Portworx-Enterprise-Professional Pure Certified Portworx Enterprise Professional (PEP) Exam Question and Answers

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Dynamic Provisioning in Kubernetes with Portworx StorageClasses enables automatic, on-demand creation of storage volumes as requested by applications through Persistent Volume Claims (PVCs). This eliminates the need for administrators to manually create and manage volumes, significantly improving operational efficiency and accelerating application deployment. StorageClasses encapsulate parameters such as replication, encryption, and IO profiles, ensuring consistent volume configuration. Dynamic Provisioning also supports scaling and workload agility by provisioning storage transparently based on application needs. This feature is central to cloud-native storage management and is well documented in both Kubernetes and Portworx installation guides. It contrasts with manual volume creation, which is labor-intensive and error-prone, thus dynamic provisioning enhances automation and simplifies storage lifecycle management【Pure Storage Portworx Kubernetes Guide†source】.

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Labeling Kubernetes nodes with rack information is achieved using the kubectl label nodes command. The syntax would be something like kubectl label nodes px/rack=. This label allows Portworx to understand the physical or logical topology of nodes, enabling placement strategies that optimize data locality, fault tolerance, and availability based on rack awareness. Taints and annotations serve different purposes; taints affect pod scheduling by repelling pods, while annotations provide metadata without influencing scheduling. Portworx uses node labels extensively for topology-aware volume placement and disaster recovery planning. Official Portworx documentation recommends labeling nodes with topology identifiers like rack or zone to enable advanced placement strategies and maintain application resiliency in distributed environments【Pure Storage Portworx Placement Guide†source】.

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Telemetry in Portworx refers to the automated collection and reporting of cluster performance and health metrics to Pure1 or other monitoring services. To enable telemetry, the spec.telemetry.enabled flag must be set to true in the StorageCluster Custom Resource Definition (CRD). This setting activates the telemetry pod on each node, which collects data such as resource usage, storage capacity, and errors, then securely uploads it to Pure Storage’s management platform. Enabling telemetry helps administrators gain insights into cluster performance trends, preemptively identify issues, and optimize resource utilization. The Portworx operator respects this flag during installation and upgrades to ensure telemetry is consistently configured. Neither spec.autopilot.enabled (which controls the Autopilot feature) nor spec.csi.enabled (which controls CSI driver deployment) affects telemetry settings. Official Portworx documentation highlights this flag as critical for activating health monitoring and analytics features within Portworx clusters【Pure Storage Portworx Telemetry Guide†source】.

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Portworx classifies alerts into three main severity levels to help administrators prioritize response actions. These levels are INFO, WARNING, and CRITICAL. INFO alerts provide informational messages about non-critical events, such as configuration changes or normal operational milestones. WARNING alerts indicate potential issues that could impact performance or availability if left unaddressed, such as increased latency or approaching capacity limits. CRITICAL alerts signal severe problems requiring immediate attention, such as node failures or data corruption risks. This severity categorization supports effective alert management and escalation policies, allowing operational teams to focus on high-impact issues first. The Portworx observability and alerting guide explains these levels in detail and recommends integrating alerts with external monitoring systems for centralized management【Pure Storage Portworx Alerting Guide†source】.

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Portworx implements Role-Based Access Control (RBAC) to secure management operations within the cluster. One of the key built-in roles is system.admin, which has full administrative privileges across Portworx resources. This role allows users to manage storage nodes, volumes, snapshots, backups, and cluster-wide settings. The system.admin role is typically assigned to trusted cluster operators or administrators responsible for cluster maintenance and configuration. Other roles like storage.manager or storage.admin are not standard built-in roles in Portworx RBAC but may be custom roles defined in some environments. The official Portworx security and RBAC documentation details system.admin as the comprehensive administrative role with full cluster management capabilities, critical for secure operations and delegation of responsibilities【Pure Storage Portworx Security Guide†source】.

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To verify a Portworx upgrade on Kubernetes, administrators use the pxctl get storagenodes command. This Portworx CLI command lists all storage nodes with detailed information including version, status, and health. By inspecting the version column, administrators can confirm whether all nodes have been successfully upgraded to the desired Portworx release. This command specifically queries Portworx daemons for accurate cluster version details, unlike kubectl get nodes which shows Kubernetes node info but not Portworx versioning. Portworx upgrade best practices stress using pxctl commands for detailed verification after an upgrade to ensure consistent cluster software versions and successful upgrade completion【Pure Storage Portworx Upgrade Guide†source】.

