Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling 900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection. What actions will meet your company's needs?
Answer(s): B
Here's a detailed justification for why option B is the most appropriate solution, along with links for further research:Option B is the best choice because it addresses the immediate and long-term data transfer needs efficiently. Given the 900 TB of initial data and a 100 MB internet connection, uploading the archived files over the internet would be incredibly slow and impractical. Transfer Appliance is designed for bulk data transfer. It allows you to physically ship a storage device containing your data to Google, providing a fast alternative for large datasets. https://cloud.google.com/transfer-applianceFor the ongoing daily 10 TB data transfer, a dedicated connection like Dedicated Interconnect or Direct Peering is necessary. These options provide higher bandwidth, lower latency, and more reliable connections than a standard internet connection or VPN over the public internet. This is critical for the consistent, high-volume data transfer required daily. https://cloud.google.com/network-connectivity/docs/interconnect/concepts/dedicated-interconnect-overviewOption A is not suitable due to the bottleneck of the 100-MB internet connection, even with compression, for the initial 900 TB upload. The daily transfer would be slow and unreliable.Option C does not provide the high bandwidth and consistent transfer that is needed for a 10TB daily load. A VPN is often over the public internet. While the gsutil "-m" option can speed up transfers, it is not sufficient to overcome the bandwidth constraints of a 100-MB internet connection when coupled with 10TB data transfer requirements.Option D, while leveraging a Transfer Appliance initially, incorrectly suggests that Cloud VPN is sufficient for ongoing 10TB daily transfers. VPNs over the public internet are not suitable for large scale, consistent data transfer.In summary, Option B combines the optimal solution for a bulk transfer (Transfer Appliance) and an adequate solution for ongoing data transfer (Dedicated Interconnect/Direct Peering), addressing both the initial and recurring data needs of the company.
You are developing a globally scaled frontend for a legacy streaming backend data API. This API expects events in strict chronological order with no repeat data for proper processing. Which products should you deploy to ensure guaranteed-once FIFO (first-in, first-out) delivery of data?
The correct answer is B. Cloud Pub/Sub to Cloud Dataflow . Here's why:The core requirement is guaranteed-once, first-in-first-out (FIFO) delivery of events to the legacy API. Cloud Pub/Sub, by itself (option A), offers at-least-once delivery, meaning messages might be delivered more than once. While it offers ordering within a single publish stream, it doesn't guarantee global FIFO delivery across different publishers or when failures occur. Options C (Stackdriver) and D (Cloud SQL) are primarily used for monitoring and data storage respectively, and don't handle event processing or guaranteed delivery.Cloud Dataflow, however, is a fully managed stream processing service that can provide the necessary guarantees when combined with Pub/Sub. Dataflow can subscribe to a Pub/Sub topic and process events while maintaining ordering within a specific key. This ensures that events related to the same entity (identified by a key) are processed in the order they were received. It can also handle retries and deduplication to ensure guaranteed-once semantics for each event. By utilizing a keyed pipeline in Dataflow, you can ensure that events within each stream are processed sequentially and without duplicates, preserving FIFO order.Therefore, Cloud Pub/Sub to Cloud Dataflow (option B) forms a pipeline that can manage guaranteed-once FIFO delivery for the legacy API. Pub/Sub acts as the messaging layer, and Dataflow handles the stream processing, deduplication, ordering and correct sequencing.Relevant links for further reading:Cloud Pub/Sub Ordering: https://cloud.google.com/pubsub/docs/ordering Cloud Dataflow Keyed Processing: https://cloud.google.com/dataflow/docs/concepts/streaming-with-dataflow#keyed-processing Cloud Dataflow Exactly-Once Processing: https://cloud.google.com/dataflow/docs/concepts/streaming-with-dataflow#exactly-once
Your company is planning to perform a lift and shift migration of their Linux RHEL 6.5+ virtual machines. The virtual machines are running in an on-premises VMware environment. You want to migrate them to Compute Engine following Google-recommended practices. What should you do?
