Sampler. Visualization for any shell command.

Sampler is a tool for shell commands execution, visualization and alerting. Configured with a simple YAML file.

Why do I need it?

One can sample any dynamic process right from the terminal — observe changes in the database, monitor MQ in-flight messages, trigger a deployment script and get notification when it's done.

If there is a way to get a metric using a shell command, then it can be visualized with Sampler momentarily.

Installation

macOS

HomeBrew:

brew install sampler

MacPorts:

sudo port install sampler

or

sudo curl -Lo /usr/local/bin/sampler https://github.com/sqshq/sampler/releases/download/v1.1.0/sampler-1.1.0-darwin-amd64
sudo chmod +x /usr/local/bin/sampler

Linux

sudo wget https://github.com/sqshq/sampler/releases/download/v1.1.0/sampler-1.1.0-linux-amd64 -O /usr/local/bin/sampler
sudo chmod +x /usr/local/bin/sampler

Note: libasound2-dev system library is required to be installed for Sampler to play a trigger sound tone. Usually the library is in place, but if not - you can install it with your favorite package manager, e.g apt install libasound2-dev

Packaging status

• Fedora sudo dnf install golang-github-sqshq-sampler (F31+)
• Arch yay -S sampler

Windows (experimental)

Recommended to use with advanced console emulators, e.g. Cmder

Via Chocolatey

choco install sampler

or

Download .exe

Docker

# Create a configuration file
vim config.yml

# Build the container image
docker build --tag sampler .

# Run a container
docker run --interactive --tty --volume $(pwd)/config.yml:/root/config.yml sampler --config /root/config.yml

Usage

You specify shell commands, Sampler executes them with a required rate. The output is used for visualization.

Using Sampler is basically a 3-step process:

• Define your shell commands in a YAML configuration file
• Run sampler -c config.yml
• Adjust components size and location on UI

But there are so many monitoring systems already

Sampler is by no means an alternative to full-scale monitoring systems, but rather an easy to setup development tool.

If spinning up and configuring Prometheus with Grafana is complete overkill for you task, Sampler might be the right solution. No servers, no databases, no deploy - you specify shell commands, and it just works.

Then it should be installed on every server I monitor?

No, you can run Sampler on local, but still gather telemetry from multiple remote machines. Any visualization might have init command, where you can ssh to a remote server. See the SSH example

Contents

• Components
  • Runchart
  • Sparkline
  • Barchart
  • Gauge
  • Textbox
  • Asciibox
• Bells and whistles
  • Triggers (conditional actions)
  • Interactive shell (database interaction, remote server access, etc)
  • Variables
  • Color theme
• Real-world recipes (contributions welcome!)
  • Databases (MySQL, PostgreSQL, MongoDB, Neo4j)
  • Kafka
  • Docker
  • SSH
  • JMX

Components

The following is a list of configuration examples for each component type, with macOS compatible sampling scripts.

Runchart

runcharts:
  - title: Search engine response time
    rate-ms: 500        # sampling rate, default = 1000
    scale: 2            # number of digits after sample decimal point, default = 1
    legend:
      enabled: true     # enables item labels, default = true
      details: false    # enables item statistics: cur/min/max/dlt values, default = true
    items:
      - label: GOOGLE
        sample: curl -o /dev/null -s -w '%{time_total}'  https://www.google.com
        color: 178      # 8-bit color number, default one is chosen from a pre-defined palette
      - label: YAHOO
        sample: curl -o /dev/null -s -w '%{time_total}'  https://search.yahoo.com
      - label: BING
        sample: curl -o /dev/null -s -w '%{time_total}'  https://www.bing.com

Sparkline

sparklines:
  - title: CPU usage
    rate-ms: 200
    scale: 0
    sample: ps -A -o %cpu | awk '{s+=$1} END {print s}'
  - title: Free memory pages
    rate-ms: 200
    scale: 0
    sample: memory_pressure | grep 'Pages free' | awk '{print $3}'

Barchart

barcharts:
  - title: Local network activity
    rate-ms: 500        # sampling rate, default = 1000
    scale: 0            # number of digits after sample decimal point, default = 1
    items:
      - label: UDP bytes in
        sample: nettop -J bytes_in -l 1 -m udp | awk '{sum += $4} END {print sum}'
      - label: UDP bytes out
        sample: nettop -J bytes_out -l 1 -m udp | awk '{sum += $4} END {print sum}'
      - label: TCP bytes in
        sample: nettop -J bytes_in -l 1 -m tcp | awk '{sum += $4} END {print sum}'
      - label: TCP bytes out
        sample: nettop -J bytes_out -l 1 -m tcp | awk '{sum += $4} END {print sum}'

