PCD Designing highly scalable, available, and reliable cloud-native applications Practice Test 5 — 15 Questions

Question 1

A Cloud Function (background function, event-driven) consistently logs this timeout error. The function processes messages from Pub/Sub. After increasing the max instances from 10 to 100, the error rate increases. What is the most likely cause of the timeouts?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The function depends on an external service that is rate-limited; scaling up causes more calls and timeouts. Increasing the max instances from 10 to 100 amplifies the number of concurrent function invocations. If the function depends on an external service (e.g., a third-party API or database) that enforces rate limits, the higher concurrency causes more requests to be throttled or rejected, leading to increased timeouts. This is a classic scaling anti-pattern where horizontal scaling exacerbates a bottleneck instead of relieving it.

Answer

Increase memory allocation to speed up processing

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Use a larger instance type (Cloud Functions does not have instance types)

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Migrate the function to Cloud Run for longer timeouts

Answer

The function timeout is set too low; increase it to 9 minutes

Question 2

A company is designing a microservices architecture on Google Kubernetes Engine (GKE). They want to ensure zero-downtime deployments. Which strategy should they use?

Accepted Answer

Blue/green deployment. Blue/green deployment is the correct strategy for achieving zero-downtime deployments on GKE because it runs two identical environments (blue and green) and switches traffic instantly via a Kubernetes Service or Ingress. This eliminates any period where the application is unavailable, as the old version remains live until the new version is fully ready and traffic is cut over. GKE's LoadBalancer or Ingress controller can route all traffic to the new environment with a single configuration update, ensuring no requests are dropped.

Answer

Recreate

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Rolling update

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Canary deployment

Question 3

A developer is using Cloud Spanner for a global application. They need to design a schema to avoid hotspots. Which practice should they follow?

Accepted Answer

Use a hash prefix on the primary key. Cloud Spanner uses a distributed architecture that splits data across splits based on the primary key. A monotonically increasing or timestamp-based key causes all new writes to hit a single split, creating a hotspot. By using a hash prefix on the primary key, writes are distributed uniformly across all splits, avoiding hotspots and maximizing write throughput.

Answer

Use a UUID primary key

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Use a monotonically increasing primary key

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Use a composite primary key with a timestamp

Question 4

What is the primary benefit of using Cloud Load Balancing with global anycast IP?

Accepted Answer

Reduces latency for users worldwide. Cloud Load Balancing with a global anycast IP directs user traffic to the nearest available backend instance based on network topology and latency. This minimizes the number of network hops and reduces round-trip time, providing lower latency for users worldwide compared to a single-region deployment.

Answer

Provides DDoS protection

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Supports WebSocket

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Enables cross-zone failover

Question 5

A company runs a stateful application on Compute Engine with local SSDs. They want high durability. Which approach should they use?

Accepted Answer

Use persistent disks instead of local SSDs for automatic replication. Local SSDs are ephemeral and data is lost when the VM is stopped or terminated. Persistent disks, by contrast, automatically replicate data within the same zone (or across zones if using regional persistent disks), providing high durability. Option D correctly identifies that switching to persistent disks is the appropriate approach for durability, as local SSDs lack built-in redundancy.

Answer

Replicate data to another zone using synchronous replication

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Use a RAID 1 array across multiple local SSDs

Answer

Take regular snapshots of local SSDs

Question 6

An application on Cloud Run needs to handle traffic spikes. Which configuration setting should be adjusted?

Accepted Answer

Set min and max instances. Cloud Run automatically scales the number of container instances based on incoming traffic. By setting min and max instances, you control the scaling range: a minimum ensures a baseline of warm instances to absorb sudden spikes, while a maximum caps costs and prevents resource exhaustion. This is the primary lever for handling traffic spikes in a serverless environment.

Answer

Enable HTTP/2

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Increase CPU allocation

Answer

Increase memory

Question 7

A developer is designing a data pipeline using Pub/Sub and Dataflow. They need to guarantee at-least-once delivery with no duplicates in the sink. Which Dataflow feature should they use?

Accepted Answer

Exactly-once processing. Dataflow's exactly-once processing (also known as 'exactly-once semantics' or 'EOS') ensures that each record is processed exactly once, even if the pipeline restarts or fails. This eliminates duplicates in the sink while still guaranteeing at-least-once delivery from Pub/Sub, because Dataflow uses a combination of source-side deduplication (via Pub/Sub message IDs) and sink-side idempotent writes (via the Dataflow sink's commit protocol). The result is that no duplicate records are written to the sink, meeting the requirement of no duplicates.

