Scraper is a web service that grabs the HTTP response status codes for a given URL.

Main features

• Custom listen ports for scraper service and metrics service
• Limit of concurrent scrapes
• Custom timeout
• Settings via command line arguments or environment variables (SCRAPER_ prefix)

How it works?

1. A client makes a HTTP POST request to the Scraper Service, to the Scraper listening port (default: 8080). The request is sent in the POST body:

   {"url": "http://phaidra.ai"}
   

2. The Scraper tries to fullfil the request by creating an HTTP GET request to {target}

3. If the {target} url exists, Scraper receives the Status Code response from {target}

4. The following prometheus metrics are updated:

   • http_requests_total{code}
     • How many HTTP requests received, partitioned response code.
   • http_get{code}
     • How many HTTP GET scraped, partitioned by url and response code.
   • workerWait
     • Histogram. Time waiting for an available worker. In milliseconds.

5. Client receives the response Status Code:

   • 200 OK: Target exists and replied with a Status Code
   • 408 RequestTimeout: No worker available in the timeout period
   • 501 NotImplemented: Scaper received a HTTP method different than POST
   • 400 BadRequest: Request POST body is malformed
   • 500 InternalServerError: Unexpected internal error

Metrics are a prometheus (prometheus-client) service accessible on port 9095 (by default) under path /metrics.

Build and run Scraper

Requirements:

• Golang go1.16

Compile and install:

$ go build .

Run Unit Tests:

$ go test .

Start Scraper Service:

$ ./scraper_service

Scraper Service settings:

$ ./scraper_service --help

Usage: scraper_service [FLAG]...

Flags:
    --listen      Service listen address.                                 (type: string; env: SCRAPER_Listen; default: :8080)
    --workers     Number of serving workers.                              (type: uint8; env: SCRAPER_Workers; default: 2)
    --timeout     Maximum time (in milliseconds) to wait for a worker.    (type: uint64; env: SCRAPER_Timeout; default: 1000)
    --metrics     Metrics listen address.                                 (type: string; env: SCRAPER_MetricsListen; default: :9095)
    -h, --help    show help                                               (type: bool)

Build docker images

This builds the docker image scraper_service/scraper:0.1.0 using a multi-stage build

docker build -t scraper_service/scraper:0.1.0 .

Launching a container

docker run -p 8080:8080 -p 9095:9095 scraper_service/scraper:0.1.0

Simple request script

./tools/request.sh <address-to-scrape> <scraper-service-address> <count>

Examples:

./tools/request.sh https://google.com localhost:8080 1

./tools/request.sh https://phaidra.ai localhost:8080 1

./tools/request.sh https://phaidra.ai/trackrecord localhost:8080 1

PromQL

Number of requests received per 10s:

sum(rate(http_requests_total[10s]))

Number of requests received per 10s, partitioned by Status Code:

sum by(code) (delta(http_requests_total[10s]))

Number of requests received per 1m, where Status Code was not 200 OK:

delta(http_requests_total{code!="200"}[1m])

Number of requests received that resulted in timeout, per 1m:

delta(http_requests_total{code!="408"}[1m])

Number of requests that waited for a worker, per bucket of wait time, per 1m:

sum by (le) (rate(wait_available_worker_bucket[1m]))

Average wait time for a worker to process the request, per 1m:

sum(wait_available_worker_sum/wait_available_worker_count)

Kubernetes deployment

Image should be available in your cluster.

Kind example:

kind load docker-image scraper_service/scraper:0.1.0

Deploying the Scraper Service:

kubectl apply -f deployment/scraper.yaml

Deploying the Prometheus with service discovery:

kubectl apply -f deployment/prometheus-rbac.yaml
kubectl apply -f deployment/prometheus.yaml