommended for high-security deployments.

? Incorrect – IBM Cloud Pak for Integration does not provide an OVA (Open Virtual Appliance) format for API Connect deployments. It is containerized and runs on OpenShift.

?

C. A pass-through route must be configured in the OpenShift Container Platform to connect to the online image registry.

? Incorrect – Air-gapped environments have no internet connectivity, so this approach would not work.

?

D. Use secure FTP to mirror software images in the OpenShift Container Platform cluster nodes.

? Incorrect – OpenShift does not use FTP for image mirroring; it relies on oc mirror and image registries for air-gapped deployments.

?

Final Answer:? A. Configure a laptop or bastion host to use Container Application Software for Enterprises files to mirror images.

IBM API Connect Air-Gapped Installation Guide

IBM Container Application Software for Enterprises (CASE) Documentation

Red Hat OpenShift - Mirroring Images for Disconnected Environments

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:

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) 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: