75 of 162 questions · Page 1/3 · Cdl Google Cloud Products topic · Answers revealed
Which Google Cloud service is used for monitoring and alerting on the performance and health of cloud resources?
Cloud Monitoring collects metrics, sets up dashboards, and sends alerts based on conditions.
Why this answer
Cloud Monitoring (formerly Stackdriver Monitoring) provides visibility into the performance, uptime, and health of cloud applications.
A financial services company needs a relational database with global strong consistency, horizontal scaling, and 99.999% availability SLA. Which database should they choose?
Cloud Spanner meets all requirements: global, strongly consistent, scalable, 99.999% SLA.
Why this answer
Cloud Spanner offers global distribution, strong consistency, automatic horizontal scaling, and a 99.999% SLA. Cloud SQL does not scale globally, Firestore is NoSQL, and Bigtable lacks strong consistency.
A company is using Cloud SQL for MySQL and wants to minimise downtime during a schema migration that may take up to 30 minutes. Which THREE steps should they take to achieve near-zero downtime? (Choose 3)
After migration, promote the replica to become the new primary, then update applications to point to it. This minimises downtime.
Why this answer
To minimise downtime, use Database Migration Service (DMS) for continuous replication to a new instance, promote the new instance, and then redirect traffic. Alternatively, you can use Cloud SQL's clone feature (point-in-time recovery) to create a replica, perform migration on the replica, and then promote. The steps: create a read replica, perform migration on the replica (it stays in sync), then promote the replica to primary.
Also, use a maintenance window to control timing. The correct combination: create a read replica, perform the migration on the replica, then promote the replica. Using a maintenance window is also good practice but not specific to schema migration.
The question asks 'which THREE steps'; options might include: create read replica, perform migration on replica, promote replica, use DMS, schedule maintenance window. I'll choose the three that are most directly involved in achieving near-zero downtime.
A company is migrating a PostgreSQL database to Google Cloud. They want high performance, AI-optimized capabilities, and compatibility with existing PostgreSQL tools. Which service should they choose?
AlloyDB is PostgreSQL-compatible with 4x faster transactions and built-in AI capabilities.
Why this answer
AlloyDB is a PostgreSQL-compatible database optimized for high performance and AI workloads, with built-in ML integration. Cloud SQL for PostgreSQL provides compatibility but lacks AI optimization. Spanner is a different architecture.
Bigtable is NoSQL.
A data scientist wants to train a custom machine learning model using their own data and deploy it for online predictions. They want a unified platform that manages the entire ML lifecycle from data preparation to model serving. Which service should they use?
Vertex AI provides a unified platform for the entire ML workflow, including custom training and online prediction.
Why this answer
Vertex AI is Google Cloud's unified ML platform that covers data labeling, training, tuning, evaluation, and deployment (online prediction endpoints). AutoML is part of Vertex AI but focuses on automated model building. Cloud Functions is for serverless code, not ML.
AI Platform (unified) is the old name for Vertex AI.
A DevOps team wants to implement infrastructure as code for deploying a multi-service application on GKE. They need to store container images, automate builds on code commits, and manage Kubernetes YAML configurations. Which THREE services should they use? (Choose 3)
Can manage Kubernetes configs (although Config Sync is more common, but DM is valid).
Why this answer
Artifact Registry stores container images, Cloud Build automates builds on commits, and Deployment Manager (or Config Sync) can manage Kubernetes configs. Cloud Source Repositories is for source code, not containers; Cloud Run is serverless, not GKE.
A company runs a global web application hosted on Compute Engine behind a Cloud Load Balancer. They want to protect against DDoS attacks and filter incoming traffic based on IP reputation and geolocation. Which Google Cloud service should they use?
Cloud Armor provides DDoS protection, WAF, IP allow/deny lists, and geo-based access control.
Why this answer
Cloud Armor is a web application firewall (WAF) and DDoS protection service that integrates with Cloud Load Balancing. It allows IP allow/deny lists, rate limiting, and predefined rules to block traffic based on geo-location and threat intelligence. VPC firewall rules operate at the network level but cannot inspect application-layer traffic or use IP reputation.
Cloud CDN caches content but does not filter traffic. Cloud NAT provides outbound connectivity only.
An organization needs to run a batch process every night that analyzes terabytes of data from Cloud Storage and writes results back to BigQuery. The job is not time-sensitive and can be preempted. Which compute approach is most cost-effective?
Preemptible VMs are ideal for fault-tolerant, interruptible batch workloads because they provide significant cost savings (up to 80% discount) and can be restarted if preempted.
Why this answer
Preemptible VMs on Compute Engine offer the lowest cost for fault-tolerant batch workloads because they are up to 80% cheaper than regular VMs but can be terminated at any time. Cloud Run has a request timeout limit and is not ideal for long-running batch jobs. GKE with preemptible nodes is also cost-effective but requires Kubernetes expertise and is more complex than simply using preemptible VMs.
