## Problem
Currently, even if `LAMBDA_REMOTE_DOCKER=1`, we unzip the zip files in the directory they are in, which is usually /var/lib/localstack, which usually has a bind mount to the host.
On docker desktop, due to the use of grpc-FUSE (on macos), this can be very slow, about 200 times slower than on volumes / directly on the host. With experimental virtio filesystem enabled (also on macos), this can be reduced to about 30 times as slow, but still problematic.
This means a lambda may take a lot of time processing, for each additional layer some more. This especially affects nodejs lambdas with huge node_modules folders.

## Probable solution
At least if `LAMBDA_REMOTE_DOCKER=1`, we should leave the initial zip files on the bind mount (for persistence etc), but the working directories after unzipping should be located on non-bind mounts, to speed up the IO for unzipping.
"State": lambda_function.state,
        "LastUpdateStatus": "Successful",
        "PackageType": lambda_function.package_type,
        "ImageConfig": getattr(lambda_function, "image_config", None),
        "Architectures": lambda_function.architectures,
    }
    if lambda_function.dead_letter_config:
        result["DeadLetterConfig"] = lambda_function.dead_letter_config
    if lambda_function.envvars:
        result["Environment"] = {"Variables": lambda_function.envvars}
    arn_parts = result["FunctionArn"].split(":")
    if (always_add_version or version != VERSION_LATEST) and len(arn_parts) <= 7:
        result["FunctionArn"] += ":%s" % version
    return result
def forward_to_fallback_url(func_arn, data):
    """If LAMBDA_FALLBACK_URL is configured, forward the invocation of this non-existing
    Lambda to the configured URL."""
    if not config.LAMBDA_FALLBACK_URL:
        return
    lambda_name = aws_stack.lambda_function_name(func_arn)
    if config.LAMBDA_FALLBACK_URL.startswith("dynamodb://"):
        table_name = urlparse(config.LAMBDA_FALLBACK_URL.replace("dynamodb://", "http://")).netloc
        dynamodb = aws_stack.connect_to_service("dynamodb")
        item = {
            "id": {"S": short_uid()},
            "timestamp": {"N": str(now_utc())},
            "payload": {"S": data},
            "function_name": {"S": lambda_name},
        }
        aws_stack.create_dynamodb_table(table_name, partition_key="id")