lambda-cache 0.7.0

Python utility for simple caching in AWS Lambda functions

simple_lambda_cache

Simple Caching for AWS Lambda

Basics

simple_lambda_cache prioritizes simplicity over performance and flexibility. The goal of the package 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.

Cache single parameter

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

from simple_lambda_cache import ssm_cache

@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, rather than making a network call to ssm. After one minute, 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 like so:

from simple_lambda_cache import ssm_cache

@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, regardless of how long the function runs. A 15 minute lambda function will not refresh the parameter, unless explicitly refreshed using get_cache_ssm. The library is primary interested in caching 'across' invocation rather than 'within' an invocation

Change cache entry settings

The name of the parameter is simply 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 simple_lambda_cache import ssm_cache

@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 simple_lambda_cache import ssm_cache

@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

Under the hood, we us the get_parameters API call for boto3, which translate to a single network call for multiple parameters. You can group all parameters types in a single call, with StringList parameters 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_ssm_cache function, and setting the ttl_seconds argument to 0.

from simple_lambda_cache import ssm_cache, get_ssm_cache

@ssm_cache(parameter='/prod/var')
def handler(event, context):

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

To disable cache, set ttl_seconds=0.

To only get parameter once in the lifetime of the function, set ttl_seconds to some arbitary large number ~36000 (10 hours).

Return Values

Caching supports String, SecureString and StringList parameters with no change required (ensure you have kms:Decrypt permission for SecureString). For simplicity, 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 secret_cache decorator.

from simple_lambda_cache import secret_cache

@secret_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_secret_cache, setting the ttl_seconds=0.

from simple_lambda_cache import secret_cache, get_secret_cache

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

    if event.get('refresh'):
        var = get_secret_cache(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