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Question 61Question →

Match each workload requirement and data access pattern on the left with the most appropriate managed Google Cloud storage or database service on the right.

Click a left item, then click its matching right item

Items

A global transactional order management system requiring multi-region, strongly consistent ACID relational operations with ANSI SQL support and a 99.999% availability SLA.
A high-velocity IoT fleet monitoring system requiring single-digit millisecond write latency for time-series key-value telemetry data and seamless analytical integration with BigQuery.
A cross-platform mobile application requiring serverless hierarchical JSON document storage, real-time client data synchronization, and offline data persistence.
An enterprise media and audit repository storing unstructured video assets and compliance logs with automated cost optimization via object lifecycle management rules.

Matches

Show answer & explanation

Answer

1. Global multi-region relational ACID with 99.999% SLA maps to Cloud Spanner.
2. Low-latency time-series key-value IoT telemetry maps to Cloud Bigtable.
3. Mobile app real-time JSON document sync maps to Firestore.
4. Unstructured media and audit log lifecycle management maps to Cloud Storage.
Each GCP database and storage service addresses specific architectural trade-offs: Cloud Spanner for globally distributed relational ACID workloads; Cloud Bigtable for high-throughput, low-latency key-value/time-series data; Firestore for real-time mobile serverless document synchronization; and Cloud Storage for unstructured object data with lifecycle management.

Step-by-Step Solution

1
Analyze global multi-region relational ACID requirements.
Cloud Spanner is the only relational GCP database service providing multi-region external consistency, ANSI SQL compatibility, and five-nines (99.999%) availability.
Traditional relational databases like Cloud SQL do not provide global multi-region horizontal scaling or 99.999% SLAs.
2
Analyze high-throughput IoT time-series telemetry data requirements.
Cloud Bigtable provides low-latency key-value write throughput suitable for massive IoT streaming datasets and integrates directly with BigQuery.
Relational databases cannot handle massive, continuous single-digit millisecond write loads efficiently without complex sharding.
3
Analyze mobile JSON document synchronization requirements.
Firestore provides serverless document storage with native client SDKs supporting offline persistence and automatic real-time listener updates.
Relational and object storage engines lack native client state synchronization and offline caching primitives.
4
Analyze unstructured object storage and tiering requirements.
Cloud Storage is designed for blob objects like media files and logs, supporting automated transition rules between Nearline, Coldline, and Archive classes.
Database services are inefficient and cost-prohibitive for storing raw binary media files.

Key Concept

Matching workload access patterns, consistency requirements, latency expectations, and data structure types to optimal GCP database and storage services.
Estimated Time:2m 0s
Question 62Question →

A telecommunications enterprise is designing a hybrid network topology to connect its on-premises data centers and remote operational facilities to Google Cloud. Match each GCP hybrid connectivity technology on the left to its corresponding architectural scenario requirement on the right.

Click a left item, then click its matching right item

Items

Dedicated Interconnect
Partner Interconnect
HA VPN
Cloud Router

Matches

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Answer

Dedicated Interconnect matches direct physical circuits (10/100 Gbps). Partner Interconnect matches service-provider backed connectivity under 10 Gbps. HA VPN matches encrypted IPsec tunnels over the public internet with 99.99% availability. Cloud Router matches dynamic BGP route exchange.
Each technology is paired correctly based on key Google Cloud network architecture specifications: Dedicated Interconnect provides 10/100 Gbps direct connections; Partner Interconnect offers provider-assisted sub-10 Gbps links; HA VPN provides encrypted 99.99% SLA IPsec tunnels over the public internet; and Cloud Router handles dynamic BGP route exchanges.

Step-by-Step Solution

1
Analyze high-bandwidth direct physical requirements
Dedicated Interconnect is required for direct 10 Gbps or 100 Gbps physical circuits without third-party service provider mediation.
Dedicated Interconnect directly links your enterprise network to a Google Colocation facility.
2
Analyze service provider hybrid connectivity needs below 10 Gbps
Partner Interconnect maps to sub-10 Gbps connectivity provided via supported service providers.
Partner Interconnect extends connectivity to locations where dedicated Google points of presence are unavailable or bandwidth needs are smaller.
3
Identify secure encrypted transport options over public internet
HA VPN matches IPsec encrypted transport delivering up to 3 Gbps per gateway with 99.99% SLA.
HA VPN provides high-availability IPsec tunnels using BGP dynamic routing without requiring private circuit installation.
4
Determine dynamic routing component
Cloud Router provides dynamic routing using Border Gateway Protocol (BGP).
Cloud Router manages dynamic route exchange between GCP VPCs and on-premises networks across Interconnects or VPNs.

