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https://github.com/GSA/notifications-admin.git
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24dbe7b7b1
Most of the time spent by the admin app to generate a page is spent waiting for the API. This is slow for three reasons: 1. Talking to the API means going out to the internet, then through nginx, the Flask app, SQLAlchemy, down to the database, and then serialising the result to JSON and making it into a HTTP response 2. Each call to the API is synchronous, therefore if a page needs 3 API calls to render then the second API call won’t be made until the first has finished, and the third won’t start until the second has finished 3. Every request for a service page in the admin app makes a minimum of two requests to the API (`GET /service/…` and `GET /user/…`) Hitting the database will always be the slowest part of an app like Notify. But this slowness is exacerbated by 2. and 3. Conversely every speedup made to 1. is multiplied by 2. and 3. So this pull request aims to make 1. a _lot_ faster by taking nginx, Flask, SQLAlchemy and the database out of the equation. It replaces them with Redis, which as an in-memory key/value store is a lot faster than Postgres. There is still the overhead of going across the network to talk to Redis, but the net improvement is vast. This commit only caches the `GET /service` response, but is written in such a way that we can easily expand to caching other responses down the line. The tradeoff here is that our code is more complex, and we risk introducing edge cases where a cache becomes stale. The mitigations against this are: - invalidating all caches after 24h so a stale cache doesn’t remain around indefinitely - being careful when we add new stuff to the service response --- Some indicative numbers, based on: - `GET http://localhost:6012/services/<service_id>/template/<template_id>` - with the admin app running locally - talking to Redis running locally - also talking to the API running locally, itself talking to a local Postgres instance - times measured with Chrome web inspector, average of 10 requests ╲ | No cache | Cache service | Cache service and user | Cache service, user and template -- | -- | -- | -- | -- **Request time** | 136ms | 97ms | 73ms | 37ms **Improvement** | 0% | 41% | 88% | 265% --- Estimates of how much storage this requires: - Services: 1,942 on production × 2kb = 4Mb - Users: 4,534 on production × 2kb = 9Mb - Templates: 7,079 on production × 4kb = 28Mb
53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
import json
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from datetime import timedelta
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from functools import wraps
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TTL = int(timedelta(hours=24).total_seconds())
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def _make_key(prefix, args, key_from_args):
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if key_from_args is None:
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key_from_args = [0]
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return '-'.join(
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[prefix] + [args[index] for index in key_from_args]
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)
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def set(prefix, key_from_args=None):
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def _set(client_method):
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@wraps(client_method)
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def new_client_method(client_instance, *args, **kwargs):
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redis_key = _make_key(prefix, args, key_from_args)
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cached = client_instance.redis_client.get(redis_key)
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if cached:
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return json.loads(cached.decode('utf-8'))
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api_response = client_method(client_instance, *args, **kwargs)
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client_instance.redis_client.set(
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redis_key,
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json.dumps(api_response),
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ex=TTL,
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)
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return api_response
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return new_client_method
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return _set
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def delete(prefix, key_from_args=None):
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def _delete(client_method):
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@wraps(client_method)
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def new_client_method(client_instance, *args, **kwargs):
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redis_key = _make_key(prefix, args, key_from_args)
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client_instance.redis_client.delete(redis_key)
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return client_method(client_instance, *args, **kwargs)
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return new_client_method
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return _delete
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