Cloud Functions has a timeout limit.
A company wants to deploy a web application that automatically scales based on traffic, and they do not want to manage infrastructure. The application is written in Python and uses a Flask framework. Which TWO Google Cloud services could they use?
Cloud Run can deploy containerized Flask apps with automatic scaling.
Why this answer
App Engine Standard supports Python and Flask, automatically scaling to zero. Cloud Run can run containerized Flask applications, scaling to zero based on requests. Compute Engine requires VM management.
Cloud Functions is for small snippets, not full web apps. GKE requires cluster management.
A data scientist wants to train a custom machine learning model using a large dataset stored in BigQuery. They need a managed service that supports distributed training with GPU accelerators. Which service should they use?
Vertex AI Training allows custom code, distributed training, and GPU/TPU support.
Why this answer
Vertex AI provides a unified ML platform with managed training jobs that support distributed training and GPU accelerators.
An engineer needs to deploy a containerized application on Google Kubernetes Engine (GKE) and ensure that each pod gets a static IP address that persists across rescheduling. Which networking approach should they use?
This annotation allows reserving a static internal IP for a pod within a VPC-native cluster.
Why this answer
GKE supports static IP addresses for pods using VPC-native clusters and alias IP ranges. By reserving a static internal IP address and assigning it to the pod via a Kubernetes annotation, the IP persists even if the pod is rescheduled.
A company is running a stateful workload on Compute Engine and needs persistent block storage that can be attached to multiple VMs in read-only mode. Which two Google Cloud storage solutions meet this requirement?
Persistent Disk can be attached in read-only mode to multiple VMs.
Why this answer
Persistent Disk (PD) supports read-only mounting to multiple VMs in the same zone. Filestore is a file-based NFS storage that can be mounted to multiple VMs with read-write access, but not specifically block storage. Cloud Storage is object storage, not block storage.
Local SSD is ephemeral and cannot be shared. Persistent Disk is the correct block storage option.
A company wants to store archived data that must be retained for 10 years. They expect to access it less than once a year. Which Cloud Storage class is the MOST cost-effective?
Archive is the lowest cost for data accessed less than once a year, with 365-day minimum.
Why this answer
Archive storage is designed for data accessed less than once a year, with the lowest storage cost but higher retrieval fees and a 365-day minimum storage duration. Coldline has a 90-day minimum and higher cost. Nearline and Standard are more expensive and have shorter minimums.
A data engineer needs to process a continuous stream of clickstream events from a website, perform real-time aggregations (e.g., counts per page per minute), and write the results to BigQuery for dashboarding. Which combination of services should they use?
Pub/Sub ingests the stream, Dataflow performs real-time transformations and aggregations, and BigQuery stores results for dashboarding.
Why this answer
Pub/Sub ingests the stream, Dataflow processes real-time aggregations using Apache Beam, and BigQuery stores results. Cloud Functions is not suitable for streaming aggregations. Cloud Storage is for batch, not real-time.
Cloud SQL is not for streaming analytics.
A developer wants to build a mobile app backend that uses a real-time database for chat messages, user profiles, and file storage for images. They want a fully managed, serverless solution. Which THREE Google Cloud services should they use? (Choose three.)
Cloud Functions can run serverless backend logic in response to Firestore or Storage events.
Why this answer
Firestore provides real-time document database for chat and profiles; Cloud Storage for images; Cloud Functions for backend logic triggered by database or storage events. App Engine is not required for serverless backend if using Cloud Functions.
A data engineering team needs to process streaming data from IoT devices, perform real-time transformations, and load the results into BigQuery for analysis. Which TWO Google Cloud services should they use?
Pub/Sub ingests streaming data from IoT devices reliably.
Why this answer
Pub/Sub is the messaging service for ingesting streaming data. Dataflow can read from Pub/Sub, perform transformations, and write to BigQuery. Cloud Functions is for small event-driven functions, not streaming pipelines.
Dataproc is for batch Hadoop/Spark jobs. Cloud Scheduler is for cron jobs.
A company is deploying a global web application and needs to serve users with low latency, protect against DDoS attacks, and scale automatically. Which two Google Cloud services should they combine? (Choose exactly 2.)
Cloud Armor provides DDoS protection and WAF rules.
Why this answer
Cloud Load Balancing distributes traffic globally and scales automatically. Cloud Armor provides DDoS protection and WAF. Cloud CDN caches content but does not provide DDoS protection.
Cloud DNS resolves domain names. Cloud NAT is for outbound connectivity.
A developer wants to trigger a serverless function in response to a file being uploaded to a Cloud Storage bucket. Which Google Cloud service should they use?
Cloud Functions is designed for event-driven, single-purpose functions that respond to Cloud Storage events.
