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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.
ML APIs (e.g., Vision API, Speech API)
Which project details can be added and changed by Project Administrators?
Data staging, cataloging, and discovery
Performing data preparation and quality control (e.g., Cloud Dataprep)
Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
Target Hosts Using Privileged Session Manager
What are all the various factors that influence whether a field is visible on a screen?
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?
Choosing between ACID, idempotent, eventually consistent requirements
What changes can be performed on statuses and transitions?
Identity and access management (e.g.,Cloud IAM)
Deploying an ML pipeline
When is it best to use components, and when is it best to use a custom field instead?
Impact of dependencies of machine learning models
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
Ensuring reliability and fidelity
Choosing the appropriate training and serving infrastructure
Ingesting appropriate data
Designing for security and compliance
Ensuring scalability and efficiency
Pipeline monitoring (e.g., Stackdriver)
Ensuring privacy (e.g., Data Loss Prevention API)
Securely Managing the System Architecture
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
What is the importance of the Browse Projects permission?
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 a Project Key, and what are the effects on issues in the project?
Continuous evaluation
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)
What workflow changes can be done through the board by board administrators?
Hardware accelerators (e.g., GPU, TPU)
Data security (encryption, key management)
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Use of edge compute
Which export options are available from the Issue Navigation? The following will be discussed here:
How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)
Monitoring Privileged Account Access
Ensuring flexibility and portability
Where are all the places you need to look to fully identify what permissions a particular user has?
Leveraging pre-built ML models as a service
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
Resizing and autoscaling resources
What things may need to be updated as a result of workflow changes of any kind?
Conversational experiences (e.g., Dialogflow)
Building and running test suites
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
What is an Issue Collector and what permissions are needed to configure it?
Distributed vs. single machine
Measuring, monitoring, and troubleshooting machine learning models
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?
What is the relationship between screens, screen schemes and issue type screen schemes?
Operationalizing machine learning models
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
Defining the CyberArk Privileged Account Security Solution Architecture
Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
Assessing, troubleshooting, and improving data representations and data processing infrastructure
How do combinations of permissions work together to enable specific actions?
Verification and monitoring
What are the uses of Project Category in Jira?
Mapping to current and future business requirements
Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?
Candidates already have experience with Sentry and Defender examination so it is not difficult to pass the recertifications. CAU-305 exam dumps and CAU-305 practice exams to revise the already discussed syllabus.
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Preparation Guide for CyberArk CDE Recertification CAU305 Exam
Introduction
CyberArk CDE Recertification CAU305 Exam is related to CyberArk CDE recertification.
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Privileged Session Management (PSM & PVWA) | 25% | - PVWA installation, configuration, and access control - Ad-Hoc Access and secure connection features - PSM deployment, configuration, and session recording |
| Topic 2: CyberArk Vault Architecture & Administration | 25% | - DBParm.ini, Vault.ini, and security settings - Vault installation, configuration, and hardening - Vault DR, backup, and recovery |
| Topic 3: Privileged Account Management (CPM) | 25% | - CPM deployment and configuration - Automatic password rotation and reconciliation - Platform management and policy enforcement |
| Topic 4: Defender & Sentry Security Components | 15% | - CyberArk Sentry configuration and integration - CyberArk Defender implementation |
| Topic 5: Troubleshooting & Best Practices | 10% | - Performance tuning and security compliance - Log analysis and common issue resolution |
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