C1000-168
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C1000 168 Cloud Pak Data Administrator
The C1000-168 training teaches administrators how to install, configure, and manage IBM Cloud Pak for Data v4.6, covering user access, service administration, monitoring, logging, and troubleshooting to ensure reliable, secure deployments.
90
Minutes
62
Questions
62/100
Passing Score
$200
Exam Cost
Who Should Take This
It is intended for IT professionals who serve as Cloud Pak for Data administrators, engineers, or consultants with baseline experience in Linux, container orchestration, and data services. Learners aim to validate their ability to design, operate, and optimize the platform, advancing their credentials and supporting enterprise analytics initiatives.
What's Covered
1
Domain 1: Installation and Configuration
2
Domain 2: User and Access Management
3
Domain 3: Service Administration
4
Domain 4: Monitoring and Logging
5
Domain 5: Troubleshooting and Maintenance
What's Included in AccelaStudy® AI
Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
20 Activity Formats
Course Outline
60 learning goals
1
Domain 1: Installation and Configuration
2 topics
Platform Installation
- Configure Cloud Pak for Data operator deployment on OpenShift with namespace creation and subscription management.
- Implement Cloud Pak for Data service instance provisioning with storage class selection and resource quota configuration.
- Configure persistent storage with appropriate storage classes for block, file, and object storage service requirements.
- Implement network policy configuration for Cloud Pak for Data pods with ingress, egress, and inter-service rules.
- Analyze installation prerequisites to identify storage, compute, and network requirements for planned service deployment.
- Design installation procedures with pre-validation checklists, staged deployment plans, and post-installation verification.
Service Provisioning
- Configure Cloud Pak for Data service catalog with selective enablement of Watson Studio, WKC, DataStage, and databases.
- Implement service instance configuration with compute profiles, scaling parameters, and high availability settings.
- Configure external data source connections with credential management, SSL certificates, and connectivity testing.
- Analyze service resource consumption to recommend appropriate sizing and scaling configurations for workload demands.
- Evaluate OpenShift cluster resource quotas and limit ranges to ensure Cloud Pak for Data services operate within allocated compute and memory boundaries.
2
Domain 2: User and Access Management
3 topics
Authentication
- Configure LDAP authentication integration with user group synchronization and attribute mapping for Cloud Pak for Data.
- Implement SAML 2.0 single sign-on configuration with identity provider metadata exchange and assertion mapping.
- Configure multi-factor authentication enforcement using IAM policies and external identity provider MFA capabilities.
- Analyze authentication configurations to verify security compliance and identify potential bypass or weakness vectors.
- Recommend user provisioning automation strategies that synchronize Cloud Pak for Data accounts with enterprise identity providers using SCIM or LDAP integration.
Authorization
- Configure role-based access control with platform roles, project roles, and catalog permissions for user management.
- Implement project-level access policies with collaborator management, data asset sharing, and compute environment access.
- Configure data protection rules in Watson Knowledge Catalog for column masking, row filtering, and access enforcement.
- Analyze user access patterns to identify over-privileged accounts and recommend least-privilege role assignments.
- Design user management frameworks with role hierarchies, automated provisioning, and periodic access review processes.
Storage and Persistence Management
- Configure persistent volume claims and storage classes for Cloud Pak for Data workloads across block, file, and object storage backends.
- Analyze storage utilization trends and I/O performance metrics to identify capacity constraints before they impact service availability.
- Design a storage tiering strategy that optimizes cost and performance by placing workloads on appropriate storage classes based on access patterns.
3
Domain 3: Service Administration
3 topics
Analytics Services
- Configure Watson Studio environments with runtime selection, GPU allocation, and environment variable management.
- Implement Watson Machine Learning deployment space management with model serving and batch scoring configuration.
- Configure Watson Knowledge Catalog administration with glossary management, governance policies, and asset access rules.
- Analyze service utilization metrics to recommend resource allocation adjustments and service scaling decisions.
- Design service administration procedures with lifecycle management, capacity planning, and service level tracking.
