Managed Valkey Service

Valkey is a highly versatile and blazing-fast in-memory data store and cache that can significantly boost the performance of your applications. It is the BSD-3-Clause licensed, Linux Foundation-governed fork of Redis 7.2 and a drop-in replacement for it. Managed Valkey Service offers a hassle-free solution for deploying and managing Valkey clusters, ensuring that your data is always available and responsive.

Deployment Details

Service runs Valkey on the freshworks-oss redis-operator, which manages Sentinel-based HA and selects the Valkey engine natively via spec.engine: Valkey — so the official valkey/valkey image is used directly, with no Redis-compatibility shim.

storageClass is annotated as immutable in the chart schema — see docs/storage-immutability.md for the contract and which consumers enforce it.

Parameters

Common parameters

NameDescriptionTypeValue
replicasNumber of Valkey replicas.int2
resourcesExplicit CPU and memory configuration for each Valkey replica. When omitted, the preset defined in resourcesPreset is applied.object{}
resources.cpuCPU available to each replica.quantity""
resources.memoryMemory (RAM) available to each replica.quantity""
resourcesPresetDefault sizing preset used when resources is omitted.stringt1.nano
sizePersistent Volume Claim size available for application data.quantity1Gi
storageClassStorageClass used to store the data.string""
externalEnable external access from outside the cluster.boolfalse
versionValkey major version to deploystringv8

Application-specific parameters

NameDescriptionTypeValue
authEnabledEnable password generation.booltrue

Parameter examples and reference

resources and resourcesPreset

resources sets explicit CPU and memory configurations for each replica. Every resource it leaves unset is taken from the preset defined in resourcesPreset.

resources:
  cpu: 4000m
  memory: 4Gi

resourcesPreset sets named CPU and memory configurations for each replica. This setting is ignored if the corresponding resources value is set.

Presets follow a cloud-style <series>.<size> naming convention. Five series cover the full CPU-to-memory ratio range (t1 1:0.5, c1 1:1, s1 1:2, u1 1:4, m1 1:8) and each series ships eight sizes (nano through 4xlarge). The legacy flat names (nano, micro, small, medium, large, xlarge, 2xlarge) remain accepted as deprecated aliases and keep their original sizes, which do not follow one series: nano through small equal the t1 sizes of the same name, while medium equals c1.small rather than c1.medium.

See docs/operations/resource-presets.md for the full size matrix and the legacy-to-instance-type mapping.