REAL PEOPLECERT AIOPS-FOUNDATION EXAM QUESTIONS - BEST WAY TO GET SUCCESS

Real Peoplecert AIOps-Foundation Exam Questions - Best Way To Get Success

Real Peoplecert AIOps-Foundation Exam Questions - Best Way To Get Success

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implementing AIOps: This section of the exam measures the skills of project managers and covers challenges, trends, and ethical considerations organizations may face when deploying an AIOps initiative. It emphasizes strategic planning for successful implementation while addressing potential risks.
Topic 2
  • Core Technologies: Big Data: This section of the exam measures the skills of data engineers and covers an introduction to Big Data, including its definition, characteristics, and the Five V's (Volume, Velocity, Variety, Veracity, and Value). It also addresses various data sources and types relevant to AIOps. A key skill assessed is identifying different types of data utilized in AIOps environments.
Topic 3
  • AIOps and Operations Metrics: This section of the exam measures the skills of performance analysts and covers industry-standard metrics used to quantify the outcomes of implementing AIOps solutions.
Topic 4
  • AIOps Use Cases and Organisational Mindset: This section of the exam measures the skills of the target audience and covers the challenges and opportunities associated with applying AIOps within organizations. It focuses on fostering an organizational mindset that embraces innovation through AIOps.
Topic 5
  • AIOps in the Organisation: This section of the exam measures the skills of organizational leaders and covers how AIOps can be integrated into existing frameworks. It discusses the impact of AIOps on DevOps practices, site reliability, security measures, and managing system complexity. A critical skill evaluated is recognizing the organizational changes required for successful AIOps implementation.
Topic 6
  • AIOps Fundamentals: This section of the exam measures the skills of IT operations professionals and covers the evolution of AIOps, differentiating it from IT Operations Analytics. It also explores the current stages of an AIOps system and its significance in modern IT environments. A key skill assessed is understanding the foundational concepts that drive AIOps adoption.

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q39-Q44):

NEW QUESTION # 39
Systems operation became elastic and dynamic thanks to:

  • A. Linux
  • B. Machine Learning
  • C. Adoption of thecloud
  • D. Contamenzation

Answer: C

Explanation:
The adoption of cloud computing has transformed system operations, making them more elastic and dynamic.
Cloud platforms provide on-demand resource allocation, enabling systems to scale up or down based on workload requirements. This elasticity allows organizations to efficiently manage resources, reduce costs, and respond swiftly to changing demands. The dynamic nature of cloud services supports continuous integration and deployment, enhancing operational agility. The DevOps Institute's AIOps Foundation course emphasizes the significance of cloud adoption in modernizing IT operations and achieving operational excellence.


NEW QUESTION # 40
How should the initial AlOps scope be defined?

  • A. All inclusive of organizational wide long term objectives
  • B. All of the above
  • C. Small but meaningful scope that will provide data points to validate success
  • D. AlOps implementation is iterative and should not have a defined scope

Answer: C

Explanation:
Defining an initial AIOps scope that is small yet meaningful allows organizations to pilot the implementation, gather valuable data, and assess its effectiveness. This approach facilitates:
* Validation: Assessing the success of the AIOps deployment in a controlled environment.
* Iterative Improvement: Making informed adjustments before broader implementation.
* Resource Management: Efficient allocation of resources and minimizing potential risks.
Starting with a focused scope enables organizations to build confidence and expertise, paving the way for successful, scaled AIOps adoption.
AIOps aims to improve incident-related metrics by:
* Decreasing Mean Time to Acknowledge (MTTA): Faster detection and acknowledgment of issues.
* Decreasing Mean Time to Resolve (MTTR): Quicker resolution through automation and actionable insights.
* Increasing Mean Time Between Failures (MTBF): Enhanced system reliability and reduced frequency of failures.
These improvements lead to more reliable IT operations, as highlighted in the DevOps Institute's AIOps Foundation course.


NEW QUESTION # 41
Targets of acceptable performance are defined in;

  • A. SLAs
  • B. SLOs
  • C. KPIs
  • D. SLIs

Answer: B

Explanation:
Service Level Objectives (SLOs)define specific, measurable targets for acceptable performance of a service.
They are critical components ofService Level Agreements (SLAs), providing clear benchmarks for service reliability and availability. By setting SLOs, organizations can align operational performance with business goals and customer expectations. The DevOps Institute's AIOps Foundation course outlines how establishing and monitoring SLOs is essential for effective service management and how AIOps can assist in meeting these objectives through enhanced monitoring and predictive analytics.


NEW QUESTION # 42
Discovering unexpected changes in system behavior or performance is satisfied by this use case:

  • A. Alert noise reduction
  • B. Event correlation
  • C. Root cause analysis
  • D. Anomaly detection

Answer: D

Explanation:
Anomaly detectionrefers to identifying unexpected changes or deviations in system behavior or performance.
This use case is essential for proactively detecting issues that may not have predefined patterns or signatures, enabling faster incident resolution.
The DevOps Institute's AIOps Foundation materials describe anomaly detection as a key feature of AIOps platforms to enhance monitoring capabilities.


NEW QUESTION # 43
Which of the following technologies is deterministic?

  • A. Analytics
  • B. Machine Learning
  • C. Artificial Intelligence
  • D. Neural networks

Answer: A

Explanation:
Deterministic technologies operate with predictable outcomes based on specific inputs. Analytics is a deterministic process, as it involves the systematic analysis of data to produce consistent and repeatable results. Given the same data set and analytical methods, analytics will yield the same conclusions, making it a deterministic approach. In contrast, technologies like machine learning, artificial intelligence, and neural networks are probabilistic, as they involve learning from data and making inferences that may vary with different inputs or training processes.


NEW QUESTION # 44
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