2025 Peoplecert AIOps-Foundation: DevOps Institute AIOps Foundation V1.0 Newest New Exam Online

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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	Evaluating AIOps Impact: This section of the exam measures the skills of professionals and covers methods for measuring the effectiveness of AIOps deployments. It discusses how to assess potential benefits such as improved efficiency and reduced operational costs.
Topic 3	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 4	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 5	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.

Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q12-Q17):

NEW QUESTION # 12
Which of the MELT data types is specific to a microservices based system?

A. Events
B. Metrics
C. Logs
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 # 13
Reactive Operations rely on:

A. Lagging indicators
B. Leading indicators
C. Big Data
D. Prediction and inference

Answer: A

Explanation:
Reactive operations focus on responding to incidents after they have occurred, relying on lagging indicators- metrics that reflect past events or performance. These indicators, such as system downtime reports or post- incident analyses, provide insights into issues that have already impacted the system. While useful for understanding and addressing past problems, reliance solely on lagging indicators can lead to delayed responses and prolonged downtime. AIOps aims to shift operations from reactive to proactive by utilizing leading indicators and predictive analytics to anticipate and prevent issues before they occur.

NEW QUESTION # 14
Which is the MOST pressing reason IT professionals look to become effective in operating systems?

A. Mergers and Acquisitions
B. Increasingly demanding user expectations
C. Risk to reductions in force
D. Constantly changing IT Landscape

Answer: B

Explanation:
IT professionals strive to become more effective in operating systems primarily due to increasingly demanding user expectations. Users today expect seamless, high-performing, and reliable digital experiences.
To meet these expectations, IT operations must adopt advanced tools and methodologies, such as AIOps, to enhance system performance, ensure uptime, and quickly resolve issues. By implementing AIOps, organizations can proactively manage IT operations, anticipate user needs, and deliver superior service quality, thereby meeting the high expectations of modern users.
In today's rapidly evolving digital landscape, IT professionals face numerous challenges that necessitate proficiency in operating systems. Among these challenges, the most pressing reason is theincreasingly demanding user expectations.
Understanding User Expectations:
Users today expect seamless, efficient, and uninterrupted digital experiences. This expectation spans across various platforms and services, including web applications, mobile apps, and enterprise software. Any downtime, lag, or inefficiency can lead to user dissatisfaction, potentially resulting in loss of business and reputation.
Impact on IT Operations:
To meet these high expectations, IT professionals must:
* Ensure System Reliability:Maintain consistent uptime and quickly address any system failures.
* Optimize Performance:Continuously monitor and enhance system performance to provide fast and responsive user experiences.
* Implement Robust Security Measures:Protect user data and ensure privacy to build and maintain trust.
Role of AIOps in Addressing User Expectations:
Artificial Intelligence for IT Operations (AIOps) plays a pivotal role in enabling IT professionals to meet and exceed user expectations. By leveraging AIOps, organizations can:
* Automate Monitoring and Incident Response:Utilize machine learning algorithms to detect anomalies and address issues proactively, minimizing downtime and enhancing user satisfaction.
* Predict and Prevent Potential Issues:Analyze historical data to forecast potential system failures and implement preventive measures.
* Optimize Resource Allocation:Ensure that system resources are efficiently utilized to handle varying user loads without compromising performance.
Supporting References from DevOps Institute AIOps Foundation:
The DevOps Institute's AIOps Foundation course emphasizes the importance of meeting user expectations in modern IT operations. It highlights how AIOps enables organizations to manage complex IT infrastructures by leveraging AI and machine learning for better business outcomes. This includesimproving operations performance, providing real-time insights, and enabling proactive monitoring and predictive analytics.
Furthermore, the course discusses how digital transformation and the evolution of machine learning have brought about the rise of AIOps as an indispensable tool in today's IT operational landscape. By understanding and implementing AIOps, IT professionals can effectively address the challenges posed by increasingly demanding user expectations.
In conclusion, while factors like a constantly changing IT landscape, risk of reductions in force, and mergers and acquisitions are significant, the most pressing reason for IT professionals to become effective in operating systems is to meet the increasingly demanding user expectations. Proficiency in operating systems, enhanced by AIOps, equips IT professionals to deliver the reliability, performance, and security that users demand.

NEW QUESTION # 15
The various key areas in a system work together in the following loop:

A. Observe, engage, act
B. Observe, automate, act
C. Automate, iterate and fail fast
D. Audit, document and restore

Answer: A

Explanation:
In the context of AIOps, the system operates through a continuous loop comprising three key stages:
* Observe: This initial phase involves monitoring and collecting data from various IT environments. By gathering metrics, logs, and events, the system gains visibility into its operations, enabling the detection of anomalies or performance issues.
* Engage: Once data is collected, this stage focuses on analyzing and correlating the information to identify patterns or issues. Engagement involves applying machine learning algorithms and analytics to interpret the observed data, facilitating informed decision-making.
* Act: Based on the insights derived from the engagement phase, the system takes appropriate actions to resolve identified issues or optimize performance. This may include automated responses such as scaling resources, restarting services, or alerting IT personnel for further investigation.
This cyclical process ensures that IT operations are continuously monitored, analyzed, and improved, aligning with the principles outlined in the DevOps Institute's AIOps Foundation.

NEW QUESTION # 16
Which definition BEST describes Big Data?

A. Data sets that are "too large" or diverse causing traditional data processing techniques to be ineffective
B. Data sets that are so large they can only be interrogated using Al
C. Data sets of structured data that have grown over time
D. Data sets thatlive in data warehouses or lakes

Answer: A

Explanation:
Big Data refers to data sets that are so large, fast, or complex that traditional data processing methods are inadequate to handle them. This concept is characterized by the Five V's:
* Volume: The sheer amount of data generated.
* Velocity: The speed at which new data is produced and needs to be processed.
* Variety: The different types of data (structured, unstructured, semi-structured).
* Veracity: The quality and accuracy of the data.
* Value: The usefulness of the data for decision-making.
In the context of AIOps, understanding Big Data is crucial as it involves combining big data analytics with machine learning algorithms to enhance IT operations.

NEW QUESTION # 17
......

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2025 Peoplecert AIOps-Foundation: DevOps Institute AIOps Foundation V1.0 Newest New Exam Online

Free AIOps-Foundation Download, Test AIOps-Foundation Passing Score

Peoplecert AIOps-Foundation Exam Syllabus Topics:

Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q12-Q17):

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