wordpressdockervarnish

Wordpress Perfect Varnish VCL Random 503 Error


I am using wordpress. I deploy Varnish Using Docker. This Is My default.vcl. What's Wrong With This Config?? Sometimes, Get Random 503 Error. I Exclude Wordpress Search Page Using RegEx. Also Get Random 503 Error On wordpress Search Page Too!!

varnishlog

https://www.dropbox.com/s/ruczg2i3h/log.txt

I am Using NGINX Backened.. Help Appreciated Thanks


Solution

  • Your log output contains the following lines:

    -   Error          out of workspace (bo)
    -   LostHeader     Date: 
    -   BerespHeader   Server: Varnish
    -   VCL_call       BACKEND_ERROR
    -   LostHeader     Content-Type:
    -   LostHeader     Retry-After:
    

    Apparently you ran out of workspace memory because the size of the response.

    The following parameters in your Docker config might cause that:

    -p http_resp_hdr_len=65536 \
    -p http_resp_size=98304 \
    

    While increasing the size of individual headers and the total response size, the total memory consumption exceeds the workspace_backend value, which defaults to 64k.

    Here's the documentation for http_resp_size:

    $ varnishadm param.show http_resp_size
    http_resp_size
            Value is: 32k [bytes] (default)
            Minimum is: 0.25k
    
            Maximum number of bytes of HTTP backend response we will deal
            with.  This is a limit on all bytes up to the double blank line
            which ends the HTTP response.
            The memory for the response is allocated from the backend
            workspace (param: workspace_backend) and this parameter limits
            how much of that the response is allowed to take up.
    

    As you can see, it affects workspace_backend. So here's the documentation for that:

    $ varnishadm param.show workspace_backend
    workspace_backend
            Value is: 64k [bytes] (default)
            Minimum is: 1k
    
            Bytes of HTTP protocol workspace for backend HTTP req/resp.  If
            larger than 4k, use a multiple of 4k for VM efficiency.
    
            NB: This parameter may take quite some time to take (full)
            effect.
    

    The solution is to increase the workspace_backend through a -p runtime parameter.