google_ redis_ instance cost estimation
A managed Redis instance. Priced per GB-hour by service tier (Basic or Standard) and capacity.
A google_
Two service tiers:
Basic (tier = "BASIC"): single-node, no SLA, no replication. Right for dev/test. About $0.049/GB-hour.
Standard (tier = "STANDARD_
Memorystore is sized by memory_
Network tier doesn't apply (Memorystore is internal to GCP). Outbound traffic from clients goes through normal GCP egress rules.
Read replicas (read_
For workloads that need more than 300 GB or Redis Cluster mode, Memorystore for Redis Cluster (google_
c3x reads tier and memory_
Terraform example
A minimal but realistic configuration that C3X can estimate.
resource "google_redis_instance" "session_cache" {
name = "session-cache"
tier = "STANDARD_HA"
memory_size_gb = 5
region = "us-central1"
redis_version = "REDIS_7_2"
display_name = "Session cache"
reserved_ip_range = "10.0.0.0/29"
redis_configs = {
maxmemory-policy = "allkeys-lru"
}
}Pricing dimensions
What you actually pay for when you provision google_.
| Dimension | Unit | What's being charged |
|---|---|---|
| Basic tier | per GB-hour | Single-node Redis instance. No SLA, no replication. Right for dev/test. $0.049/GB-hour in us-central1 |
| Standard HA tier | per GB-hour | Primary/replica with 99.9% SLA. Slightly more expensive than Basic. $0.054/GB-hour in us-central1 |
| Read replicas | per replica per GB-hour | Each additional read replica is billed at the same per-GB-hour rate as the primary. |
| Outbound network egress | per GB | Bytes from clients leaving the GCP region. Free intra-region. |
Optimization tips
Common ways to reduce google_ cost without changing the workload.
Use Basic tier for non-production
About 10%Basic is 10% cheaper than Standard HA. For dev/staging where there's no SLA requirement, Basic is sufficient.
Right-size memory by actual usage
Linear with size reductionMemorystore exposes memory metrics in Cloud Monitoring. If you're consistently using less than 50% of provisioned memory, drop the size. Memory is the only thing you're paying for.
Buy Committed Use Discounts for steady-state
17-30%1-year CUDs cut Memorystore prices by ~17%; 3-year by ~30%. Right for production caches that won't shrink.
Use read replicas only when read-after-write isn't required
Avoid unnecessary replica costEach read replica doubles the cost of its own size. Only add replicas if you actually have high read traffic that the primary can't serve. Many workloads don't need them.
Consider Memorystore for Redis Cluster for larger workloads
At very large scaleCluster mode (google_
FAQ
Basic or Standard HA?
Standard HA for any production workload (the 10% premium is small and you get failover). Basic for dev/test/ephemeral where downtime is acceptable.
How does c3x compute Memorystore cost?
c3x multiplies memory_
What about Memorystore for Redis Cluster?
Different resource type (google_
Are connections to Memorystore free?
Yes, within the same region. Memorystore is VPC-internal; intra-region traffic is free. Cross-region access requires VPC peering and incurs cross-region egress.
Related resources
More Google Cloud resources
Further reading
- GCP Memorystore cost: you pay for provisioned capacity per hour
Memorystore for Redis bills per GB of provisioned capacity by the hour, by tier (Basic or Standard with a replica). Capacity, not usage, sets the bill, so right-sizing the instance and choosing the tier are the levers. Here is how it prices.
- Azure Cache for Redis cost: tier and size, billed per hour
Azure Cache for Redis bills per hour by tier (Basic, Standard, Premium, Enterprise) and cache size, provisioned regardless of use. Basic has no replica; Standard and above add availability. Here is how the tiers price and how to choose.
- The cost of running Redis in the cloud
Managed Redis (ElastiCache, Memorystore, Azure Cache) bills mostly for the node size and count you run, per hour, plus data transfer and optional replicas. Here is how Redis pricing works and how to size it without overpaying.
- Caching to reduce cloud cost: deflect the work you are paying for
Every cache hit is a database query, a Lambda invocation, or an origin fetch you did not pay for. Caching is one of the few levers that cuts cost and improves latency at once. Here is where to add it and how the math works.
Estimate this resource in your own Terraform
Free, open source, no API key. C3X parses your Terraform and shows line-item cost for every resource, including google_.