Why this answer
Cloud Functions is an event-driven serverless compute service that can be triggered by Cloud Storage events (e.g., object finalize).
A data engineering team wants to process continuous streams of real-time events from millions of devices, perform transformations, and load the results into BigQuery for analysis. They need a fully managed, serverless solution. Which service should they use?
Dataflow is a serverless stream and batch processing service with native BigQuery integration.
Why this answer
Dataflow is a fully managed, serverless service for stream and batch data processing, with built-in connectors to Pub/Sub and BigQuery. Pub/Sub is for ingestion only, not processing. Cloud Functions is not designed for high-throughput streaming.
Dataproc is a managed Hadoop/Spark service, not serverless.
A company wants to migrate its on-premises PostgreSQL database to Google Cloud with minimal downtime. They also need the ability to perform point-in-time recovery. Which TWO services or features should they use? (Choose two.)
Cloud SQL is the target managed PostgreSQL service.
Why this answer
Cloud SQL for PostgreSQL supports database migration and point-in-time recovery. Database Migration Service provides for minimal-downtime migrations.
A company runs a critical application on Compute Engine. They need a backup and disaster recovery strategy that includes automated backups and the ability to restore in a different region. Which TWO services should they use together? (Select 2)
Snapshots provide point-in-time backups of persistent disks and can be automated.
Why this answer
Persistent Disk snapshots can be used for automated backups. Cloud Storage can store these snapshots in a different region for DR. Cloud SQL is not relevant if the application runs on Compute Engine.
Cloud Run is a compute service, not backup. Dataflow is processing.
A team wants to use a managed MySQL database that offers automatic failover, backups, and read replicas. They also need to connect from Compute Engine instances in the same region. Which service should they use?
Cloud SQL for MySQL offers all requested features as a managed service.
Why this answer
Cloud SQL provides managed MySQL with high availability, automated backups, and read replicas, and can be accessed from Compute Engine via internal IP.
A company has a critical application running on Compute Engine instances in a managed instance group (MIG) that must remain highly available across three zones in a region. The application stores state on Persistent Disk. What is the correct approach to achieve high availability?
Regional PD replicates synchronously across zones, enabling fast failover for stateful apps.
Why this answer
For stateful workloads, regional Persistent Disk replicates data synchronously across zones, enabling rapid failover. Zonal PD is single-zone only. Regional managed instance groups distribute instances across zones but do not replicate disks.
A load balancer distributes traffic but does not handle disk replication.
A security team wants to restrict access to a Cloud Storage bucket so that only Compute Engine VMs in the same VPC network can read objects. The VMs do not have public IP addresses. Which configuration should they use?
Private Google Access allows VMs without external IPs to access Google APIs; VPC Service Controls further restrict access to the VPC.
Why this answer
Private Google Access allows VMs without external IPs to access Google APIs and services via the VPC network. Combined with VPC Service Controls and bucket IAM, this ensures only VMs in the VPC can access the bucket.
A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
Why this answer
Cloud Bigtable is designed for exactly this use case — petabyte-scale, low-latency (single-digit ms), high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes. BigQuery is optimised for analytics (seconds-to-minutes latency), Cloud SQL is for OLTP (limited to tens of thousands of QPS), and Firestore is for document data with hierarchical structure.
Which Google Cloud service is a fully managed, serverless data warehouse for running SQL queries on petabyte-scale datasets?
BigQuery is the correct serverless data warehouse.
Why this answer
BigQuery is the serverless data warehouse for analytics SQL queries. Dataflow is for stream processing, Dataproc for Hadoop/Spark, and Cloud SQL for OLTP.
A company has a multi-regional deployment of a web application on Compute Engine. They want to improve latency for users worldwide and reduce load on the origin servers. They also need to protect against SQL injection and cross-site scripting attacks. Which TWO Google Cloud services should they implement?
Cloud Armor provides WAF rules to block SQL injection and XSS attacks.
Why this answer
Cloud CDN caches content at edge locations to improve latency and reduce origin load. Cloud Armor provides WAF capabilities to protect against application attacks like SQL injection and XSS. Cloud Load Balancing distributes traffic but doesn't cache.
Cloud DNS is for DNS resolution. Cloud NAT is for outbound internet.
Which Google Cloud service provides a serverless data warehouse for running SQL queries on petabyte-scale data with no need to manage infrastructure?
BigQuery is serverless, scalable, and designed for SQL analytics on large datasets.
Why this answer
BigQuery is a fully managed, serverless data warehouse that supports SQL queries on massive datasets.
A company is building a real-time leaderboard for an online game using Google Cloud. They need a database that can handle millions of updates per second with low latency and serve the current top scores. Which TWO services should they use together? (Choose 2)
Bigtable handles high write throughput with low latency.
Why this answer
Cloud Bigtable can ingest high-velocity score updates, and Memorystore (Redis) can maintain a sorted set for the leaderboard. BigQuery is too slow for real-time updates; Firestore is not designed for millions of writes per second.
