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PROFESSIONAL-DATA-ENGINEER · Question #309

You stream order data by using a Dataflow pipeline, and write the aggregated result to Memorystore. You provisioned a Memorystore for Redis instance with Basic Tier, 4 GB capacity, which is used by…

The correct answer is B. Create a new Memorystore for Redis instance with Standard Tier. Set capacity to 5 GB and create multiple read replicas. Delete the old instance. Option B is correct because scaling to hundreds of read-only clients requires read replicas to distribute the read load, while Standard Tier provides high availability (automatic failover) to protect write access - together satisfying both requirements. The slight capacity bump…

Submitted by stefanr· Mar 30, 2026Designing data processing systems

Question

You stream order data by using a Dataflow pipeline, and write the aggregated result to Memorystore. You provisioned a Memorystore for Redis instance with Basic Tier, 4 GB capacity, which is used by 40 clients for read-only access. You are expecting the number of read-only clients to increase significantly to a few hundred and you need to be able to support the demand. You want to ensure that read and write access availability is not impacted, and any changes you make can be deployed quickly. What should you do?

Options

  • ACreate a new Memorystore for Redis instance with Standard Tier. Set capacity to 4 GB and read replica to No read replicas (high availability only). Delete the
  • BCreate a new Memorystore for Redis instance with Standard Tier. Set capacity to 5 GB and create multiple read replicas. Delete the old instance.
  • CCreate a new Memorystore for Memcached instance. Set a minimum of three nodes, and memory per node to 4 GB. Modify the Dataflow pipeline and all clients
  • DCreate multiple new Memorystore for Redis instances with Basic Tier (4 GB capacity). Modify the Dataflow pipeline and new clients to use all instances.

How the community answered

(61 responses)
  • A
    8% (5)
  • B
    75% (46)
  • C
    3% (2)
  • D
    13% (8)

Explanation

Option B is correct because scaling to hundreds of read-only clients requires read replicas to distribute the read load, while Standard Tier provides high availability (automatic failover) to protect write access - together satisfying both requirements. The slight capacity bump to 5 GB accounts for replication overhead, and creating a new instance rather than migrating in-place enables fast deployment.

Option A fails because selecting "No read replicas" means all hundreds of clients still hammer a single endpoint - HA alone does not distribute read traffic, it only provides failover.

Option C is wrong on two counts: switching to Memcached requires rewriting both the Dataflow pipeline and all clients, violating the "deploy quickly" requirement, and Memcached is a different product with no Redis-compatible API or persistence semantics.

Option D is disqualified because Basic Tier has no high availability - there is no replica or automatic failover, so write availability is unprotected, and it also requires pipeline changes to fan out writes across instances.

Memory tip: Memorize this pairing - Standard Tier = HA for the write endpoint; Read Replicas = horizontal scale for reads. Whenever a question demands both write availability and read scalability, you need Standard Tier plus read replicas, not one or the other.

Topics

#Memorystore for Redis#Read Replicas#Scaling#High Availability

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