cdp-cache

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• Caddy Http Cache

  This is a http cache plugin for caddy 2. In fact, I am not so familiar with the part of cdn cache's mechanism so I reference the code from https://github.com/nicolasazrak/caddy-cache. which is the caddy v1's cache module. Then, I migrate the codebase to be consist with the caddy2 architecture and develop more features based on that.

  Currently, this doesn't support =distributed cache= yet. It's still in plan.

• Features

** Multi storage backends support Now the following backends are supported.

• file
• inmemory
• redis

In the latter part, I will show the example Caddyfile to serve different type of proxy cache server.

** Conditional rule to cache the upstream response

• uri path matcher
• http header matcher

** Set default cache's max age A default age for matched responses that do not have an explicit expiration. ** Purge cache There are exposed endpoints to purge cache. I implement it with admin apis endpoints. The following will show you how to purge cache

*** first you can list the current caches

Given that you specify the port 7777 to serve caddy admin, you can get the list of cache by the api below.

#+begin_src restclient
  GET http://example.com:7777/caches
#+end_src

*** purge the cache with http DELETE request It supports the regular expression.

#+begin_src restclient
  DELETE http://example.com:7777/caches/purge
  Content-Type: application/json

  {
    "method": "GET",
    "host": "localhost",
    "uri": ".*\\.txt"
  }
#+end_src

** Support cluster with consul

NOTE: still under development and only the =memory= backend supports.

I've provided a simple example to mimic a cluster environment.

#+begin_src sh PROJECT_PATH=/app docker-compose --project-directory=./ -f example/distributed_cache/docker-compose.yaml up #+end_src

• How to build

  In development, go to the cmd folder and type the following commands.

  #+begin_src sh go build -ldflags="-w -s" -o caddy #+end_src

  To build linux binary by this #+begin_src GOOS=linux GOARCH=amd64 go build -ldflags="-w -s" -o caddy #+end_src

  Or you can use the [[https://github.com/caddyserver/xcaddy][xcaddy]] to build the executable file. Ensure you've install it by =go get -u github.com/caddyserver/xcaddy/cmd/xcaddy= #+begin_src sh xcaddy build v2.4.1 --with github.com/sillygod/cdp-cache #+end_src

  Xcaddy also provide a way to develop plugin locally. #+begin_src sh xcaddy run --config cmd/Caddyfile #+end_src

  To remove unused dependencies #+begin_src sh go mod tidy #+end_src

• How to run

  You can directly run with the binary. #+begin_src sh caddy run --config [caddy file] --adapter caddyfile #+end_src

  Or if you are preferred to use the docker #+begin_src sh docker run -it -p80:80 -p443:443 -v [the path of caddyfile]:/app/Caddyfile docker.pkg.github.com/sillygod/cdp-cache/caddy:latest #+end_src

• Configuration

  The following will list current support configs in the caddyfile.

*** status_header The header to set cache status. default value: =X-Cache-Status=

*** match_path Only the request's path match the condition will be cached. Ex. =/= means all request need to be cached because all request's path must start with =/=

*** match_methods By default, only =GET= and =POST= methods are cached. If you would like to cache other methods as well you can configure here which methods should be cached, e.g.: =GET HEAD POST=.

To be able to distinguish different POST requests, it is advisable to include the body hash in the cache key, e.g.: ={http.request.method} {http.request.host}{http.request.uri.path}?{http.request.uri.query} {http.request.contentlength} {http.request.bodyhash}=

*** default_max_age The cache's expiration time.

*** stale_max_age The duration that a cache entry is kept in the cache, even though it has already expired. The default duration is =0=.

If this duration is > 0 and the upstream server answers with an HTTP status code >= 500 (server error) this plugin checks whether there is still an expired (stale) entry from a previous, successful call in the cache. In that case, this stale entry is used to answer instead of the 5xx response.

*** match_header only the req's header match the condtions ex.

#+begin_quote
match_header Content-Type image/jpg image/png "text/plain; charset=utf-8"
#+end_quote

*** path The position where to save the file. Only applied when the =cache_type= is =file=.

*** cache_key The key of cache entry. The default value is ={http.request.method} {http.request.host}{http.request.uri.path}?{http.request.uri.query}=

*** cache_bucket_num The bucket number of the mod of cache_key's checksum. The default value is 256.

*** cache_type Indicate to use which kind of cache's storage backend. Currently, there are two choices. One is =file= and the other is =in_memory=

*** cache_max_memory_size

The max memory usage for in_memory backend.

*** distributed

Working in process. Currently, only support =consul= to establish the cluster of cache server node.

To see a example config, please refer [[file:example/distributed_cache/Caddyfile::health_check ":7777/health"][this]]

**** service_name specify your service to be registered in the consul agent.

**** addr the address of the consul agent.

**** health_check indicate the health_check endpoint which consul agent will use this endpoint to check the cache server is healthy

** Example configs You can go to the directory [[file:example/][example]]. It shows you each type of cache's configuration.

• Benchmarks

  Now, I just simply compares the performance between in-memory and disk.

** Env Caddy run with the config file under directory =benchmark= and tests were run on the mac book pro (1.4 GHz Intel Core i5, 16 GB 2133 MHz LPDDR3)

** Test Result

The following benchmark is analysized by =wrk -c 50 -d 30s --latency -t 4 http://localhost:9991/pg31674.txt= without log open. Before running this, ensure you provision the tests data by =bash benchmark/provision.sh=

| | req/s | latency (50% 90% 99%) | | proxy + file cache | 13853 | 3.29ms / 4.09ms / 5.26ms | | proxy + in memory cache | 20622 | 2.20ms / 3.03ms / 4.68ms |

• Todo list

  • [ ] distributed cache (in progress)
  • [ ] more optimization..