slow_cooker

A load tester for tenderizing your servers.

Most load testers work by sending as much traffic as possible to a backend. We wanted a different approach, we wanted to be able to test a service with a predictable load and concurrency level for a long period of time. Instead of getting a report at the end, we wanted periodic reports of qps and latency.

Running it

go build; ./slow_cooker <url>

or:

go run main.go <url>

Flags

-qps <int>

Queries per second to send to a backend.

-concurrency <int>

How many goroutines to run, each at the specified qps level. Measure total qps as qps * concurrency.

-host <string>

Set a Host: header.

-interval 10s

How often to report to stdout.

-noreuse

Do not reuse connections. (Connection reuse is the default.)

-compress

Ask for compressed responses.

-noLatencySummary

Don't print the latency histogram report at the end.

-reportLatenciesCSV <filename>

Writes a CSV file of latencies. Format is: milliseconds to number of requests that fall into that bucket.

-totalRequests <int>

Exit after sending this many requests.

Using multiple Host headers

If you want to send multiple Host headers to a backend, pass a comma separated list to the host flag. Each request will be selected randomly from the list.

For more complex distributions, you can run multiple slow_cooker processes:

$ slow_cooker -host web_a,web_b -qps 200 http://localhost:4140

$ slow_cooker -host web_b -qps 100 http://localhost:4140

This example will send 300 qps total to http://localhost:4140/ with 100 qps sent with Host: web_a and 200 qps sent with Host: web_b

TLS use

Pass in an https url and it'll use TLS automatically.

Warning We do not verify the certificate, we use InsecureSkipVerify: true

Example usage

$ ./slow_cooker -qps 100 -concurrency 10 http://slow_server

2016-05-16T20:45:05Z   7102/0/0 10000 71% 10s 0 [ 12  26  37  91 ] 91
2016-05-16T20:45:16Z   7120/0/0 10000 71% 10s 1 [ 11  27  37  53 ] 53
2016-05-16T20:45:26Z   7158/0/0 10000 71% 10s 0 [ 11  27  37  74 ] 74
2016-05-16T20:45:36Z   7169/0/0 10000 71% 10s 1 [ 11  27  36  52 ] 52
2016-05-16T20:45:46Z   7273/0/0 10000 72% 10s 0 [ 11  27  36  58 ] 58
2016-05-16T20:45:56Z   7087/0/0 10000 70% 10s 1 [ 11  28  37  61 ] 61
2016-05-16T20:46:07Z   7231/0/0 10000 72% 10s 0 [ 11  26  35  71 ] 71
2016-05-16T20:46:17Z   7257/0/0 10000 72% 10s 0 [ 11  27  36  57 ] 57
2016-05-16T20:46:27Z   7205/0/0 10000 72% 10s 0 [ 11  27  36  64 ] 64
2016-05-16T20:46:37Z   7256/0/0 10000 72% 10s 0 [ 11  27  36  62 ] 62
2016-05-16T20:46:47Z   7164/0/0 10000 71% 10s 0 [ 11  27  38  74 ] 74
2016-05-16T20:46:58Z   7232/0/0 10000 72% 10s 0 [ 11  26  35  63 ] 63

In this example, we see that the server is too slow to keep up with our requested load. that slowness is noted via the throughput percentage.

Docker usage

Run

docker run -it buoyantio/slow_cooker -qps 100 -concurrency 10 http://$(docker-machine ip default):4140

Build your own

docker build -t buoyantio/slow_cooker -f Dockerfile .

Log format

We use vertical alignment in the output to help find anomalies and spot slowdowns. If you're running multi-hour tests, bumping up the reporting interval to 60 seconds (60s or 1m) is recommended.

$timestamp $good/$bad/$failed $trafficGoal $percentGood $interval $min [$p50 $p95 $p99 $p999] $max

bad means a status code in the 500 range. failed means a connection failure.

Tips and tricks

keep a logfile

Use tee to keep a logfile of slow_cooker results and cut to find bad or failed requests.

./slow_cooker_linux_amd64 -qps 5 -concurrency 20 -interval 10s -reuse http://localhost:4140 | tee slow_cooker.log

use cut to look at specific fields from your tee'd logfile

cat slow_cook.log |cut -d ' ' -f 3 | cut -d '/' -f 2 |sort -rn |uniq -c

will show all bad (status code >= 500) requests.

cat slow_cook.log |cut -d ' ' -f 3 | cut -d '/' -f 3 |sort -rn |uniq -c

will show all failed (connection refused, dropped, etc) requests.

dig into the full latency report

With the -reportLatenciesCSV flag, you can thoroughly inspect your service's latency instead of relying on pre-computed statistical summaries. We chose CSV to allow for easy integration with statistical environments like R and standard spreadsheet tools like Excel.

use the latency CSV output to see system performance changes

Use -totalRequests and -reportLatenciesCSV to see how your system latency grows as a function of traffic levels.

use -concurrency to improve throughput

If you're not hitting the throughput numbers you expect, try increasing -concurrency so your requests are issued over more goroutines. Each goroutine issues requests serially, waiting for a response before issuing the next request.

If you have scripts that process slow_cooker logs, feel free to add them to this project!