Gauge

gauges:
  - title: Minute progress
    rate-ms: 500        # sampling rate, default = 1000
    scale: 2            # number of digits after sample decimal point, default = 1
    percent-only: false # toggle display of the current value, default = false
    color: 178          # 8-bit color number, default one is chosen from a pre-defined palette
    cur:
      sample: date +%S  # sample script for current value
    max:
      sample: echo 60   # sample script for max value
    min:
      sample: echo 0    # sample script for min value
  - title: Year progress
    cur:
      sample: date +%j
    max:
      sample: echo 365
    min:
      sample: echo 0

Textbox

textboxes:
  - title: Local weather
    rate-ms: 10000      # sampling rate, default = 1000
    sample: curl wttr.in?0ATQF
    border: false       # border around the item, default = true
    color: 178          # 8-bit color number, default is white
  - title: Docker containers stats
    rate-ms: 500
    sample: docker stats --no-stream --format "table {{.Name}}\t{{.CPUPerc}}\t{{.MemUsage}}\t{{.PIDs}}"

Asciibox

asciiboxes:
  - title: UTC time
    rate-ms: 500        # sampling rate, default = 1000
    font: 3d            # font type, default = 2d
    border: false       # border around the item, default = true    
    color: 43           # 8-bit color number, default is white
    sample: env TZ=UTC date +%r

Bells and whistles

Triggers

Triggers allow to perform conditional actions, like visual/sound alerts or an arbitrary shell command. The following examples illustrate the concept.

Clock gauge, which shows minute progress and announces current time at the beginning of each minute

gauges:
  - title: MINUTE PROGRESS
    position: [[0, 18], [80, 0]]  
    cur:
      sample: date +%S
    max:
      sample: echo 60
    min:
      sample: echo 0
    triggers:
      - title: CLOCK BELL EVERY MINUTE
        condition: '[ $label == "cur" ] && [ $cur -eq 0 ] && echo 1 || echo 0'  # expects "1" as TRUE indicator
        actions:
          terminal-bell: true  # standard terminal bell, default = false
          sound: true    # NASA quindar tone, default = false
          visual: false  # notification with current value on top of the component area, default = false
          script: say -v samantha `date +%I:%M%p`  # an arbitrary script, which can use $cur, $prev and $label variables

Search engine latency chart, which alerts user when latency exceeds a threshold

runcharts:
  - title: SEARCH ENGINE RESPONSE TIME (sec)
    rate-ms: 200
    items:
      - label: GOOGLE
        sample: curl -o /dev/null -s -w '%{time_total}'  https://www.google.com
      - label: YAHOO
        sample: curl -o /dev/null -s -w '%{time_total}'  https://search.yahoo.com     
    triggers:
      - title: Latency threshold exceeded
        condition: echo "$prev < 0.3 && $cur > 0.3" |bc -l  # expects "1" as TRUE indicator
        actions:
          terminal-bell: true  # standard terminal bell, default = false
          sound: true   # NASA quindar tone, default = false
          visual: true  # visual notification on top of the component area, default = false
          script: 'say alert: ${label} latency exceeded ${cur} second' # an arbitrary script, which can use $cur, $prev and $label variables

Interactive shell support

In addition to the sample command, one can specify init command (executed only once before sampling) and transform command (to post-process sample command output). That covers interactive shell use case, e.g. to establish connection to a database only once, and then perform polling within interactive shell session.