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Upgrading Portworx clusters managed by the Kubernetes Operator requires a declarative update to the StorageCluster Custom Resource Definition (CRD). Specifically, the administrator must edit the StorageCluster resource and update the .spec.image field to point to the new version image, such as changing portworx/oci-monitor:3.0 to portworx/oci-monitor:3.1. This change instructs the Operator to roll out the new image across the cluster nodes, performing a seamless upgrade with minimal downtime. The pxctl CLI does not perform upgrades in Operator-managed environments; it is primarily for direct cluster management. The Operator ensures orderly upgrade sequencing, node by node, handling pod restarts and health checks. Automatic upgrades without manual intervention are not currently supported to prevent unintentional disruptions. Official Portworx upgrade documentation details this procedure, emphasizing the importance of version pinning and controlled rollout for production stability and rollback capabilities during upgrades【Pure Storage Portworx Upgrade Guide†source】.

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The command pxctl cluster status provides a concise summary of the Portworx cluster’s health and operational status. This includes node states, storage pool information, volume statuses, and quorum information. It is the primary CLI command for administrators to quickly assess cluster health and detect any issues affecting storage availability or performance. helm list --px is a Helm package management command unrelated to cluster status, and kubectl get pxstatus is not a valid Kubernetes or Portworx command. Portworx documentation recommends pxctl cluster status as an essential monitoring command during routine operations and troubleshooting to ensure the cluster is functioning properly and that all nodes are communicating and healthy【Pure Storage Portworx CLI Guide†source】

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To collect a comprehensive support bundle for Portworx Autopilot, the proper procedure is to create a dedicated directory, send a support signal to the running Autopilot process to trigger diagnostics collection, and then the generated support bundle files from that directory. This approach ensures all relevant Autopilot logs, configuration files, and runtime metrics are gathered in a structured way, enabling effective troubleshooting and root cause analysis. Simply restarting or deleting pods is insufficient, as it does not guarantee a full diagnostics capture. The Portworx troubleshooting and support documentation outlines this method as the standard for collecting detailed Autopilot support information, facilitating accelerated support response and issue resolution in production clusters【Pure Storage Portworx Support Guide†source】.

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To ensure Portworx volumes for an ElasticSearch application are created only on specific Kubernetes nodes, the Volume Placement Strategy feature is used. This feature allows administrators to define node affinity or anti-affinity rules that restrict volume provisioning to a subset of nodes. By tagging the six nodes with appropriate labels and configuring the StorageClass or volume parameters to respect these labels, Portworx guarantees that volumes will only be provisioned on those nodes. This targeted volume placement is critical for performance optimization, data locality, and compliance with infrastructure constraints. Autopilot automates scaling and Stork manages storage-aware scheduling but does not directly control volume node placement. The Portworx deployment documentation highlights Volume Placement Strategy as the tool for precise volume-to-node mapping in Kubernetes clusters【Pure Storage Portworx Deployment Guide†source】.

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The StorageCluster Custom Resource Definition (CRD) is the central object used to configure and manage a Portworx installation on Kubernetes. It contains essential parameters including cluster-wide settings, KVDB configuration, storage pool definitions, security options, and CSI driver configurations. The StorageCluster resource declaratively defines how Portworx should be deployed, upgraded, and operated within the Kubernetes cluster. Administrators edit this object to adjust configurations, enabling features like telemetry, monitoring, and cloud integration. Unlike VolumeSnapshot (which manages snapshots) or ServiceAccount (which controls Kubernetes permissions), StorageCluster governs the overall lifecycle and parameters of the Portworx deployment. Portworx operator documentation identifies StorageCluster as the fundamental CRD for installation and configuration management【Pure Storage Portworx Operator Guide†source】.

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The VolumeSnapshot Kubernetes resource provides metadata about snapshots of Persistent Volumes, including references to the parent volume and snapshot IDs. It represents a snapshot request and maintains information linking it to the source PVC and the actual snapshot data. This resource enables Kubernetes-native management of volume snapshots, allowing users to create, delete, and list snapshots declaratively. Portworx integrates with Kubernetes snapshot APIs and populates VolumeSnapshot resources with detailed information necessary for managing snapshot lifecycle and restoring data. The Kubernetes and Portworx documentation highlight VolumeSnapshot as the primary interface to monitor and interact with snapshot metadata, crucial for backup, restore, and disaster recovery workflows in containerized environments【Pure Storage Portworx Snapshot API Guide†source】.

