memoization.md

Step Level Memoization

v2.10 and after

Introduction

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

Cache Method

Currently, caching can only be performed with ConfigMaps. This allows you to easily manipulate cache entries manually through kubectl and the Kubernetes API without having to go through Argo.

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 ConfigMap cache.

apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
 generateName: memoized-workflow-
spec:
 entrypoint: whalesay
 templates:
    - name: whalesay
      memoize:
        key: "{{inputs.parameters.message}}" 
        cache:
          configMap:
            name: whalesay-cache

...