Answer

Checkpointing

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Idempotent writes

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Windowing

Question 8

A team is migrating a monolithic app to microservices. They need to handle distributed transactions across services. Which pattern should they use?

Accepted Answer

Saga pattern. The Saga pattern is the correct choice for managing distributed transactions across microservices because it breaks a long-lived transaction into a sequence of local transactions, each with a compensating action to roll back if a subsequent step fails. This avoids the tight coupling and performance bottlenecks of distributed locking or two-phase commit, which are unsuitable for cloud-native, highly scalable environments. Sagas can be orchestrated (via a coordinator) or choreographed (via events), and they align with eventual consistency principles required for high availability.

Answer

Eventual consistency with compensation

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Distributed lock manager

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Two-phase commit

Question 9

An application uses Cloud SQL for read-heavy workloads. To scale reads, which configuration is best?

Accepted Answer

Add read replicas across zones. Read replicas in Cloud SQL allow you to offload read traffic from the primary instance to one or more replica instances, which are kept in sync using asynchronous replication. This configuration directly scales read capacity by distributing SELECT queries across replicas, making it the best choice for read-heavy workloads.

Answer

Use connection pooling

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Enable high availability with standby

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Enable automatic storage increase

Question 10

A company uses Cloud Storage for backups. They need to comply with a regulation requiring immutable storage for 7 years. Which bucket configuration should they use?

Accepted Answer

Set a retention policy and lock the bucket. Locking a retention policy in Cloud Storage enforces immutable storage for the specified duration (7 years). Once locked, the retention policy cannot be removed or shortened, ensuring compliance with regulations that require data to be preserved in its original state and not modifiable or deletable until the retention period expires.

Answer

Use a bucket with a retention policy (not locked)

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Set a lifecycle rule to archive to Coldline

Answer

Enable Object Versioning

Question 11

Which two strategies should be implemented to ensure high availability for a Compute Engine instance group running a stateless web application?

Accepted Answer

Use regional managed instance group. Regional managed instance groups (MIGs) distribute instances across multiple zones within a region, providing automatic healing and high availability by recovering from zone failures. Combined with a global load balancer, they ensure traffic is routed only to healthy instances, making them ideal for stateless web applications that require resilience against zonal outages.

Answer

Use preemptible VMs

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Use global load balancing

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Use instance templates

Question 12

Which two design patterns help decouple microservices?

Accepted Answer

Event-driven architecture. Event-driven architecture (B) decouples microservices by allowing them to communicate asynchronously through events, eliminating direct dependencies between services. This pattern uses a message broker (e.g., Kafka, RabbitMQ) to publish and consume events, enabling services to evolve independently without blocking each other.

Answer

Service mesh

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Database per service

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Circuit breaker

Question 13

Refer to the exhibit. A developer notices that instance-3 is in TERMINATED state. What is the most likely reason?

Accepted Answer

The instance had automatic restart disabled. When an instance's 'automatic restart' is disabled, the instance will not be automatically restarted after a host maintenance event or a failure. If the underlying host experiences an issue, the instance transitions to TERMINATED state instead of being migrated or restarted. This is the most likely reason for instance-3 being in TERMINATED state while other instances remain running.

Answer

The instance was deleted

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The instance was preempted

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The instance's zone was unavailable

Question 14

Refer to the exhibit. Which schema or index change would most improve this query?

Accepted Answer

Create a secondary index on Orders.CustomerID and Customers.CustomerID. Creating secondary indexes on both `Orders.CustomerID` and `Customers.CustomerID` allows Spanner to perform an index-based join without scanning the full base tables. Spanner uses distributed, strongly consistent secondary indexes to avoid full table scans, which dramatically reduces latency and resource consumption for join queries. Without these indexes, Spanner must perform a broadcast join or a full table scan on both tables, which is inefficient at scale.

Answer

Create a primary key on CustomerID

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Rewrite the query as a subquery

Answer

Increase the number of Spanner nodes

Question 15

Refer to the exhibit. The user developer@example.com tries to create a firewall rule and receives a permission denied error. What is the most likely reason?

Accepted Answer

All of the above. All of the above. In Google Cloud, creating a firewall rule requires the `compute.securityAdmin` role (which includes `compute.firewalls.create` permission) or the `compute.networkAdmin` role (which also includes `compute.firewalls.create` permission). If the user lacks any of these roles or the specific permission, they will receive a permission denied error. While options A, B, and C are individually true statements, the question asks for the 'most likely reason,' and since all three are valid, the single correct answer is D. This tests the understanding that multiple permission deficiencies can cause the same error.

Answer

The user lacks compute.networkAdmin role

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The user lacks compute.securityAdmin role

Answer

The user is missing compute.firewalls.create permission