A company wants to store archival data that is accessed less than once a year and needs the lowest storage cost. Which TWO Cloud Storage classes are most cost-effective for this use case?
Archive is the lowest cost, for data accessed less than once a year.
Why this answer
Archive storage has the lowest cost for data accessed less than once a year. Coldline is for data accessed every 90 days. Standard and Nearline are more expensive.
Archive and Coldline are both lower cost than Standard, but Archive is cheapest. The question asks for TWO, so Archive and Coldline are both cold storage classes. However, Archive is the best for annual access.
Coldline is for quarterly access but still cheaper than Standard. The correct TWO are Archive and Coldline, as they are the cold storage classes.
A DevOps team wants to automatically build a Docker image from a GitHub repository and store it in a private registry whenever a new tag is pushed. Which Google Cloud services should they combine?
Cloud Build can be configured with a GitHub trigger to build on tag push, and Artifact Registry stores the resulting images.
Why this answer
Cloud Build can be triggered by GitHub events (like tag push) to build a container image and push it to Artifact Registry. Artifact Registry is the managed container registry. Container Registry is deprecated.
Cloud Source Repositories is a Git repository, not a registry. Cloud Functions could trigger a build but is not the primary service.
A company wants to build a global application that requires strong consistency across regions and an SLA of 99.999% for its transactional database. The workload involves moderate write throughput (10K writes/sec) and high read throughput (100K reads/sec). Which database should they choose?
Spanner offers global distribution, strong consistency, SQL, and 99.999% availability SLA.
Why this answer
Cloud Spanner is a globally distributed relational database that provides ACID transactions across regions, strong consistency, and a 99.999% availability SLA. It can handle millions of reads per second with automatic horizontal scaling. Bigtable does not offer SQL or ACID transactions; Cloud SQL is not globally distributed; Firestore is eventually consistent by default.
An organization needs to apply security policies to protect their web application from DDoS attacks and SQL injection. Which Google Cloud service should they use?
Cloud Armor offers WAF capabilities including DDoS protection and SQL injection filtering.
Why this answer
Cloud Armor is a web application firewall (WAF) that provides DDoS protection and security rules to block threats like SQL injection. Cloud CDN is for content caching. Load Balancing distributes traffic.
Cloud NAT is for outbound connectivity.
A company runs a containerized microservices application on Google Kubernetes Engine (GKE). They want to expose a set of services externally with a single IP address, implement SSL termination, and protect against DDoS attacks. Which THREE Google Cloud services should they use together?
Cloud Armor provides DDoS protection and WAF rules to secure the application.
Why this answer
Cloud Load Balancing provides a single anycast IP and SSL termination. Cloud CDN accelerates content delivery and can be integrated with the load balancer. Cloud Armor provides DDoS protection and WAF capabilities.
Cloud NAT is for outbound internet access, Cloud VPN for site-to-site VPN, and Cloud Interconnect for dedicated connectivity.
An organisation is migrating its on-premises Oracle database to Google Cloud. They need a fully managed, PostgreSQL-compatible database with high performance for transaction processing and built-in AI capabilities for predictive analytics. Which database service should they choose?
AlloyDB is PostgreSQL-compatible, fully managed, optimised for performance, and includes AI features.
Why this answer
AlloyDB is a fully managed PostgreSQL-compatible database that offers high performance (4x faster than standard PostgreSQL) and integrated AI capabilities for vector search and predictive analytics. Cloud SQL for PostgreSQL is also managed but lacks the AI optimisations. Cloud Spanner is globally distributed but not PostgreSQL-compatible.
Bare Metal Solution runs Oracle on dedicated hardware, not managed.
A data analytics team wants to analyze large datasets using SQL and create dashboards with minimal latency. They need a serverless data warehouse and a BI tool. Which two services should they use? (Choose exactly 2.)
Enterprise BI platform for dashboards and analytics.
Why this answer
BigQuery is a serverless data warehouse for SQL analytics. Looker is a BI platform integrated with BigQuery for dashboards. Dataflow is for data processing, not storage.
Cloud Storage is for object storage, not SQL analytics. Looker Studio is free but less feature-rich for enterprise needs.
Which Google Cloud service provides a managed Redis or Memcached in-memory data store for caching and low-latency data access?
Memorystore provides managed Redis and Memcached.
Why this answer
Memorystore is the fully managed in-memory data store service for Redis and Memcached, used for caching and low-latency access.
A startup wants to deploy a containerised web application that scales automatically from zero to handle traffic spikes and charges only for the resources used during request processing. They want to avoid managing servers or Kubernetes clusters. Which compute service should they choose?
Cloud Run is serverless, scales to zero, and charges per request and compute time. Ideal for containerised web apps with variable traffic.
