Analyze and optimize technical and business processes

A company is migrating its on-premises Oracle database to Cloud SQL for PostgreSQL. The database team wants to minimize downtime during migration. Which approach should they use?

An e-commerce platform uses Cloud Spanner for order processing. Recently, latency spikes have occurred during flash sales. The team suspects hot spots due to monotonically increasing order IDs. Which table design change would best solve this?

A company uses BigQuery for analytics. They have a large partitioned table that is queried frequently. The query performance has degraded over time. Which optimization should they try first?

An organization runs a Kubernetes cluster on GKE with cluster autoscaling enabled. They notice that pods are frequently in 'Pending' state due to insufficient CPU, but the cluster autoscaler does not add nodes quickly enough. What is the most likely cause?

Your company runs a multi-tier web application on Google Kubernetes Engine (GKE). The application consists of a frontend service, a backend API service, and a PostgreSQL database deployed using a StatefulSet with persistent volumes. The backend service exposes a gRPC endpoint. Recently, the team noticed that the backend service experiences intermittent high latency and occasional timeouts. The frontend service is stateless and scales well. The backend service is CPU-bound. The database is not the bottleneck. The cluster has three nodes of type n1-standard-4. The backend service is deployed with 10 replicas, each requesting 1 CPU and 2 Gi memory. Node utilization is around 70% CPU. The team suspects the network is the issue. However, after reviewing the GKE monitoring dashboard, they see that the network bytes sent/received per second for the backend pods is well below the node's network bandwidth limit. The latency spikes seem correlated with periods of high CPU throttling on the backend pods. The backend service's gRPC requests are small (under 1 KB), and the responses are also small. The team has already optimized the application code. What should the team do to reduce latency?

A company runs a monolithic application on Compute Engine. They want to modernize by moving to microservices on Google Kubernetes Engine (GKE) to improve deployment frequency and resource utilization. However, they are concerned about the increased operational complexity. Which approach best balances modernization benefits with operational overhead?

Refer to the exhibit. A DevOps engineer created this Terraform configuration to deploy a Compute Engine instance. After applying, they notice the instance is not accessible from the internet. What is the most likely cause?

Drag and drop the steps to implement a disaster recovery plan using Cloud Storage and Cloud Functions in the correct order.

Match each GCP migration term to its description.

A startup deploys a web application on Compute Engine instances behind an HTTP load balancer. They need to handle unpredictable spikes in traffic with minimal operational overhead. What is the simplest scaling approach?

A company stores backup data in Cloud Storage. They observe high egress costs when clients download backups. Additionally, they must retain backups for 7 years for compliance. Which optimization should they implement first?

A company runs a streaming data pipeline using Dataflow to process real-time data and insert into BigQuery. Recently, workers are frequently failing with out-of-memory errors and the pipeline latency is increasing. What should they do to resolve the issue?

A developer is migrating a stateful application to GKE. The application requires persistent storage with high IOPS for a database. Which storage option is most suitable?

A company uses Cloud Composer to manage Apache Airflow workflows. They want to optimize costs. Which practice is most effective?

A company uses Cloud Armor to protect their HTTP load balancer. They need to block traffic from a specific set of IP addresses and also prevent SQL injection attacks. Which two configurations should they use? (Choose TWO.)

A company runs a large-scale data processing pipeline using Dataflow with streaming data from Pub/Sub. They notice increasing costs due to high data shuffle operations. They want to optimize the pipeline performance and cost. Which approach should they take?

A company is using Cloud Storage for backups and wants to minimize costs. The backups are accessed infrequently and can tolerate retrieval delays. Which storage class is most appropriate?

A company migrated their on-premises database to Cloud SQL and now experiences high latency for read-heavy workloads. How can they optimize performance?

A company is using BigQuery for analytics and wants to optimize query costs. They have many ad-hoc queries that scan large tables. What is the best practice?

A company has a multi-region deployment of App Engine and wants to optimize request routing for latency and cost. Which GCP service should they use?

Which THREE steps can reduce processing costs in a Dataflow streaming pipeline? (Choose three.)

Refer to the exhibit. The output is from `gcloud compute instances describe instance-1 --format=json`. What can you conclude from this output?

A team uses Cloud Build for CI/CD. The builds are taking longer than expected due to dependency downloads. What is the best practice to speed up builds?

A Cloud Spanner instance is experiencing high latency for point reads. The instance has 5 nodes and the read throughput is moderate. The table has a primary key with monotonically increasing values. What is the most likely cause and optimization?

A company commits to using Compute Engine for 3 years and wants the maximum discount. Which purchasing option should they use?

A company stores large amounts of data in Cloud Storage and wants to reduce costs. Which two actions should they take? (Choose two.)

