C1000-147 IBM Cloud Pak for Integration V2021.4 Solution Architect Practice Questions

The Cloud Pak for Integration licensing model provides a single, flexible entitlement. Customers purchase a quantity of CP4I VPCs, and this pool of licenses can be used to deploy any of the included capabilities. Each capability consumes VPCs from the pool at a specific ratio (e.g., 1 VPC of API Connect might consume 1 license VPC, while 2 VPCs of MQ might consume 1 license VPC). This allows customers to flexibly shift their license usage between capabilities as their needs change.

Automation assets (formerly known as the Asset Repository) provides a central location to store and govern reusable assets such as API specifications, integration templates, schemas, and policies. This promotes reuse, consistency, and collaboration across development teams working with the Cloud Pak for Integration.

KEDA is designed specifically for event-driven autoscaling. It extends the standard Kubernetes HPA with triggers based on external metrics. The KEDA IBM MQ scaler can monitor the depth of a specific queue and automatically scale the number of pods (in this case, ACE pods) up or down based on configured thresholds. This is the ideal solution for scaling based on application-specific metrics like queue depth.

This statement is true. Public cloud providers offer highly available, performant, and managed block storage services (like AWS EBS, Azure Disk, GCP Persistent Disk) that integrate seamlessly with their managed Kubernetes/OpenShift offerings. These services are the standard and recommended choice for provisioning RWO volumes as they are optimized for performance and reliability within that cloud ecosystem.

OpenShift's logging subsystem is based on the EFK stack (Elasticsearch, Fluentd, Kibana). Fluentd runs as a DaemonSet on each node, collecting container logs. To forward these logs to an external system like Splunk, the standard approach is to configure the ClusterLogging custom resource or deploy a custom Fluentd configuration. This configuration will define an output pipeline that sends the collected logs to the Splunk endpoint, typically using the HTTP Event Collector (HEC).

To achieve high availability across availability zones for IBM MQ with no data loss, a multi-instance queue manager is the recommended pattern. This requires a shared file system that can be accessed by multiple pods simultaneously, which is provided by a ReadWriteMany (RWX) storage class. A StatefulSet is used to ensure stable network identifiers and ordered deployment for the active and standby queue manager instances.

A key principle of agile integration is moving away from a central, monolithic ESB to decentralized, fine-grained integration runtimes. This empowers application teams to manage their own integrations, promoting agility and reducing bottlenecks.

Exposing business capabilities through managed APIs is a cornerstone of modern integration. Using API Connect as a gateway provides security, control, and discoverability for these services, enabling a modern API-led approach.

NetworkPolicy is a Kubernetes/OpenShift resource that controls the traffic flow at the IP address or port level (OSI layer 3 or 4). A NetworkPolicy object can be defined to create an ingress rule for the cp4i-mq namespace that explicitly allows traffic from pods in the cp4i-ace namespace to TCP port 1414, while denying all other traffic by default. This is the standard mechanism for implementing network segmentation and zero-trust principles within an OpenShift cluster.

This statement is true. The Operations Dashboard integrates with CP4I capabilities like App Connect Enterprise and MQ. It leverages OpenTracing standards and built-in probes to automatically generate and correlate trace data as messages pass between these components. This allows for end-to-end visibility without requiring developers to manually add tracing instrumentation to their integration logic.

Kafka is optimized for high-volume, sequential writes as it appends messages to log files. Therefore, the underlying storage system's ability to sustain high sequential write throughput is the most critical performance factor. While read performance is important for consumers, the write performance is paramount for the brokers to handle ingress traffic without becoming a bottleneck.