Monitoring and Optimization of Resources Flashcards
Microsoft Fabric Data Engineer Associate DP-700 Flashcards
| Front | Back |
| Best practice for monitoring data pipelines | Regularly check data pathway performance and identify bottlenecks |
| Best way to identify resource hotspots | Use monitoring tools to analyze patterns and pinpoint overused resources |
| How can automation aid in optimization efforts | Automating routine tasks reduces manual workload and ensures consistent results |
| How do caching strategies improve performance | By reducing the need to retrieve data repeatedly from slow storage |
| How does performance monitoring work in Microsoft Fabric | It tracks system metrics like memory usage, CPU load, and query performance |
| How does proper indexing improve performance | Speeds up data retrieval and reduces processing time in databases |
| Key benefit of optimizing resources | Improved efficiency and reduced operational costs |
| Key metric to track for query optimization | Query duration and resource utilization |
| Purpose of resource tagging | Categorize and track resources for better management and monitoring |
| Role of predictive analytics in optimization | Anticipating future usage trends to allocate resources accordingly |
| What is a resource pool in Microsoft Fabric | A shared pool of CPU and memory resources for tasks across a workload |
| What is capacity planning | Estimating resources required to meet future demand |
| What is governance in resource monitoring | Policies and controls to ensure efficient, secure, and compliant resource use |
| What is load balancing | Distributing workloads across multiple resources to improve performance and fault tolerance |
| What is monitoring in resource optimization | Tracking system performance to identify issues and areas for improvement |
| What is the difference between vertical and horizontal scaling | Vertical scaling adds resources to a single system, while horizontal scaling adds systems to the pool |
| What is throttling in resource management | Reducing resource usage when system limits are reached to maintain stability |
| What to do when a system experiences high latency | Analyze resource usage and optimize queries or increase allocated resources |
| What tools are used for monitoring in Microsoft Fabric | Power BI, Fabric Monitoring Dashboard, and built-in analytics features |
| Why is scaling important in resource optimization | It ensures systems can handle increased workloads without performance degradation |
About the Flashcards
Flashcards for the Microsoft Fabric Data Engineer Associate exam provide a concise review of resource optimization and monitoring concepts used in Microsoft Fabric. The deck covers monitoring fundamentals, common metrics (CPU, memory, query duration), tools such as Power BI and the Fabric Monitoring Dashboard, and practices like throttling, caching, and load balancing to maintain performance.
Students can use these cards to reinforce terminology and key ideas-scaling strategies (vertical vs horizontal), capacity planning, resource pools and tagging, governance controls, automation, predictive analytics, and query/index optimization. The set focuses on practical troubleshooting steps, identifying hotspots, and metrics-driven decisions you are likely to encounter on the exam.
Topics covered in this flashcard deck:
- Monitoring tools and metrics
- Scaling and capacity planning
- Query optimization and indexing
- Caching and load balancing
- Governance and resource tagging