Why this answer
Cloud Run is a serverless compute platform that runs containers, scales to zero when not in use, and charges for resources used during request processing. It fits the description perfectly.
A company is migrating a legacy monolithic application to Google Cloud. They want to reduce operational overhead by eliminating server management while keeping the ability to run containers. The application has unpredictable traffic patterns and needs to scale to zero when idle. Which compute option is the best fit?
Cloud Run is serverless, scales to zero, and runs container images. Ideal for unpredictable traffic.
Why this answer
Cloud Run is a serverless container platform that automatically scales to zero when idle, eliminating server management and cost during idle periods. GKE requires cluster management, Compute Engine is not serverless, and App Engine Flex requires VMs always running.
A company runs a globally distributed application with users in North America, Europe, and Asia. They need to serve static content (images, videos) with low latency from edge locations. They also need to protect against DDoS attacks. Which combination of services should they use?
Cloud CDN provides edge caching for static content, and Cloud Armor protects against DDoS attacks.
Why this answer
Cloud CDN caches static content at edge locations for low latency, and Cloud Armor provides DDoS protection and WAF capabilities.
A company wants to implement a data pipeline that ingests streaming events from a global user base, processes them in real-time to detect anomalies, and stores the results in a database for low-latency querying. The solution must be fully managed. Which THREE services should they use? (Choose 3)
Dataflow performs real-time stream processing and anomaly detection.
Why this answer
Pub/Sub ingests streaming events with global scalability. Dataflow processes events in real-time with exactly-once semantics. Bigtable provides low-latency access for storing and querying processed results.
Cloud Storage is for object storage, not low-latency queries. Cloud SQL is for relational OLTP but may not match Bigtable's throughput for anomaly detection results. Cloud Functions is not suited for continuous stream processing.
A startup is building a mobile app backend that stores user profiles and session data. They need a NoSQL database with real-time synchronization across devices and offline support. Which TWO Google Cloud services are suitable?
Firestore provides real-time sync and offline support for mobile apps.
Why this answer
Firestore is a NoSQL document database with real-time listeners and offline persistence, ideal for mobile apps. Cloud Storage can store user-uploaded content like profile pictures. Memorystore is a cache, Bigtable is for time-series, Cloud Spanner is relational.
A developer wants to deploy a containerized web application that can automatically scale to zero when there are no requests, and charges only for resources used during request processing. Which Google Cloud compute service should they use?
Cloud Run is a serverless container platform that scales to zero when idle and charges per request.
Why this answer
Cloud Run is a serverless container platform that scales to zero and charges per request. Google Kubernetes Engine and Compute Engine require running instances, and App Engine Standard is a platform as a service but not container-based.
A company uses Google Workspace for email, documents, and meetings. They want to leverage an AI assistant that can help draft emails, create slides, and summarise meeting notes. Which product provides this functionality?
Gemini for Workspace (formerly Duet AI) integrates AI assistance directly into Workspace apps.
Why this answer
Duet AI (now Gemini for Workspace) provides AI-powered assistance across Gmail, Docs, Slides, Meet, and more.
A company needs to perform interactive SQL analytics on petabytes of data without managing any infrastructure. They need to query data stored in Cloud Storage and want the fastest query performance. Which Google Cloud service should they use?
BigQuery is a serverless data warehouse optimised for fast SQL analytics on large datasets.
Why this answer
BigQuery is a serverless, highly scalable data warehouse that supports SQL queries on data stored in Cloud Storage (external tables) or natively. It provides fast performance on petabyte-scale data without infrastructure management. Dataflow is for ETL, not ad-hoc analytics; Cloud SQL is for OLTP; Looker is a BI layer on top of a data warehouse.
A company wants to use a pre-trained model to extract text from scanned invoices. They need a fully managed API that can be called via REST. Which Google Cloud service should they use?
Document AI specializes in extracting data from documents like invoices with pre-trained processors.
Why this answer
Document AI is a fully managed service for document processing, including OCR and extraction from invoices. Vision AI is for general image analysis. Natural Language AI handles text sentiment/entities.
Vertex AI is a platform for custom models, not pre-built API for invoices.
A company runs a global e-commerce platform that requires a relational database with strong consistency across continents and an SLA of 99.999% availability. Which Google Cloud database service meets these requirements?
Cloud Spanner is a globally distributed relational database with strong consistency and 99.999% SLA.
Why this answer
Cloud Spanner is the only Google Cloud database that provides globally distributed, strongly consistent relational transactions with a 99.999% SLA. Cloud SQL is regional, Firestore is eventually consistent by default, and Bigtable does not support SQL and is not strongly consistent.
A startup is building a mobile app backend that requires a scalable NoSQL database with real-time synchronisation across devices. The database should support offline access and automatic conflict resolution. Which Google Cloud database service meets these requirements?
Firestore provides real-time updates, offline support, and automatic conflict resolution for mobile apps.
