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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 3

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 4

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.

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Peoplecert AIOps-Foundation Practice Exams for Thorough Preparation (Desktop & Web-Based)

This way you will be able to experience the actual DevOps Institute AIOps Foundation V1.0 exam environment and become a more prepared and confident candidate to step into the examination center. You will know where exactly you stand before the actual Peoplecert AIOps-Foundation Certification Exam. The actual Peoplecert AIOps-Foundation exam questions will make you familiar with the inside-out view of the exam pattern and syllabus.

Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q19-Q24):

NEW QUESTION # 19
Which of the following technologies is deterministic?

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

Answer: D

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 # 20
Which of the MELT data types is specific to a microservices based system?

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

Answer: D

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 # 21
Targets of acceptable performance are defined in;

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

Answer: C

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 # 22
Which are core technologies used by an AlOps system?

A. Automation
B. Machine Learning
C. All of the above
D. Big Data

Answer: C

Explanation:
AIOps systems rely on a combination of technologies to achieve their goals:
* Big Data: Collects and processes vast amounts of operational data from diverse sources to ensure comprehensive analysis.
* Machine Learning (ML): Identifies patterns, anomalies, and trends within the data, enabling predictive capabilities.
* Automation: Ensures rapid and reliable responses to identified issues, enhancing efficiency and minimizing manual intervention.
The interplay of these technologies creates a cohesive system capable of dynamic, scalable, and intelligent IT operations.
As per DevOps Institute, the integration of these technologies underpins the core functionality and effectiveness of AIOps solutions.

NEW QUESTION # 23
How do SLAs relate To AlOps?

A. AlOps indicates which SLOs to define in an SLA
B. There is no relationship between AlOps and SLAs
C. AlOps automates the generation of SLA documentation
D. AlOps reduces the risk and improves SLA targets by overall improving IT Operations speed and capabilities.

Answer: D

Explanation:
Service Level Agreements (SLAs) define the expected performance and availability standards for IT services.
AIOps enhances the ability to meet and exceed these SLA targets by improving IT operations' speed and capabilities. Through the integration of big data analytics and machine learning, AIOps enables real-time monitoring, rapid issue detection, and automated responses, reducing downtime and enhancing service reliability. This proactive approach minimizes risks associated with SLA breaches and ensures that IT services consistently meet agreed-upon performance standards.

NEW QUESTION # 24
......

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