Data Services
- Configure DataStage service administration with pipeline execution management, resource allocation, and job scheduling.
- Implement database service provisioning including Db2, PostgreSQL, and data virtualization instance management.
- Configure database service backup scheduling, retention policies, and point-in-time recovery procedures.
- Analyze data service performance to identify query optimization opportunities and resource scaling requirements.
Automation and Scripting
- Configure Cloud Pak for Data administrative automation using the cpd-cli command-line tool for service provisioning, patching, and health verification.
- Analyze automation script execution logs to identify deployment failures, configuration drift, and environment inconsistencies requiring remediation.
- Design an infrastructure-as-code approach for Cloud Pak for Data administration that enables repeatable, version-controlled environment management.
4
Domain 4: Monitoring and Logging
2 topics
Platform Monitoring
- Configure Cloud Pak for Data health monitoring dashboards with service status, resource utilization, and capacity views.
- Implement alert notification configuration for critical platform events including service failures and resource exhaustion.
- Configure audit logging for user activities, data access events, and administrative operations across platform services.
- Implement integration with external monitoring systems using Prometheus metrics export and log forwarding configuration.
- Analyze monitoring data trends to identify capacity planning needs and predict resource exhaustion timeframes.
- Design monitoring frameworks with service-level dashboards, automated alerting, and capacity forecasting for operations.
Log Management
- Configure centralized log collection from Cloud Pak for Data pods with structured parsing and searchable indexing.
- Implement log retention policies with archival procedures and compliance-driven data lifecycle management.
- Analyze platform logs to identify error patterns, service degradation root causes, and configuration issues.
- Evaluate log aggregation configurations to determine optimal retention periods, index strategies, and alert thresholds for operational monitoring.
- Design a centralized logging and monitoring architecture that correlates Cloud Pak for Data platform events with OpenShift infrastructure metrics.
5
Domain 5: Troubleshooting and Maintenance
3 topics
Troubleshooting
- Implement systematic troubleshooting procedures for Cloud Pak for Data service failures with log analysis and diagnostics.
- Configure support data collection using must-gather tools for IBM Support case submission and issue documentation.
- Implement pod restart and service recovery procedures for resolving common Cloud Pak for Data operational issues.
- Analyze troubleshooting data including pod logs, events, and resource states to diagnose root causes of failures.
- Design troubleshooting runbooks with diagnostic decision trees, common resolution procedures, and escalation guidelines.
Upgrade and Backup
- Configure platform backup procedures with metadata, user data, and configuration preservation for disaster recovery.
- Implement Cloud Pak for Data upgrade procedures with pre-upgrade validation, staged execution, and rollback planning.
- Configure automated health checks for post-upgrade validation with service status verification and regression testing.
- Analyze upgrade impact and compatibility to plan migration procedures minimizing downtime and service disruption.
- Design a platform upgrade strategy for Cloud Pak for Data that sequences service updates to minimize downtime and maintain cross-service compatibility.
Disaster Recovery Administration
- Configure Cloud Pak for Data backup procedures including metadata export, persistent volume snapshots, and service configuration archival.
- Analyze disaster recovery test results to evaluate recovery time, data completeness, and service functionality after simulated failure scenarios.
- Design a disaster recovery strategy for Cloud Pak for Data that defines recovery objectives, backup schedules, and failover procedures across environments.
Scope
Included Topics
- All domains of IBM Cloud Pak for Data v4.6 Administrator (C1000-168): installation, user management, service administration, monitoring, and troubleshooting.
- Installation: Cloud Pak for Data operator deployment, service provisioning, storage configuration, and network setup.
- User management: LDAP integration, SAML SSO, role assignments, project permissions, and multi-tenancy configuration.
- Service administration: Watson Studio, Watson ML, WKC, DataStage, and database service lifecycle management.
- Monitoring: platform health dashboards, resource utilization, service status, and audit log management.
- Troubleshooting: log analysis, common issues, support data collection, and performance diagnosis procedures.
Not Covered
- Data science workflows.
- Application development.
- Non-IBM data platforms.
- OpenShift administration.
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