Why this answer
Firestore is a NoSQL document database that offers real-time listeners, offline data persistence, and automatic multi-device synchronisation. It is designed for mobile and web apps. Bigtable is for high-throughput time-series, Cloud SQL is relational, and Cloud Spanner is for globally distributed relational workloads without built-in offline syncing.
A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
Why this answer
Cloud Bigtable is designed for exactly this use case — petabyte-scale, low-latency (single-digit ms), high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes. BigQuery is optimised for analytics (seconds-to-minutes latency), Cloud SQL is for OLTP (limited to tens of thousands of QPS), and Firestore is for document data with hierarchical structure.
A data analyst needs to create interactive dashboards and reports from data stored in BigQuery. They want a fully managed business intelligence platform without building custom applications. Which Google Cloud product should they use?
Looker is a managed BI platform for interactive dashboards and reports on BigQuery.
Why this answer
Looker is a BI platform that connects to BigQuery and provides interactive dashboards, reports, and embedded analytics. Looker Studio is a free tool for simple visualizations. Data Studio is the old name.
Vertex AI is for ML.
An engineer is troubleshooting a Cloud SQL instance that is running out of memory. They want to reduce memory usage without changing the machine type. Which action would help?
Each connection consumes memory; lowering max_connections reduces memory usage.
Why this answer
Enabling automatic storage increase helps with disk space but not memory. Reducing max_connections limits concurrent connections, saving memory. Adding a read replica shares read load but doesn't reduce memory per instance.
Switching to MyISAM is not possible in Cloud SQL for InnoDB-based MySQL.
A developer wants to deploy a containerised microservice that can scale to zero when not in use and automatically scale up based on HTTP requests. The microservice is stateless and runs a custom Docker image. Which Google Cloud compute service is BEST suited for this workload?
Cloud Run is serverless and scales to zero when no requests are received, automatically scaling up on demand.
Why this answer
Cloud Run is a serverless compute platform that runs stateless containers and can scale to zero when idle. It automatically scales based on incoming requests, making it ideal for event-driven microservices. GKE requires a cluster to run even when idle, Compute Engine VMs are always on, and App Engine Standard does not support custom containers.
An organisation needs to block common web attacks like SQL injection and cross-site scripting (XSS) at the edge of Google's network, before traffic reaches their applications. Which Google Cloud service should they use?
Cloud Armor is a WAF that blocks SQL injection, XSS, and other attacks at the edge, using pre-configured or custom rules.
Why this answer
Cloud Armor is Google's web application firewall (WAF) service that protects against web attacks at the edge. It integrates with Cloud Load Balancing and Cloud CDN. Cloud CDN caches content, Cloud Load Balancing distributes traffic, and Cloud IDS is for network threat detection.
A company has a batch processing job that reads data from Cloud Storage, transforms it, and writes to BigQuery. The job runs nightly and takes approximately 2 hours. The team wants to reduce costs by using a managed service that automatically provisions and de-provisions resources. Which service should they use?
Dataflow (batch mode) is a fully managed service that autoscales resources, reads from Cloud Storage, transforms data, and writes to BigQuery, optimising cost by de-provisioning after completion.
Why this answer
Dataflow is a managed service that automatically scales resources up and down for batch and stream processing. It reads from Cloud Storage, transforms data, and writes to BigQuery. Dataproc is also managed but requires cluster configuration and is more suited for Hadoop/Spark.
Cloud Composer is for workflow orchestration, not data transformation. Cloud Functions is not suitable for long-running batch jobs.
A startup wants to run a Node.js web application with zero server management and automatic scaling. They expect unpredictable traffic and want to minimise costs. Which Google Cloud service should they choose?
Standard Environment automatically scales, scales to zero, and is cost-effective for variable traffic.
Why this answer
App Engine Standard Environment is a PaaS that automatically scales, manages the runtime, and can scale to zero. App Engine Flexible runs in VMs, does not scale to zero, and costs more. Compute Engine requires manual scaling.
Cloud Run is also serverless but for containers; App Engine Standard is simpler for code-based apps.
A company wants to set up a hybrid cloud network connecting their on-premises data center to Google Cloud with high bandwidth and low latency. They also need to provide DDoS protection for their applications. Which THREE services should they consider? (Choose THREE.)
Cloud CDN uses Google's global edge network to deliver content quickly and can absorb some DDoS traffic.
Why this answer
Cloud Interconnect provides dedicated connectivity, Cloud CDN caches content for performance, and Cloud Armor provides DDoS protection. VPN is not high bandwidth; VPC is a logical network, not a connectivity solution.
A developer needs to trigger a serverless function whenever a new file is uploaded to a Cloud Storage bucket. The function will process the file and store results in Firestore. Which Google Cloud service should they use for the function?
Cloud Functions is purpose-built for event-driven, single-purpose functions that respond to GCP events like storage object finalize.
