pastebin

Simple, fast, standalone pastebin service.

Why?

Whenever you need to share a code snippet, diff, logs, or a secret with another human being, the Pastebin service is invaluable. However, using public services such as pastebin.com, privnote.com, etc. should be avoided when you're sharing data that should be available only for a selected audience (i.e., your company, private network). Instead of trusting external providers, you could host your own Pastebin service and take ownership of all your data!

There are numerous Pastebin implementations out there, why would you implement another one?

While the other implementations are great, I couldn't find one that would satisfy my requirements:

• no dependencies - one binary is all I want, no python libs, ruby runtime magic, no javascript or external databases to setup
• storage - fast, lightweight, self-hosted key-value storage able to hold a lot of data.
• speed - it must be fast. Once deployed in a mid-sized company you can expect high(er) traffic with low latency expectations from users
• reliability - no one wants to fix things that should just work (and are that simple!)
• cheap - low-cost service that would not steal too much CPU time, thus adding up to your bill
• CLI + GUI - it must be easy to interface from both ends (but still, no deps!)
• other features:
  • on-demand encryption
  • syntax highlighting
  • destroy after reading
  • destroy after expiration date

This Pastebin implementation satisfies all of the above requirements!

Implementation

This is a rust version of Pastebin service with rocksdb database as storage. In addition to previously mentioned features it's worth to mention:

• all-in-one binary - all the data, including css/javascript files are compiled into the binary. This way you don't need to worry about external dependencies, it's all within. (see: std::include_bytes)
• REST endpoint - you can add/delete pastes via standard HTTP client (ie. curl)
• RocksDB compaction filter - the expired pastes will be automatically removed by custom compaction filter
• flatbuffers - data is serialized with flatbuffers (access to serialized data without parsing/unpacking)
• GUI - the UI is a plain HTML with Bootstrap JS, jQuery and prism.js
• Encryption - password-protected pastes are AES encrypted/decprypted in the browser via CryptoJS

Plugins

The default configuration enables only one plugin, this is syntax highlighting through prism.js. This should be enough for p90 of the users but if you need extra features you might want to use the plugin system (src/plugins).

To enable additional plugins, pass:

--plugins prism <custom_plugin_name>

Currently supported:

• prism.js
• mermaid.js

Usage

Pastebin builds only with rust-nightly version and requires llvm compiler (rocksdb deps). To skip the build process, you can use the docker image.

Cargo

cargo build --release
cargo run

x86 image:

docker pull mkaczanowski/pastebin:latest
docker run --init --network host mkaczanowski/pastebin --address localhost --port 8000

ARM images:

docker pull mkaczanowski/pastebin:armv7
docker pull mkaczanowski/pastebin:armv8

Compose setup:

URI="http://localhost" docker-compose up
curl -L "http://localhost"

alias pastebin="curl -w '\n' -q -L --data-binary @- -o - http://localhost:8000/"


echo "hello World" | pastebin
http://localhost:8000/T9kGrI5aNkI4Z-PelmQ5U

The Pastebin service serves /static files from memory. To lower down the load on the service you might want to consider setting up nginx with caching and compression enabled, as shown here:

map $sent_http_content_type $expires {
    default                    off;
    text/css                   30d;
    application/javascript     30d;
    image/x-icon               30d;
}


server {
    listen       80; 
    server_name  paste.domain.com;

gzip on;
gzip_types text/plain application/xml text/css application/javascript;

expires $expires;
location  / {
    proxy_pass        http://localhost:8000;
       include        proxy-settings.conf;
}

access_log /var/log/nginx/access.log;


}

See REST API doc

Benchmark

I used k6.io for benchmarking the read-by-id HTTP endoint. Details:

• CPU: Intel(R) Core(TM) i7-8650U CPU @ 1.90GHz (4 CPUs, 8 threads = 16 rocket workers)
• Mem: 24 GiB
• Storage: NVMe SSD Controller SM981/PM981/PM983
• both client (k6) and server (pastebin) running on the same machine