Key Concept

Selecting and combining Google Cloud hybrid connectivity options (Dedicated Interconnect, Partner Interconnect, HA VPN, and Cloud Router) based on enterprise bandwidth, encryption, SLA, and routing requirements.
Question 63Question →

Match each enterprise application storage requirement to the most appropriate Google Cloud database or storage service based on data access patterns, scalability, and structural requirements.

Click a left item, then click its matching right item

Items

Low-latency, high-throughput NoSQL key-value storage for real-time application session data and user profile caching.
Globally distributed relational database requiring horizontal scaling and multi-region ACID transactional consistency.
Fully managed serverless enterprise data warehouse optimized for running ad-hoc analytical SQL queries on petabyte-scale data.
Unstructured object storage service for storing compliance archives requiring write-once-read-many (WORM) retention policies.

Matches

Show answer & explanation

Answer

The requirement for real-time NoSQL key-value caching matches Cloud Bigtable; global ACID relational transactions match Cloud Spanner; petabyte-scale serverless SQL analytics matches BigQuery; and regulatory object archival matches Cloud Storage.
Each Google Cloud database and storage offering aligns with specific access patterns and architectural demands: Cloud Bigtable serves high-speed NoSQL key-value patterns; Cloud Spanner handles global ACID relational workloads; BigQuery executes serverless analytical OLAP queries; Cloud Storage manages unstructured object files with WORM regulatory capabilities.

Step-by-Step Solution

1
Analyze high-throughput NoSQL key-value caching access patterns.
Identify Cloud Bigtable as the optimal service for ultra-low latency NoSQL key-value workloads.
Cloud Bigtable scales seamlessly to handle massive write/read throughput with single-digit millisecond latencies.
2
Evaluate global transactional relational consistency requirements.
Identify Cloud Spanner as the correct choice for multi-region relational ACID transactions.
Cloud Spanner combines traditional relational schema support and ACID guarantees with global horizontal scalability.
3
Examine large-scale analytical query requirements.
Identify BigQuery as the appropriate serverless data warehouse.
BigQuery is designed to execute fast SQL queries over petabytes of structured or semi-structured analytical data.
4
Determine compliance object storage requirements.
Identify Cloud Storage with Bucket Lock features.
Cloud Storage provides durable unstructured object store functionality and legal hold/retention policy compliance.

Key Concept

Selecting and Designing Storage and Database Resources in Google Cloud
Question 64Question →

Match each application data access pattern on the left with the most appropriate Google Cloud database or storage service on the right based on GCP architectural best practices.

Click a left item, then click its matching right item

Items

Storing large binary media files with configurable lifecycle rules for automatic archival to cost-effective storage tiers.
Ingesting high-throughput time-series IoT metrics requiring consistent single-digit millisecond latency at scale.
Managing financial ledger transactions requiring multi-region, strong ACID consistency with relational SQL querying.
Serving hierarchical mobile app user preferences requiring live client synchronization and offline database support.

Matches

Show answer & explanation

Answer

Large binary media files with lifecycle rules match Cloud Storage. High-throughput time-series IoT metrics match Cloud Bigtable. Financial ledger transactions needing multi-region ACID consistency match Cloud Spanner. Mobile app user preferences with offline sync match Firestore.
Each requirement directly aligns with key capabilities of GCP database offerings: Cloud Storage for object lifecycle management; Cloud Bigtable for high-scale time-series ingestion; Cloud Spanner for global ACID relational workloads; and Firestore for mobile document syncing with offline support.

Step-by-Step Solution

1
Analyze storage object structure and access lifecycle for un-structured data requirement.
Unstructured binary objects with lifecycle management requirements uniquely fit Cloud Storage.
Cloud Storage handles unstructured file objects and lifecycle transitions across storage tiers.
2
Evaluate throughput and latency metrics for time-series IoT workload.
High-velocity streaming data requiring single-digit millisecond latency matches wide-column NoSQL.
Cloud Bigtable provides sub-10ms performance specifically designed for high-throughput time-series analytics.
3
Assess consistency and scale demands for relational financial transactions.
Multi-region horizontal scalability with ACID compliance requires Cloud Spanner.
Cloud Spanner is the only GCP service offering globally synchronous transactions with SQL capabilities.
4
Determine mobile app offline synchronization and document storage needs.
Real-time client updates and offline local caching match Firestore.
Firestore client libraries natively handle offline state persistence and dynamic real-time data sync.

Key Concept

GCP Storage and Database Resource Selection Criteria
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