Why this answer
Cloud Functions is an event-driven serverless compute service that can be triggered by Cloud Storage events.
A security team needs to protect a web application behind an HTTP(S) Load Balancer from SQL injection and cross-site scripting (XSS) attacks. Which Google Cloud service provides these protections?
Cloud Armor provides WAF capabilities with rules to block SQL injection and XSS.
Which Google Cloud service provides a fully managed, scalable NoSQL document database suitable for mobile and web applications with real-time data synchronization?
Firestore is a NoSQL document database designed for mobile and web apps with real-time listeners and offline persistence.
Why this answer
Firestore is a document database with real-time syncing and offline support. Bigtable is wide-column, Cloud SQL is relational, and Memorystore is a cache.
A data engineer needs to process a continuous stream of events from a global user base, perform real-time transformations, and write the results to both Cloud Storage and BigQuery. The solution must handle sudden traffic spikes and be fully managed (no server management). Which combination of services should the engineer use?
Dataflow reads from Pub/Sub, processes, and writes to both Cloud Storage and BigQuery, all fully managed.
Why this answer
Pub/Sub ingests and buffers the stream, Dataflow (a fully managed stream processing service) reads from Pub/Sub, performs transformations, and writes to Cloud Storage and BigQuery with exactly-once semantics. Cloud Functions is for lightweight event-driven code, not heavy stream processing. Cloud Scheduler is for cron jobs.
Composer is for workflow orchestration.
A company is deploying a stateful web application on Compute Engine that requires persistent block storage for the database. They need high IOPS and the ability to dynamically resize the disk without downtime. Which TWO storage options meet these requirements? (Choose two.)
SSD persistent disk offers high IOPS and can be resized online.
Why this answer
Persistent Disk supports dynamic resizing without downtime (when using live resize) and offers high IOPS. Additionally, you can use SSD persistent disks for higher IOPS. Alternatively, Google Cloud Hyperdisk provides higher performance and also supports resizing.
However, the simplest answer is to choose Persistent Disk (which includes both standard and SSD). Since the question expects two, and Filestore is file storage, not block storage, and Cloud Storage is object storage. The two correct are: Persistent Disk (standard and SSD).
But the options might differentiate. Let's create options: A. Persistent Disk (standard), B.
Persistent Disk (SSD), C. Filestore, D. Cloud Storage, E.
Local SSD. Local SSD provides high IOPS but cannot be resized and is ephemeral. So the two that meet both requirements are Persistent Disk (any type) and Hyperdisk.
Since Hyperdisk is not listed, we consider Persistent Disk (SSD and standard both allow resizing and high IOPS). So I'll make A and B correct.
A developer wants to deploy a containerised web application that can scale to zero when not in use, and only pay for actual request processing time. Which Google Cloud compute service should they choose?
Cloud Run is a fully managed serverless container platform that scales to zero and charges only for resources used during request processing.
Why this answer
Cloud Run is a serverless compute platform that runs containers, scales to zero when idle, and charges per request and CPU/memory usage only during request handling. App Engine Standard can scale to zero but does not support arbitrary containers. GKE and Compute Engine are provisioned infrastructure that does not scale to zero.
A developer wants to build a CI/CD pipeline that automatically builds a Docker container from a GitHub repository, stores the image securely, and deploys it to Cloud Run. Which THREE services should they integrate? (Select 3)
Cloud Build can automatically build Docker images from source code.
Why this answer
Cloud Build builds the Docker image, Artifact Registry stores the image, and Cloud Run deploys it. Cloud Storage is for object storage, not container images. Cloud Build triggers can be used with GitHub, but the question asks for services that are part of the pipeline; Cloud Source Repositories is a code repository, not required if using GitHub.
A startup wants to deploy a containerized web application that can scale to zero during periods of no traffic, and they want to minimize operational overhead. Which Google Cloud compute service is the BEST fit?
Cloud Run is serverless, scales to zero, and handles infrastructure automatically.
Why this answer
Cloud Run is a serverless container platform that automatically scales your containers up and down, including scaling to zero when there is no traffic. It abstracts away infrastructure management, making it ideal for this use case.
A company wants to implement a serverless event-driven architecture where object uploads to Cloud Storage trigger a function that processes the file and stores results in Firestore. The function needs to be written in Python. Which three Google Cloud services are required?
Cloud Functions runs the Python code in response to the Cloud Storage event.
Why this answer
The architecture uses Cloud Storage (trigger), Cloud Functions (compute), and Firestore (database). Cloud Build is for CI/CD, not runtime. Pub/Sub could be used but is not required if the function is triggered directly from Cloud Storage.
