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How to Prepare for CyberArk CDE Recertification CAU305 Exam

Preparation Guide for CyberArk CDE Recertification CAU305 Exam

Introduction

CyberArk CDE Recertification CAU305 Exam is related to CyberArk CDE recertification.

This program is specially designed for aspirants who are really interested in earning CyberArk stars and can start working as PAM technology experts. This shows knowledge of end to end implementation of CyberArk Privilege Access Security Solution.

Vault Administrators, IT Personnel, CyberArk PAS Consultants usually hold or pursue this certification and you can expect the same job role after completion of this certification.

The CyberArk Certification Program offers a variety of options to those who want recognition for their technical expertise. The CyberArk Certification Program, hosted and proctored by Pearson VUE*, offers multi-level industry certifications covering privileged account security. CyberArk offers certifications designed for various roles and experience, each introducing progressively more advanced and challenging material and exams. You can work up to the level that best aligns with your responsibilities and career ambitions.

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Who should take the CAU305 exam

The CyberArk CDE certification is valid for 18 months. Certified Delivery Engineers will get automatic notifications 6 months and 3 months before their certification is expired. To get re-certified, CyberArk Certified Delivery Engineers should pass the CAU305: CyberArk CDE Recertification exam.

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CAU305 Exam topics

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.

• 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?

• What are all the various factors that influence whether a field is visible on a screen?

• Distributed vs. single machine

• Ensuring scalability and efficiency

• Hardware accelerators (e.g., GPU, TPU)

• Ensuring reliability and fidelity

• Identity and access management (e.g.,Cloud IAM)

• Pipeline monitoring (e.g., Stackdriver)

• Assessing, troubleshooting, and improving data representations and data processing infrastructure

• What is an Issue Collector and what permissions are needed to configure it?

• Ensuring privacy (e.g., Data Loss Prevention API)

• Impact of dependencies of machine learning models

• Choosing the appropriate training and serving infrastructure

• Resizing and autoscaling resources

• What changes can be performed on statuses and transitions?

• What are the uses of Project Category in Jira?

• Measuring, monitoring, and troubleshooting machine learning models

• Target Hosts Using Privileged Session Manager

• Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)

• Which export options are available from the Issue Navigation? The following will be discussed here:

• Use of edge compute

• Performing data preparation and quality control (e.g., Cloud Dataprep)

• Which project details can be added and changed by Project Administrators?

• Verification and monitoring

• Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?

• How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)

• What workflow changes can be done through the board by board administrators?

• Ensuring flexibility and portability

• Securely Managing the System Architecture

• What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?

• Deploying an ML pipeline

• Common sources of error (e.g., assumptions about data)

• Defining the CyberArk Privileged Account Security Solution Architecture

• Operationalizing machine learning models

• 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))

• Mapping to current and future business requirements

• What types of workflow changes can Project Administrators make if Extended Project Administration is activated?

• Monitoring Privileged Account Access

• Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)

• Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?

• Who can change a Project Key, and what are the effects on issues in the project?

• Customizing ML APIs (e.g., AutoML Vision, Auto ML text)

• Data staging, cataloging, and discovery

• Leveraging pre-built ML models as a service

• ML APIs (e.g., Vision API, Speech API)

• Continuous evaluation

• Data security (encryption, key management)

• Designing for security and compliance

• What are the use cases where it is best to use Project Roles rather than Groups?

• What is the relationship between screens, screen schemes and issue type screen schemes?

• Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)

• Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?

• When is it best to use components, and when is it best to use a custom field instead?

• How do combinations of permissions work together to enable specific actions?

• Ingesting appropriate data

• Designing for data and application portability (e.g., multi-cloud, data residency requirements)

• Building and running test suites

• What things may need to be updated as a result of workflow changes of any kind?

• Where are all the places you need to look to fully identify what permissions a particular user has?

• Choosing between ACID, idempotent, eventually consistent requirements

• What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?

• Conversational experiences (e.g., Dialogflow)

CyberArk CAU305 Exam Syllabus Topics: