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Peoplecert AIOps-Foundation Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

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 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.

Topic 5

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 6

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.

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Peoplecert DevOps Institute AIOps Foundation V1.0 Sample Questions (Q15-Q20):

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

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

Answer: C

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
What is an effective way for an AlOps system to provide visibility?

A. With a pub/sub architecture
B. Via email
C. Through dashboards and metrics
D. Using Slack or Teams

Answer: C

Explanation:
An effective AIOps system provides visibility into IT operations through comprehensive dashboards and metrics. These tools offer real-time insights into system performance, health, and anomalies, enabling IT teams to monitor operations proactively. Dashboards consolidate data from various sources, presenting it in an accessible format, while metrics track key performance indicators essential for informed decision-making.

NEW QUESTION # 17
How did systems architecture transform?

A. From cloud to edge
B. From monoliths to microservices
C. From docker to OCI
D. From object oriented languages to functional languages

Answer: B

Explanation:
System architecture has evolved significantly, transitioning from monolithic structures to microservices.
* Monolithic Architecture: In this traditional model, applications are built as a single, unified unit. While simpler to develop initially, monoliths can become cumbersome to manage, scale, and update as they grow in complexity.
* Microservices Architecture: This modern approach decomposes applications into smaller, independent services that communicate through APIs. Each microservice handles a specific function, allowing for greater flexibility, scalability, and ease of deployment.

NEW QUESTION # 18
What impact on incident related metrics is the desired outcome from AlOps implementation?

A. Decrease in MTTA, Increase in MTTR and Decrease in MTBF
B. Decrease in MTTA. Decrease in MTTR and Increase in MTBF
C. Decrease in MTTA. Decrease in MTTR and Decrease in MTBF
D. Increase in MTTA, Increase in MTTR and Decrease in MTBF

Answer: B

Explanation:
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 # 19
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 # 20
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