A data scientist needs to build a custom machine learning model using TensorFlow on Google Cloud. The training data is stored in Cloud Storage and is hundreds of gigabytes. The data scientist wants to use a managed service that handles hyperparameter tuning and distributed training without managing infrastructure. Which TWO services can be used together to achieve this? (Choose 2)
Vertex AI Training provides managed distributed training and hyperparameter tuning.
Why this answer
Vertex AI Training is a managed service for training ML models, supporting distributed training and hyperparameter tuning. Vertex AI Workbench is a Jupyter-based notebook environment for prototyping. Cloud Functions is for event-driven code, not ML training.
Cloud Run is for containers. BigQuery ML allows building models using SQL but is limited to simple models.
A startup wants to deploy a containerized web application that can scale to zero when not in use and automatically scale based on request traffic. They have limited DevOps experience and want minimal infrastructure management. Which compute service should they choose?
Cloud Run is a fully managed serverless container platform that scales to zero and automatically scales based on requests.
Why this answer
Cloud Run is a serverless container platform that scales to zero, automatically scales based on requests, and requires no cluster management, making it ideal for this scenario.
A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
Why this answer
Cloud Bigtable is designed for exactly this use case — petabyte-scale, low-latency (single-digit ms), high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes. BigQuery is optimised for analytics (seconds-to-minutes latency), Cloud SQL is for OLTP (limited to tens of thousands of QPS), and Firestore is for document data with hierarchical structure.
A company is building a data pipeline that ingests events from multiple sources, processes them in real-time, and stores the results in a data warehouse for analysis. They need a fully managed, serverless solution for stream processing. Which THREE Google Cloud services should they use?
Pub/Sub ingests streaming events.
Why this answer
Pub/Sub ingests events. Dataflow processes streams. BigQuery stores and analyzes results.
Cloud Functions is for lightweight event-driven functions, not stream processing. Dataproc is for batch processing.
An engineer needs to create a Pub/Sub subscription that delivers messages exactly once to a subscriber that processes them idempotently. The subscriber runs on Compute Engine and must handle messages at least once but the engineer wants to minimise duplicates. Which subscription type should be configured?
Pub/Sub supports exactly-once delivery on pull subscriptions, minimising duplicates while the subscriber processes idempotently.
Why this answer
Pub/Sub offers 'exactly-once delivery' as a subscription feature when enabled. It reduces duplicates but requires idempotent processing because exactly-once is best-effort. Push and pull subscriptions can both use exactly-once delivery. 'Exactly-once' is not a subscription type but a property; the question tests knowledge that Pub/Sub supports exactly-once delivery on subscriptions.
A data analyst wants to create interactive dashboards and reports using data from BigQuery, without writing code. Which Google Cloud BI tool should they use?
Looker Studio (formerly Data Studio) is a free, drag-and-drop BI tool for creating dashboards and reports.
Why this answer
Looker Studio is a free, self-service BI tool that allows users to create interactive dashboards and reports from various data sources including BigQuery, with a drag-and-drop interface. Looker is a more advanced enterprise BI platform. Data Studio is the former name; it is now Looker Studio.
Dataflow is for data processing.
A DevOps engineer wants to automatically delete a Cloud Storage object after 30 days from creation. The object is stored in a bucket with the 'Standard' storage class. Which approach should the engineer use?
Lifecycle rules can specify an age-based condition to delete objects automatically.
Why this answer
Object Lifecycle Management rules can be configured on a bucket to delete objects based on age (days since creation). The rule sets a condition (e.g., age: 30) and action (Delete). Changing the storage class or using bucket lock does not delete objects.
Object versioning is for keeping multiple versions.
A development team runs a web application on Cloud Run. They need to store session state across requests. Which Google Cloud service should they use?
Memorystore provides a managed Redis cache ideal for storing session state.
Why this answer
Cloud Run instances are stateless; for session state, use an external caching layer like Memorystore (Redis). Pub/Sub is for messaging, Cloud SQL for relational data, and Cloud Storage for objects.
A company wants to migrate its on-premises PostgreSQL database to Google Cloud with minimal application changes. They need high availability and want to leverage AI-powered optimizations for performance. Which service should they choose?
AlloyDB is fully PostgreSQL-compatible, offers high availability, and includes AI-powered optimizations for performance.
Why this answer
AlloyDB is a fully managed PostgreSQL-compatible database optimized for demanding workloads, with high availability and AI-powered performance features. Cloud SQL for PostgreSQL also supports HA but lacks the AI optimizations. Cloud Spanner is not PostgreSQL-compatible.
Bigtable is NoSQL.
An e-commerce company needs a globally distributed relational database with strong consistency and 99.999% SLA to handle customer orders and inventory across multiple regions. They require SQL compatibility and automatic replication. Which database should they use?
Cloud Spanner provides global distribution, strong consistency, and 99.999% SLA.
Why this answer
Cloud Spanner is a globally distributed relational database with strong consistency, high availability (99.999% SLA), and SQL support, perfect for multi-region transactional workloads.
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