Basic mode

textboxes:
  - title: MongoDB polling
    rate-ms: 500
    init: mongo --quiet --host=localhost test # executes only once to start the interactive session
    sample: Date.now();                       # executes with a required rate, in scope of the interactive session
    transform: echo result = $sample          # executes in scope of local session, $sample variable is available for transformation

PTY mode

In some cases interactive shell won't work, because its stdin is not a terminal. We can fool it, using PTY mode:

textboxes:
  - title: Neo4j polling
    pty: true  # enables pseudo-terminal mode, default = false
    init: cypher-shell -u neo4j -p pwd --format plain
    sample: RETURN rand();
    transform: echo "$sample" | tail -n 1
  - title: Top on a remote server
    pty: true  # enables pseudo-terminal mode, default = false
    init: ssh -i ~/user.pem [email protected]
    sample: top    

Multistep init

It is also possible to execute multiple init commands one after another, before you start sampling.

textboxes:
  - title: Java application uptime
    multistep-init:
      - java -jar jmxterm-1.0.0-uber.jar
      - open host:port # or local PID
      - bean java.lang:type=Runtime
    sample: get Uptime

Variables

If the configuration file contains repeated patterns, they can be extracted into the variables section. Also variables can be specified using -v/--variable flag on startup, and any system environment variables will also be available in the scripts.

variables:
    mongoconnection: mongo --quiet --host=localhost test
barcharts:
  - title: MongoDB documents by status
    items:
      - label: IN_PROGRESS
        init: $mongoconnection
        sample: db.getCollection('events').find({status:'IN_PROGRESS'}).count()
      - label: SUCCESS
        init: $mongoconnection
        sample: db.getCollection('events').find({status:'SUCCESS'}).count()
      - label: FAIL
        init: $mongoconnection
        sample: db.getCollection('events').find({status:'FAIL'}).count()

Color theme

theme: light # default = dark
sparklines:
  - title: CPU usage
    sample: ps -A -o %cpu | awk '{s+=$1} END {print s}'

Real-world recipes

Databases

The following are different database connection examples. Interactive shell (init script) usage is recommended to establish connection only once and then reuse it during sampling.

MySQL

# prerequisite: installed mysql shell

variables:
  mysql_connection: mysql -u root -s --database mysql --skip-column-names
sparklines:  
  - title: MySQL (random number example)
    pty: true
    init: $mysql_connection
    sample: select rand();

PostgreSQL

# prerequisite: installed psql shell

variables:
  PGPASSWORD: pwd
  postgres_connection: psql -h localhost -U postgres --no-align --tuples-only
sparklines:
  - title: PostgreSQL (random number example)
    init: $postgres_connection
    sample: select random();

MongoDB

# prerequisite: installed mongo shell

variables:
  mongo_connection: mongo --quiet --host=localhost test
sparklines:
  - title: MongoDB (random number example)
    init: $mongo_connection
    sample: Math.random();

Neo4j

# prerequisite: installed cypher shell

variables:
  neo4j_connection: cypher-shell -u neo4j -p pwd --format plain
sparklines:
  - title: Neo4j (random number example)
    pty: true
    init: $neo4j_connection
    sample: RETURN rand();
    transform: echo "$sample" | tail -n 1

Kafka

Kafka lag per consumer group

variables:
  kafka_connection: $KAFKA_HOME/bin/kafka-consumer-groups --bootstrap-server localhost:9092
runcharts:
  - title: Kafka lag per consumer group
    rate-ms: 5000
    scale: 0
    items:
      - label: A->B
        sample: $kafka_connection --group group_a --describe | awk 'NR>1 {sum += $5} END {print sum}'
      - label: B->C
        sample: $kafka_connection --group group_b --describe | awk 'NR>1 {sum += $5} END {print sum}'
      - label: C->D
        sample: $kafka_connection --group group_c --describe | awk 'NR>1 {sum += $5} END {print sum}'

Docker

Docker containers stats (CPU, MEM, O/I)

textboxes:
  - title: Docker containers stats
    sample: docker stats --no-stream --format "table {{.Name}}\t{{.CPUPerc}}\t{{.MemPerc}}\t{{.MemUsage}}\t{{.NetIO}}\t{{.BlockIO}}\t{{.PIDs}}"

SSH

TOP command on a remote server

variables:
  sshconnection: ssh -i ~/my-key-pair.pem [email protected]
textboxes:
  - title: SSH
    pty: true
    init: $sshconnection
    sample: top

JMX

Java application uptime example

# prerequisite: download [jmxterm jar file](https://docs.cyclopsgroup.org/jmxterm)

textboxes:
  - title: Java application uptime
    multistep-init:
      - java -jar jmxterm-1.0.0-uber.jar
      - open host:port # or local PID
      - bean java.lang:type=Runtime
    sample: get Uptime
    transform: echo $sample | tr -dc '0-9' | awk '{printf "%.1f min", $1/1000/60}'