Your company runs a containerized e-commerce API on GKE in us-central1. To reduce latency during flash-sale traffic, you need an external cache for 500-byte session objects with 15-minute TTLs. The cache must support Redis commands, provide automatic failover across zones, and require minimal operational effort. Which Google Cloud service best meets these needs?
Provision Memorystore for Redis in Standard Tier with automatic failover across two zones.
Deploy Cloud Bigtable and enable its in-memory cache feature for session data.
Run a Redis StatefulSet on GKE and attach a regional persistent disk for high availability.
Create a Cloud SQL for PostgreSQL instance using a memory-optimized machine type to store session rows.
Memorystore for Redis is a fully managed, in-memory data store that speaks the native Redis protocol. When you create an instance in Standard Tier, the service automatically provisions a replica in a different zone within the same region, replicates data asynchronously to that replica, and performs automatic failover if the primary node becomes unavailable. Because Google operates the service, there is no need for customers to handle cluster installation, patching, or failover scripting, satisfying the minimal-operations requirement.
Cloud SQL and Cloud Bigtable are durable databases, not low-latency in-memory caches, and they do not support Redis commands. Running a self-managed Redis StatefulSet on GKE could meet the protocol requirement but leaves failover, monitoring, and maintenance tasks to your team, conflicting with the low-operations mandate.
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What is Memorystore for Redis?
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How does automatic failover work in Memorystore for Redis?
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Why isn’t Cloud SQL or Cloud Bigtable suitable for this use case?
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What is Memorystore for Redis?
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What does TTL mean in caching?
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What is the difference between Memorystore Standard Tier and Basic Tier?
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