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Step Level Memoization

v2.10 and after


Workflows often have outputs that are expensive to compute. Memoization reduces cost and workflow execution time by recording the result of previously run steps: it stores the outputs of a template into a specified cache with a variable key.

Prior to version 3.5 memoization only works for steps which have outputs, if you attempt to use it on steps which do not it should not work (there are some cases where it does, but they shouldn't). It was designed for 'pure' steps, where the purpose of running the step is to calculate some outputs based upon the step's inputs, and only the inputs. Pure steps should not interact with the outside world, but workflows won't enforce this on you.

If you are using workflows prior to version 3.5 you should look at the work avoidance technique instead of memoization if your steps don't have outputs.

In version 3.5 or later all steps can be memoized, whether or not they have outputs.

Cache Method

Currently, the cached data is stored in config-maps. This allows you to easily manipulate cache entries manually through kubectl and the Kubernetes API without having to go through Argo. All cache config-maps must have the label Cache to be used as a cache. This prevents accidental access to other important config-maps in the system

Using Memoization

Memoization is set at the template level. You must specify a key, which can be static strings but more often depend on inputs. You must also specify a name for the config-map cache. Optionally you can set a maxAge in seconds or hours (e.g. 180s, 24h) to define how long should it be considered valid. If an entry is older than the maxAge, it will be ignored.

kind: Workflow
   generateName: memoized-workflow-
   entrypoint: whalesay
      - name: whalesay
           key: "{{inputs.parameters.message}}"
           maxAge: "10s"
                 name: whalesay-cache

Find a simple example for memoization here.


In order to use memoization it is necessary to add the verbs create and update to the configmaps resource for the appropriate (cluster) roles. In the case of a cluster install the argo-cluster-role cluster role should be updated, whilst for a namespace install the argo-role role should be updated.


  1. If you see errors like error creating cache entry: ConfigMap \"reuse-task\" is invalid: []: Too long: must have at most 1048576 characters, this is due to the 1MB limit placed on the size of ConfigMap. Here are a couple of ways that might help resolve this:
    • Delete the existing ConfigMap cache or switch to use a different cache.
    • Reduce the size of the output parameters for the nodes that are being memoized.
    • Split your cache into different memoization keys and cache names so that each cache entry is small.
  2. My step isn't getting memoized, why not? If you are running workflows <3.5 ensure that you have specified at least one output on the step.