VISUAL PEOPLECERT AIOPS-FOUNDATION CERT EXAM | AIOPS-FOUNDATION VALID TEST TUTORIAL

Visual Peoplecert AIOps-Foundation Cert Exam | AIOps-Foundation Valid Test Tutorial

Visual Peoplecert AIOps-Foundation Cert Exam | AIOps-Foundation Valid Test Tutorial

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Tags: Visual AIOps-Foundation Cert Exam, AIOps-Foundation Valid Test Tutorial, AIOps-Foundation Latest Materials, Valid AIOps-Foundation Exam Topics, New AIOps-Foundation Test Dumps

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AIOps-Foundation is so flexible that you can easily change the timings, types of questions, and topics for each mock exam. Actual4Exams's DevOps Institute AIOps Foundation V1.0 practice test contains all the important questions that will appear in the actual AIOps-Foundation Exam. We design and update our Peoplecert AIOps-Foundation exam questions after receiving precious feedback. You can try a demo and sample of AIOps-Foundation exam questions before purchasing.

Peoplecert AIOps-Foundation Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • Core Technologies: Machine Learning (ML): This section of the exam measures the skills of machine learning practitioners and covers the role of AI and machine learning in AIOps. It includes discussions on supervised versus unsupervised learning, differences between ML and analytics, and training models for practical applications. A vital skill evaluated is understanding how to apply machine learning techniques to enhance operational efficiency.
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.

Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q30-Q35):

NEW QUESTION # 30
Which of the following describes MLOps?

  • A. Applying artificial intelligence to IT Operations
  • B. A set of capabilities that primarily focuses on the governance and the full life cycle management of all Al and decision models
  • C. Software that thinks like a human through analysis and reasoning to perform complex tasks
  • D. Implementing CI/CD. testing and accelerated development lifecycle to the machine learning model development

Answer: D

Explanation:
MLOps, or Machine Learning Operations, applies DevOps principles such as Continuous Integration and Continuous Deployment (CI/CD) to the development and deployment of machine learning models. This approach emphasizes automation, testing, and streamlined workflows to accelerate the machine learning lifecycle, ensuring models are reliable, reproducible, and maintainable in production environments.
The AIOps Foundation course discusses the relationship between AIOps and MLOps, highlighting how integrating these practices can enhance IT operations.


NEW QUESTION # 31
Surfacing relevant notifications and alerts from among large volumes of alerts is satisfied by this use case:

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

Answer: B

Explanation:
Alert noise reductionis the use case focused on identifying and prioritizing relevant alerts from a large volume of notifications, which helps prevent alert fatigue for IT teams.
By reducing noise, AIOps enables teams to focus on significant issues that require immediate attention, improving operational efficiency.
The DevOps Institute's AIOps Foundation course highlights this capability as a core advantage of AIOps systems.


NEW QUESTION # 32
Which of the following is a characteristic of Machine Learning?

  • A. Uses small amounts of historical data to generate accurate inferences or prediction
  • B. Gradually improves accuracy through iterative optimization
  • C. Requires explicit programming to learn
  • D. A superset of Al

Answer: B

Explanation:
Machine Learning (ML) involves algorithms that learn from data and improve their performance over time through iterative optimization. Unlike traditional programming, where explicit instructions are coded, ML models identify patterns and make predictions based on historical data, refining their accuracy as they process more information.
The AIOps Foundation course covers core technologies of machine learning, emphasizing how these models enhance IT operations by automating tasks and providing predictive insights.


NEW QUESTION # 33
The incident related metric MTTD means:

  • A. Mean time to Detect
  • B. Mean Time to Delivery
  • C. Mean Time to Distribution
  • D. Mean Time to Deployment

Answer: A

Explanation:
Mean Time to Detect (MTTD)is an incident management metric that measures the average time taken to identify an issue within a system. A lower MTTD indicates a more responsive monitoring system, allowing for quicker remediation and minimizing potential impact. Improving MTTD is crucial for maintaining system reliability and performance. The DevOps Institute's AIOps Foundation course emphasizes the importance of MTTD in evaluating the effectiveness of IT operations and the implementation of AIOps solutions to enhance detection capabilities.


NEW QUESTION # 34
Which of the MELT data types is specific to a microservices based system?

  • A. Traces
  • B. Logs
  • C. Events
  • D. Metrics

Answer: A

Explanation:
In microservices-based systems, "Traces" are a specific MELT (Metrics, Events, Logs, Traces) data type.
Traces track the flow of requests through various services, providing visibility into the interactions and performance of microservices. This tracing is crucial for diagnosing issues, understanding system behavior, and optimizing performance in complex, distributed environments. The DevOps Institute's AIOps Foundation course emphasizes the role of traces in observability practices, enabling teams to monitor and improve microservices architectures effectively.
For more detailed information, refer to the DevOps Institute's AIOps Foundation course materials.


NEW QUESTION # 35
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