lambda-cache 0.7.2

Python utility for simple caching in AWS Lambda functions

lambda-cache

Simple Caching for AWS Lambda

Basics

lambda_cache prioritizes simplicity over performance and flexibility. The goal is to provide the simplest way for developers to cache api calls in their Lambda functions.

Currently only SSM Parameters and Secrets from Secrets Manager are supported. S3 and generic function support is coming soon.

Cache single parameter

To cache a parameter from ssm, decorate your handler function:

from lambda_cache import ssm

@ssm.cache(parameter='/production/app/var')
def handler(event, context):
    var = context.get('var')
    response = do_something(var)
    return response

All invocations of this function over in the next minute will reference the parameter from the function's internal cache, without making a network call to ssm. After one minute has lapsed, the the next invocation will invoke get_parameter to refresh the cache.

Change cache settings

The default ttl_seconds settings is 60 seconds (1 minute), it defines how long a parameter should be kept in cache before it is refreshed from ssm. To configure longer or shorter times, modify this argument in the decorator:

from lambda_cache import ssm

@ssm.cache(parameter='/production/app/var', ttl_seconds=300)
def handler(event, context):
    var = context.get('var')
    response = do_something(var)
    return response

Note: The caching logic runs only at invocation of the function. A 15 minute lambda function will not refresh the parameter, unless explicitly refreshed using get_entry.The package is primary interested in caching 'across' invocations rather than 'within' one invocation

Change cache entry settings

The name of the parameter is shortened to the string after the last slash('/') character of its name. This means /production/app/var and test/app/var resolve to just var. To over-ride this default, use entry_name:

from lambda_cache import ssm

@ssm.cache(parameter='/production/app/var', entry_name='new_var')
def handler(event, context):
    var = context.get('new_var')
    response = do_something(var)
    return response

Cache multiple parameters

To cache multiple entries at once, pass a list of parameters to the parameter argument, and grab the parameters from context['parameters'].

from lambda_cache import ssm

@ssm.cache(parameter=['/app/var1', '/app/var2'], entry_name='parameters')
def handler(event, context):
    var1 = context.get('parameters').get('var1')
    var2 = context.get('parameters').get('var2')
    response = do_something(var)
    return response

Note: we use the get_parameters API call for boto3, which makes a single network call for multiple parameters. You can group all parameters types in a single call, with String and SecureString parameters returned as strings, while StringList parameters are returned a python lists.

Decorator stacking

If you wish to cache multiple parameters with different expiry times, stack the decorators. In this example, var1 will be refreshed every 30 seconds, var2 will be refreshed after 60.

@ssm.cache(parameter='/production/app/var1', ttl_seconds=30)
@ssm.cache(parameter='/production/app/var2', ttl_seconds=60)
def handler(event, context):
    var1 = context.get('var1')
    var2 = context.get('var2')
    response = do_something(var)
    return response

Note: Decorator stacking performs one API call per decorator, which might result is slower performance.

Cache invalidation

If you require a fresh value at some point of the code, you can force a refresh using the get_entry function, and setting the ttl_seconds argument to 0.

from lambda_cache import ssm

@ssm.cache(parameter='/prod/var')
def handler(event, context):

    if event.get('refresh'):
        # refresh parameter
        var = ssm.get_entry(parameter='/prod/var', ttl_seconds=0)
    else:
        var = context.get('var')
    
    response = do_something(var)
    return response

Return Values

Caching supports String, SecureString and StringList parameters with no change required (ensure you have kms:Decrypt permission for SecureString). For simplicity, the package takes away the heavy lifting of dealing with these different parameter types. StringList parameters are automatically converted into list (delimited by '/'), while String and SecureString both return the single string value of the parameter.

Secrets Manager

Secret support is similar, but uses the secrets_manager decorator.

from lambda_cache import secrets_manager

@secrets_manager.cache(name='/prod/db/conn_string')
def handler(event, context):
    conn_string = context.get('conn_string')
    return context

Secrets Managers supports all the previously mentioned features including ttl_seconds, entry_name and cache invalidation.

Cache Invalidation

To invalidate a secret, use the get_entry method, setting ttl_seconds=0.

from lambda_cache import secrets_manager

@secrets_manager.cache(name='/prod/db/conn_string')
def handler(event, context):

    if event.get('refresh'):
        var = secrets_manager.get_entry(name='/prod/db/conn_string', ttl_seconds=0)
    else:
        var = context.get('conn_string')
    response = do_something(var)
    return response

Return Values

Secrets Manager supports both string and binary secrets. For simplicity we will cache the secret in the format it is stored. It is up to the calling application to process the return as Binary or Strings.

Credit

Project inspired by:

• SSM-Cache
• middy