mirror of
https://github.com/hanzo-ml/kserve.git
synced 2026-10-30 20:53:49 +00:00
Dan SunandGitHub
5437fe397e
* Update sklearn example storage uri Signed-off-by: Dan Sun <[email protected]> * Fix installation script Signed-off-by: Dan Sun <[email protected]> * Fix metrics port and use non default service account Signed-off-by: Dan Sun <[email protected]> * Use non-root runtime base image Signed-off-by: Dan Sun <[email protected]>
Local Test of Kfserving Logger
In one terminal start an echo http server on port 8000
docker run -it -p 8000:80 --rm -t mendhak/http-https-echo
Start an SKLearn Iris model on port 8080. You will need to have pip installed the sklearnserver. See /python/sklearnserver.
gsutil cp -r gs://kfserving-examples/models/sklearn/1.0/model .
LOCAL_DIR=$(pwd)/iris
python -m sklearnserver --model_dir $LOCAL_DIR --model_name sklearn-iris --http_port 8080
Start the Kfserving logger from Kfserving root folder:
bin/logger --log-url http://0.0.0.0:8000 --component-port 8080 --log-mode all --inference-service=iris --namespace=default --endpoint=default
Send a request:
curl -v -d @./input.json http://0.0.0.0:8081/v1/models/sklearn-iris:predict
You should see output like:
* Trying 0.0.0.0...
* Connected to 0.0.0.0 (127.0.0.1) port 8081 (#0)
> POST /v1/models/sklearn-iris:predict HTTP/1.1
> Host: 0.0.0.0:8081
> User-Agent: curl/7.47.0
> Accept: */*
> Content-Length: 76
> Content-Type: application/x-www-form-urlencoded
>
* upload completely sent off: 76 out of 76 bytes
< HTTP/1.1 200 OK
< Content-Type: text/html; charset=UTF-8
< Date: Fri, 20 Dec 2019 18:23:49 GMT
< Content-Length: 23
<
* Connection #0 to host 0.0.0.0 left intact
{"predictions": [1, 1]}
This shows the prediction has worked. In the output of the http-https-echo server you should see the request and response payloads echoed.
{ path: '/',
headers:
{ host: '0.0.0.0:8000',
'user-agent': 'Go-http-client/1.1',
'content-length': '23',
'ce-id': '3ba84918-209f-4d8d-ae38-b041e5e4a328',
'ce-inferenceservice': '"iris"',
'ce-namespace': '"default"',
'ce-endpoint': '"default"',
'ce-source': 'http://localhost:8081/',
'ce-specversion': '0.2',
'ce-time': '2020-02-27T09:52:15.820509751Z',
'ce-type': 'org.kubeflow.serving.inference.response',
'content-type': 'application/json',
'accept-encoding': 'gzip' },
method: 'POST',
body: '{"predictions": [1, 1]}',
cookies: undefined,
fresh: false,
hostname: '0.0.0.0',
ip: '::ffff:172.17.0.1',
ips: [],
protocol: 'http',
query: {},
subdomains: [],
xhr: false,
os: { hostname: '00ed2b10cbea' } }
::ffff:172.17.0.1 - - [27/Feb/2020:09:52:15 +0000] "POST / HTTP/1.1" 200 798 "-" "Go-http-client/1.1"
-----------------
{ path: '/',
headers:
{ host: '0.0.0.0:8000',
'user-agent': 'Go-http-client/1.1',
'content-length': '76',
'ce-id': '3ba84918-209f-4d8d-ae38-b041e5e4a328',
'ce-inferenceservice': '"iris"',
'ce-namespace': '"default"',
'ce-endpoint': '"default"',
'ce-source': 'http://localhost:8081/',
'ce-specversion': '0.2',
'ce-time': '2020-02-27T09:52:15.816441245Z',
'ce-type': 'org.kubeflow.serving.inference.request',
'content-type': 'application/json',
'accept-encoding': 'gzip' },
method: 'POST',
body: '{ "instances": [ [6.8, 2.8, 4.8, 1.4], [6.0, 3.4, 4.5, 1.6] ]}',
cookies: undefined,
fresh: false,
hostname: '0.0.0.0',
ip: '::ffff:172.17.0.1',
ips: [],
protocol: 'http',
query: {},
subdomains: [],
xhr: false,
os: { hostname: '00ed2b10cbea' } }
::ffff:172.17.0.1 - - [27/Feb/2020:09:52:15 +0000] "POST / HTTP/1.1" 200 850 "-" "Go-http-client/1.1"