A company runs a web application on App Engine Standard environment. The application experiences downtime during deployments due to traffic shifting. Which two strategies should they implement to improve reliability? (Choose two.)

A company is running a web application on Compute Engine instances that average 20% CPU utilization. They want to reduce costs without impacting performance. What is the most effective action?

A company uses Cloud Armor to protect their HTTP Load Balancer from DDoS attacks. Recently, they experienced a targeted attack that bypassed Cloud Armor's predefined rules. The attack involved a high rate of legitimate-looking requests from a small set of IPs that made the application unresponsive. The team needs to block the attack quickly without affecting legitimate users. What should they do?

A media company's analytics team runs a nightly Apache Spark ETL job on a Dataproc cluster with 20 worker nodes. The job processes raw logs from Cloud Storage and writes Parquet files back to Cloud Storage. The cluster is created before the job starts and deleted after the job finishes, taking about 90 minutes total. The team wants to reduce the cost of this workload without changing the Spark code or increasing job runtime. What should they do?

A retail company runs a customer-facing API on GKE Autopilot in a single region. During a quarterly sales event, traffic triples for six hours and then returns to baseline. The SRE team wants to keep the API responsive during the spike, control spend, and avoid manual intervention. They have already configured a Horizontal Pod Autoscaler based on CPU utilization with a target of 60%. Which additional action best addresses the remaining scaling bottleneck?

A healthcare company runs a regulated patient-portal application on Google Cloud. Auditors require evidence that infrastructure changes are reviewed before they reach production and that production access is limited. The platform team currently applies Terraform changes directly from engineer laptops using personal credentials. Which two practices should the team adopt to satisfy the auditors while keeping delivery efficient? (Choose two.)

A healthcare company runs a critical patient portal on Compute Engine. The portal uses a Cloud SQL for PostgreSQL database. The company needs to perform a major version upgrade of the database with minimal downtime and wants to minimize the risk of data loss. They also want to be able to roll back quickly if issues arise. Which approach should they take?

A company runs a high-traffic web application on Google Kubernetes Engine (GKE). The application uses a Cloud SQL for MySQL instance as its backend. The operations team wants to optimize the cost of the GKE cluster and the Cloud SQL instance without sacrificing performance or availability. Which two actions should they take? (Choose two.)

A retail company runs a legacy order-processing system on a single Compute Engine VM with a local SSD. The system is business-critical and must be migrated to Google Cloud with minimal downtime and no data loss. The database is PostgreSQL, and the company wants to move to a managed service. The cutover window is only 30 minutes. Which migration approach should the architect recommend?

A healthcare company stores patient records in Cloud Storage buckets across multiple projects. An audit reveals that several buckets containing protected health information are publicly accessible. The security team wants a centralized, automated way to detect and remediate public access across all current and future projects, with minimal operational effort. Which solution should the architect recommend?

A media company uses a multi-project Google Cloud organization. They want to optimize their cloud spend across all projects without sacrificing performance or reliability. They have already implemented committed use discounts for Compute Engine. Which two additional actions should the architect recommend to reduce costs? (Choose two.)

A startup is deploying a new web application on Google Cloud. They want to ensure that their development, staging, and production environments are isolated from each other for security and billing purposes. They also want to apply different IAM policies per environment. Which Google Cloud resource hierarchy structure should the architect recommend?

A financial services company runs a high-volume transaction processing system on Google Cloud. They need to ensure that the system can handle sudden spikes in traffic during market open and close. The system uses a managed instance group of Compute Engine VMs behind a load balancer. They want to optimize costs while maintaining performance during peak hours. Which approach should the architect recommend?

A logistics company has a BigQuery dataset that is queried heavily by scheduled reports each morning. Finance wants predictable monthly spend and the ability to attribute query cost to each department. Analysts currently run ad hoc queries against on-demand pricing, and costs vary widely month to month. What should the architect recommend?

An online learning platform runs its API on a regional managed instance group behind an external Application Load Balancer. The operations team wants to release new versions with the ability to shift a small percentage of user traffic to the new version first, then increase it gradually, and roll back instantly if error rates rise. What should they implement?

A startup is deploying a new web application on Google Cloud. The application runs in containers on Google Kubernetes Engine (GKE) and uses a Cloud SQL for MySQL instance. The team wants to follow the principle of least privilege for the application's access to Cloud SQL. Which method should the architect recommend for authenticating the application to Cloud SQL?

A healthcare analytics firm processes patient records in a Dataflow streaming pipeline that writes enriched events to BigQuery. The pipeline currently uses a fixed number of workers sized for peak load, and utilization is low for most of the day. The team wants the pipeline to scale with incoming volume while keeping late-arriving events correct and bounded in cost. What should they do?