CyberArk CAU305 Exam Reference
The recertification exam provides the practical knowledge and technical skills to securely design, install, and configure the CyberArk Privileged Access Security Solution. The candidates will gain valuable hands-on experience installing CyberArk components, configuring Authentication Types, and System Integrations (SIEM, SMTP, SNMP), using our step-by-step exercise guide, official product documentation and a dedicated lab environment.
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Candidates must know the Defender + Sentry exam topics before they start of preparation because it will really help them in hitting the core. Our CAU-305 practice test and CAU-305 practice exams will include the following topics. These are covered in our CAU-305 exam dumps.
Ingesting appropriate data
Pipeline monitoring (e.g., Stackdriver)
Conversational experiences (e.g., Dialogflow)
Data security (encryption, key management)
Defining the CyberArk Privileged Account Security Solution Architecture
Measuring, monitoring, and troubleshooting machine learning models
What is an Issue Collector and what permissions are needed to configure it?
What is the importance of the Browse Projects permission?
Resizing and autoscaling resources
Target Hosts Using Privileged Session Manager
What changes can be performed on statuses and transitions?
Distributed vs. single machine
Building and running test suites
Ensuring reliability and fidelity
Which project details can be added and changed by Project Administrators?
Data staging, cataloging, and discovery
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Hardware accelerators (e.g., GPU, TPU)
Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?
Choosing the appropriate training and serving infrastructure
What things may need to be updated as a result of workflow changes of any kind?
Verification and monitoring
Where are all the places you need to look to fully identify what permissions a particular user has?
Ensuring flexibility and portability
Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
Who can change a Project Key, and what are the effects on issues in the project?
Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
Assessing, troubleshooting, and improving data representations and data processing infrastructure
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
How do combinations of permissions work together to enable specific actions?
Securely Managing the System Architecture
Operationalizing machine learning models
What workflow changes can be done through the board by board administrators?
What is the relationship between screens, screen schemes and issue type screen schemes?
What are the use cases where it is best to use Project Roles rather than Groups?
Common sources of error (e.g., assumptions about data)
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
Identity and access management (e.g.,Cloud IAM)
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
ML APIs (e.g., Vision API, Speech API)
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
Impact of dependencies of machine learning models
Performing data preparation and quality control (e.g., Cloud Dataprep)
Continuous evaluation
What are all the various factors that influence whether a field is visible on a screen?
Use of edge compute
Choosing between ACID, idempotent, eventually consistent requirements
Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
Leveraging pre-built ML models as a service
Deploying an ML pipeline
What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
What types of workflow changes can Project Administrators make if Extended Project Administration is activated?
Designing for security and compliance
Ensuring scalability and efficiency
Mapping to current and future business requirements
How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)
What are the uses of Project Category in Jira?
What are the configuration options for all the out-of-box reports and gadgets (except Agile reports and gadgets)? What is their behavior and expected results?
Which export options are available from the Issue Navigation? The following will be discussed here:
Monitoring Privileged Account Access
Ensuring privacy (e.g., Data Loss Prevention API)
When is it best to use components, and when is it best to use a custom field instead?
| Section | Objectives |
|---|---|
| Topic 1: Advanced Security and Use Cases | - Privilege threat analytics overview - Security best practices in PAS - Session management and PSM usage |
| Topic 2: Operations and Maintenance | - Upgrades and patch management - Backup and restore procedures - Monitoring and troubleshooting |
| Topic 3: Privileged Access Management Fundamentals | - Core components (Vault, PVWA, CPM, PSM) - CyberArk PAS architecture overview |
| Topic 4: Implementation and Configuration | - Platform management and onboarding - Vault deployment and configuration - Safe management and permissions |
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