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The Kubernetes secret named px-kvdb-auth is used to store external KVDB certificates in a Portworx deployment. These certificates enable mutual TLS authentication for the KVDB pods, ensuring secure and authenticated communication between the distributed KVDB instances running on different nodes. The px-kvdb-auth secret includes private keys and certificate chains that are essential for encrypting KVDB traffic and verifying peer identities within the cluster. This security feature prevents unauthorized access and protects sensitive KVDB data in transit. Portworx’sofficial security and KVDB documentation detail the use of this secret, highlighting its role in certificate management and enabling encryption for high-availability clusters running on Kubernetes environments【Pure Storage Portworx Security Guide†source】.

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The DriveStateChange alert in Portworx indicates that free disk space on a storage device has fallen below the recommended threshold of 10%. This alert warns administrators that storage capacity on a particular disk is critically low and that immediate action may be needed to avoid performance degradation or failures. Monitoring disk space is essential to maintain cluster health and prevent data loss. Portworx automatically generates this alert as part of its proactive monitoring system, providing early warning so operators can add capacity, remove unnecessary data, or re-balance workloads. The alert documentation advises maintaining sufficient free space to ensure optimal performance and data durability in the Portworx cluster【Pure Storage Portworx Alerting Guide†source】.

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Stork (Storage Orchestrator for Kubernetes) is a Portworx utility designed to improve Kubernetes storage orchestration. Its two main components are the Stork scheduler and the Stork extender. The scheduler works by placing pods in Kubernetes clusters based on storage constraints, such as volume affinity and anti-affinity, improving application resiliency and data locality. The extender integrates with Kubernetes’ default scheduler, influencing pod scheduling decisions to respect storage policies and optimize workload placement. Together, these components enable advanced features such as application-aware migration, snapshot management, and backup coordination. Portworx documentation explains that Stork’s design helps maintain stateful application availability during scaling, upgrades, or disaster recovery scenarios by making Kubernetes scheduling storage-aware【Pure Storage Portworx Stork Guide†source】.

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Portworx’s Volume Placement Strategy ensures that persistent volumes are co-located with the pods that use them, enhancing performance and reducing latency. This strategy involves applying placement rules and constraints that guide Kubernetes scheduler and Portworx storage operations to place data volumes on nodes close to or the same as the pods. Co-location improves I/O throughput and application responsiveness by minimizing network hops between compute and storage resources. While Autopilot automates scaling and Stork manages storage-aware scheduling, Volume Placement Strategy specifically handles volume location relative to workloads. The Portworx architecture documentation highlights this component as critical for optimizing storage efficiency and workload performance in Kubernetes environments running Portworx storage【Pure Storage Portworx Architecture Docs†source】.

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Portworx alerts are generated for several resource types within the storage cluster environment, primarily including Nodes, Disks, Pods, Namespaces, and Volumes. These alerts provide real-time notifications of events such as node failures, disk health degradation, volume status changes, pod crashes, or namespace-level issues affecting storage consumption or performance. Monitoring these resource types helps administrators proactively manage cluster health, maintain high availability, and troubleshoot faults before they impact applications. The Portworx alerting framework aggregates data from these resources and integrates with external monitoring systems for centralized alert management. Official Portworx observability and alerting documentation list these resource categories as the core focus of Portworx alerting mechanisms, critical for operational awareness and automation【Pure Storage Portworx Observability Guide†source】.

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A local snapshot in Portworx refers to a point-in-time of a volume’s data that is stored within the same storage cluster as the original volume. Local snapshots use efficient -on-write techniques to minimize storage overhead while preserving the volume state for backup, recovery, or rollback operations. Unlike cloud or remote snapshots, local snapshots do not require network transfer or object storage integration, enabling fast snapshot creation and restoration with low latency. They are ideal for short-term data protection, testing, or recovery scenarios where immediate access to snapshots is required. Portworx’s snapshot documentation describes local snapshots as the foundational snapshot type, essential for operational backups and data consistency within Kubernetes clusters using Portworx storage【Pure Storage Portworx Snapshot Guide†source】.

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The recommended approach to managing Portworx snapshots is to configure retention policies that automatically govern the lifecycle of snapshots, including their expiration and deletion. These policies ensure that snapshots are retained only as long as needed, preventing uncontrolled accumulation that can consume excessive storage and degrade performance. By setting retention rules, administrators can automate snapshot cleanup, enforce compliance requirements, and optimize resource usage. Manual deletion is error-prone and inefficient at scale, and retaining all snapshots indefinitely can lead to capacity exhaustion and management challenges. Portworx documentation provides detailed guidance on defining snapshot retention schedules, including time-based expiration and count limits, enabling administrators to maintain a balance between data protection and storage efficiency【Pure Storage Portworx Snapshot Management Guide†source】.