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Which two options describe the capabilities of IBM Cloud Block Storage for VPC?
The capabilities of IBM Cloud Block Storage for VPC are:
Stores Volume Data Redundantly Across Multiple Physical Disks in an Availability Zone: IBM Cloud Block Storage is designed to provide redundancy and durability by storing data across multiple physical disks within the same availability zone. This ensures data availability and protection against disk failures.
Provides Primary Boot Volumes and Secondary Data Volumes: Block Storage in IBM Cloud VPC can be used as both primary boot volumes for the operating system and secondary data volumes for storing additional data.
Reference from IBM Cloud Professional Architect Materials:
IBM documentation on IBM Cloud Block Storage for VPC outlines these capabilities, including redundant data storage and support for both boot and data volumes.
Other options are incorrect:
A . Provides a highly available, durable, and secure platform for storing unstructured data describes object storage, not block storage.
C . Provides storage in a separate zone is incorrect; storage is typically within the same zone as compute resources.
E . Provides fast, flexible network-attached, NFS-based storage describes a different type of storage.
Therefore, the correct answers are B. Stores volume data redundantly across multiple physical disks in an availability zone and D. Provides primary boot volumes and secondary data volumes.
Why does IBM Cloud Analytics Engine decouple compute and storage?
IBM Cloud Analytics Engine decouples compute and storage to provide independent scaling and cost management capabilities. This approach allows organizations to scale compute resources (such as CPU and memory) separately from storage resources, optimizing both performance and cost.
Independent Scaling: Decoupling compute and storage means that users can scale the computational power (e.g., number of nodes, processing capabilities) independently of the storage capacity (e.g., data stored in IBM Cloud Object Storage). This is particularly useful in data analytics workloads where the compute requirements may vary significantly over time, but the storage requirements remain relatively constant.
Cost Control: By allowing compute and storage to be managed separately, users have greater flexibility to control costs. For example, users can increase compute power temporarily to handle a peak workload without the need to increase storage costs. Conversely, they can store large datasets without paying for unused compute capacity. This decoupling leads to a more cost-effective and efficient use of cloud resources.
Advantages in Cloud Environments: Decoupling compute and storage aligns with the best practices in modern cloud environments, where elasticity, scalability, and cost efficiency are paramount. It allows organizations to adapt quickly to changing business needs and workload demands, reducing overhead and improving resource utilization.
IBM Cloud Analytics Engine Documentation
IBM Cloud Architect Exam Study Guide
IBM Cloud Object Storage
An architect is tasked with determining the resiliency option for an application where the data must remain in-country and locally restricted.
Which IBM Cloud Object Storage resiliency option is best for this use case?
The best IBM Cloud Object Storage resiliency option for a use case where data must remain in-country and locally restricted is Single Data Center.
Single Data Center: This option ensures that all data is stored within a single geographic location, which complies with regulations or requirements that mandate data residency within a specific country. By using a single data center, the data remains locally restricted.
Data Residency Requirements: When an application has strict regulatory or compliance requirements that specify data must not leave the country, the Single Data Center option ensures that data does not cross geographic boundaries.
Reference from IBM Cloud Professional Architect Materials:
IBM documentation on IBM Cloud Object Storage Resiliency Options states that the Single Data Center option is best suited for scenarios where data residency is a concern.
Other options are incorrect:
A . Cross Zone, C. Cross Region, and D. Multizone involve data being stored across multiple locations or regions, which would not meet the requirement of keeping the data locally restricted.
An organization has recently deployed Red Hat OpenShift on an IBM Cloud cluster on a VPC infrastructure. Several of the internal applications running in the cluster require access to resources hosted on an IBM Cloud Classic infrastructure. Which two connectivity options would enable this?
When an organization has deployed Red Hat OpenShift on an IBM Cloud cluster on a Virtual Private Cloud (VPC) infrastructure and needs to connect to resources hosted on the IBM Cloud Classic infrastructure, IBM Cloud Direct Link and Transit Gateway are the two most suitable connectivity options.
IBM Cloud Direct Link:
IBM Cloud Direct Link provides dedicated, high-speed, and secure connectivity between IBM Cloud infrastructure components, including between VPCs and IBM Cloud Classic infrastructure. By establishing a Direct Link connection, traffic can securely flow between the Red Hat OpenShift workloads in the VPC and the applications or services running on the Classic infrastructure without traversing the public internet.
Transit Gateway:
IBM Cloud Transit Gateway allows organizations to establish a hub-and-spoke model of connectivity, facilitating communication between different networks, such as VPCs and Classic infrastructure, across IBM Cloud. With Transit Gateway, you can interconnect multiple VPCs and Classic networks, allowing seamless communication across the cloud environments. This option is ideal for managing traffic between isolated network segments while maintaining control over traffic routing and security policies.
These two options are typically used in multi-cloud or hybrid cloud architectures to ensure smooth, secure, and scalable communication between cloud environments (VPC and Classic infrastructure) in IBM Cloud.
IBM Cloud Documentation Reference:
IBM Cloud Direct Link
IBM Cloud Transit Gateway
Which IBM Cloud service can be used to store and analyze data collected to identify the root causes of slowness?
Elasticsearch is a powerful search and analytics engine commonly used to store, search, and analyze large volumes of data in real time. IBM Cloud's 'Databases for Elasticsearch' service is specifically designed for this purpose, allowing users to ingest, search, and analyze log data or other large datasets to identify root causes of slowness or performance issues.
Why Databases for Elasticsearch? Elasticsearch is ideal for storing and analyzing logs due to its ability to quickly index and query large amounts of data. It provides powerful search capabilities, aggregations, and visualization tools that are well-suited for identifying performance bottlenecks and troubleshooting.
Comparison with Other Options:
A (Databases for etcd): Not used for analytics or identifying performance issues.
B (Databases for Redis): Primarily an in-memory data store, not suitable for complex data analysis.
D (Cloudant): A NoSQL database service optimized for web and mobile applications, but not primarily for analyzing log data.
IBM Cloud Databases for Elasticsearch
IBM Cloud Architect Exam Study Guide