Answer(s): C
The correct answer is C because it outlines a systematic and Google-recommended approach to migrating on-premises VMware virtual machines to Compute Engine, specifically leveraging Migrate for Compute Engine. Option A is less ideal as it skips assessment and planning, which are crucial for a successful migration. Option B involves manual disk image import, a less efficient method than using a dedicated migration tool. Option D suggests using a third-party agent, which is unnecessary when Google provides Migrate for Compute Engine.Here's a breakdown of why option C is the best approach:Assessment: Performing a thorough assessment of the existing VMware environment is paramount. This step identifies VM characteristics, dependencies, and potential migration challenges. Migration Plan: A well-defined migration plan clarifies the order, scope, and strategy of the migration, ensuring minimal disruptions. Migrate for Compute Engine: Google's Migrate for Compute Engine is designed for large-scale migrations. It streamlines the process by allowing live migrations (meaning no downtime), automated conversion of VMs, and efficient replication. Runbook: Creating a Runbook documents the steps involved in migration using Migrate for Compute Engine, ensuring repeatability and minimizing human error.Using Migrate for Compute Engine offers numerous advantages, including reduced downtime, minimized risk, and simplified migration management. It aligns with Google's best practices, making option C the most appropriate.Authoritative links for further research:Migrate for Compute Engine Documentation: https://cloud.google.com/migrate/compute-engine/docs Google Cloud Migration Overview: https://cloud.google.com/migrate Best Practices for Migrating to Google Cloud: https://cloud.google.com/architecture/migration
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud. What should you do?
Answer(s): D
Here's a breakdown of why option D is the correct solution and why other options are unsuitable:Justification for Option D:Option D, using an unmanaged instance group with an active/standby setup, a regional persistent disk, and a network load balancer, aligns with the application's unique constraints. The application cannot scale horizontally, necessitating a failover strategy rather than load balancing across multiple instances. An unmanaged instance group allows for the manual configuration needed for this specific active/standby setup. A regional persistent disk is crucial since data needs to be preserved upon failover. The network load balancer (TCP traffic) is ideal because the application uses TCP and doesn't require HTTP specific features.Unmanaged Instance Group: The application's lack of horizontal scaling requires explicit control over instances. Unmanaged groups provide this control, allowing for manual failover implementation between active and standby instances. This directly addresses the non-scaling requirement. Active/Standby Setup: This design ensures that only one instance is active at any given time, preventing the concurrency issues leading to data corruption on the filesystem as stated in the question. The standby instance is ready for a failover in case of the active instance failing. This aligns with the requirement that the application must be available 24/7. Regional Persistent Disk: This storage option ensures data persistence across zones. In the event of the primary instance failing, the standby instance in a different zone can mount the regional persistent disk and take over. This addresses the need for data consistency and availability during failover. Network Load Balancer: The requirement specifies that the application uses TCP. A network load balancer is designed for TCP traffic and routes connections to a single instance, which perfectly matches the design of active/standby. It doesn't perform any HTTP-specific functions, aligning with the application's needs.Why other options are incorrect:Option A and B (Managed Instance Group with Filestore): Managed instance groups are designed for autoscaling, which isn't required here. They are not suitable for active/standby configurations. Cloud Filestore is a network file system, which introduces the same issue of concurrent access that the question specifies as the reason to not be able to scale horizontally, and is not necessary when you have an active/standby instance. Option A (HTTP Load Balancer): This load balancer is designed for HTTP traffic, not the required TCP.Authoritative Links:Instance Groups: https://cloud.google.com/compute/docs/instance-groups Unmanaged Instance Groups: https://cloud.google.com/compute/docs/instance-groups/unmanaged Regional Persistent Disks: https://cloud.google.com/compute/docs/disks#regional-pd Network Load Balancer: https://cloud.google.com/load-balancing/docs/network/In summary, Option D provides the necessary architecture using an unmanaged instance group, regional persistent disk, and network load balancer to support an application with the stated constraints, while other options deviate from the established requirements or use incompatible features.
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?
The correct answer is D. Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.Here's why:The scenario demands high-throughput, low-latency communication between Google Cloud Compute Engine instances and an on-premises service using internal IPs. Cloud Dedicated Interconnect provides a direct physical connection between your on-premises network and Google's network, offering the highest bandwidth and lowest latency compared to other connection options. This is crucial when dealing with applications requiring high-performance communication between the two environments. Internal IPs are supported over Dedicated Interconnect, ensuring that communication remains within private networks, avoiding the public internet.OpenVPN (A) and Cloud VPN (C) both utilize VPN tunnels, which introduce encryption overhead and potentially higher latency compared to a dedicated connection. Although they offer security, VPNs do not provide the high-throughput and low-latency requirements of the use case, which is critical for the application described.Direct peering (B) establishes a business-level relationship and facilitates the exchange of internet traffic. It does not provide private network connectivity over internal IP addresses and might not offer a solution for the high bandwidth and low latency requirements demanded here.Therefore, a Cloud Dedicated Interconnect provides the most suitable infrastructure with guaranteed bandwidth and minimal latency, which aligns with the stated needs for the application.Authoritative Links:Google Cloud Dedicated Interconnect: https://cloud.google.com/network-connectivity/docs/interconnect/concepts/dedicated-interconnect Google Cloud VPN: https://cloud.google.com/network-connectivity/docs/vpn/concepts/overview Google Cloud Peering: https://cloud.google.com/peering/docs/overview
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