Scenario: A large organization requires secure DNS resolution and protection against DDoS attacks. Which feature of Cloud DNS should they leverage?
- Cloud DNS Security
- Global Anycast Network
- DNS Caching
- Traffic Management Policies
Security is a critical consideration for organizations managing DNS infrastructure, especially for large enterprises facing potential DDoS attacks. Leveraging features like DNSSEC and DDoS protection in Cloud DNS can help ensure secure and reliable DNS resolution.
Cloud Billing APIs enable users to retrieve detailed _______ information.
- cost
- usage
- security
- latency
Cloud Billing APIs are designed to provide detailed cost information, helping users understand their cloud expenses.
What does VM stand for in the context of cloud computing?
- Virtual Machine
- Variable Module
- Virtual Module
- Virtual Management
In cloud computing, VM stands for Virtual Machine, which allows for running multiple operating systems on a single physical machine.
What are the considerations for setting up custom autoscaling policies in Google Compute Engine?
- Considerations include defining appropriate scaling metrics, setting threshold values, configuring cooldown periods, and testing the effectiveness of the autoscaling policies under different workload scenarios.
- Considerations for setting up custom autoscaling policies in Google Compute Engine include relying solely on default scaling metrics provided by the platform, avoiding cooldown periods to minimize scaling delays, and deploying policies without testing them in production environments.
- Considerations for custom autoscaling policies involve setting up complex rules and conditions based on external factors such as weather forecasts or stock market trends to dynamically adjust resource allocation.
- Considerations for custom autoscaling policies revolve around manual intervention and human judgment to override automated scaling decisions based on subjective assessments of workload conditions and business priorities.
Designing effective custom autoscaling policies requires a thorough understanding of the underlying infrastructure and application requirements, as well as careful consideration of various factors such as scaling metrics, threshold values, cooldown periods, and testing procedures. By following best practices and iterative refinement, organizations can optimize their autoscaling strategies to meet performance objectives and cost targets.
Cloud Bigtable supports a wide range of client libraries, including _______ for seamless application development.
- Apache Hadoop
- Apache Spark
- Apache Cassandra
- Apache HBase
Knowing the supported client libraries for Cloud Bigtable is essential for developers to choose the appropriate tools and frameworks for building applications that interact with Cloud Bigtable. Understanding that Cloud Bigtable supports Apache HBase client libraries provides compatibility and flexibility for application development.
How does Stackdriver Trace handle tracing requests across distributed systems?
- Utilizes distributed tracing
- Aggregates log data
- Monitors network bandwidth
- Analyzes CPU utilization
Stackdriver Trace's distributed tracing capabilities enable developers to track requests as they traverse across distributed systems, facilitating performance analysis and debugging.
_______ is a feature of Google App Engine that allows developers to create flexible and scalable applications.
- Managed Infrastructure
- Serverless Computing
- Autoscaling
- Container Orchestration
Understanding the features of Google App Engine, such as its ability to provide managed infrastructure for building flexible and scalable applications, is crucial for developers working with the platform.
What role does sampling play in Stackdriver Trace?
- Reducing overhead
- Increasing latency
- Capturing all requests
- Enabling real-time tracing
Sampling in Stackdriver Trace is crucial for managing the volume of tracing data generated by applications, reducing overhead while still providing valuable insights into application performance.
What are the potential cost-saving benefits of utilizing Nearline or Coldline storage for long-term data retention?
- Lower storage costs compared to standard storage classes.
- Faster access times for data retrieval.
- Higher durability and reliability for stored data.
- Increased scalability for storage capacity.
Understanding the cost-saving benefits of Nearline and Coldline storage helps organizations make informed decisions about data storage strategies, particularly for long-term retention needs where access frequency may be low.
Which of the following data models does Cloud Datastore support?
- Document-oriented and Entity-relationship
- Relational Only
- Key-value Only
- Graph Only
Understanding the supported data models of Cloud Datastore helps beginners design their data schemas effectively and choose appropriate data modeling techniques for their applications. Recognizing the flexibility of data models offered by Cloud Datastore is crucial for building scalable and adaptable systems.