Setup

$ cargo run --release


$ echo "Hello world" | curl -q -L -d @- -o - http://localhost:8000/
http://localhost:8000/0FWc4aaZXzf6GZBsuW4nv

$ cat > script.js <<EOL
import http from "k6/http";

export default function() {
    let response = http.get("http://localhost:8000/&lt;ID&gt;");
};
EOL

$ docker pull loadimpact/k6

$ docker run --network=host -i loadimpact/k6 run --vus 5 -d 15s - <script.js


data_received..............: 206 MB 14 MB/s
data_sent..................: 1.6 MB 108 kB/s
http_req_blocked...........: avg=203.98µs min=59.63µs med=97.34µs max=280.74ms p(90)=142.01µs p(95)=161.72µs
http_req_connecting........: avg=60.48µs  min=0s      med=54.22µs max=9.57ms   p(90)=79.67µs  p(95)=93.6µs

http_req_duration..........: avg=4.75ms   min=2.87ms  med=4.66ms  max=27.25ms  p(90)=6.02ms   p(95)=6.59ms

http_req_receiving.........: avg=69.16µs  min=18.54µs med=59µs    max=12.94ms  p(90)=103µs    p(95)=128.14µs
http_req_sending...........: avg=53.21µs  min=18.11µs med=33.01µs max=5.82ms   p(90)=62.68µs  p(95)=166.06µs
http_req_tls_handshaking...: avg=0s       min=0s      med=0s      max=0s       p(90)=0s       p(95)=0s

http_req_waiting...........: avg=4.62ms   min=2.8ms   med=4.54ms  max=20.25ms  p(90)=5.87ms   p(95)=6.36ms

http_reqs..................: 14986  999.062363/s
iteration_duration.........: avg=4.98ms   min=2.96ms  med=4.8ms   max=299.92ms p(90)=6.18ms   p(95)=6.77ms

iterations.................: 14986  999.062363/s
vus........................: 5      min=5 max=5
vus_max....................: 5      min=5 max=5

docker run --network=host -i loadimpact/k6 run --vus 2 --stage 15s:4,15s:8,15s:16,15s:32 - <script.js


data_received..............: 654 MB 11 MB/s
data_sent..................: 5.9 MB 98 kB/s
http_req_blocked...........: avg=175.61µs min=56.88µs med=133.4µs max=168.74ms p(90)=175.38µs p(95)=219.87µs
http_req_connecting........: avg=86.58µs  min=0s      med=67.93µs max=34.36ms  p(90)=95.52µs  p(95)=116.89µs
http_req_duration..........: avg=13.29ms  min=2.64ms  med=8.3ms   max=129.12ms p(90)=30.32ms  p(95)=38.67ms 
http_req_receiving.........: avg=223.36µs min=18.63µs med=71.91µs max=39.84ms  p(90)=143.88µs p(95)=217.81µs
http_req_sending...........: avg=461.61µs min=17.23µs med=46.8µs  max=62.26ms  p(90)=335.01µs p(95)=857.64µs
http_req_tls_handshaking...: avg=0s       min=0s      med=0s      max=0s       p(90)=0s       p(95)=0s

http_req_waiting...........: avg=12.6ms   min=2.59ms  med=8ms     max=106.26ms p(90)=28.61ms  p(95)=36.55ms 
http_reqs..................: 47699  794.982442/s
iteration_duration.........: avg=13.48ms  min=2.75ms  med=8.47ms  max=185.95ms p(90)=30.55ms  p(95)=38.91ms 
iterations.................: 47699  794.982442/s
vus........................: 31     min=2  max=31
vus_max....................: 32     min=32 max=32

At first glance, the performance is pretty good. In the simplest scenario (5 concurrent clients), we can get up to 1000 rps with the p95 response time at 6.59 ms (14986 total requests made).

As we add more concurrent clients, the rps drops a bit (794 rps) but still provides a good timing (p95 38.67ms) with high throughput at 47699 request made in 15s window (3x compared to Test 1).

The CPU utilization is at 100% on every core available and the memory usage is stable at ~13 Mb RSS.

Demo