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m3em's Introduction

M3

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Distributed TSDB and Query Engine, Prometheus Sidecar, Metrics Aggregator, and more such as Graphite storage and query engine.

Table of Contents

More Information

Community Meetings

You can find recordings of past meetups here: https://vimeo.com/user/120001164/folder/2290331.

Install

Dependencies

The simplest and quickest way to try M3 is to use Docker, read the M3 quickstart section for other options.

This example uses jq to format the output of API calls. It is not essential for using M3DB.

Usage

The below is a simplified version of the M3 quickstart guide, and we suggest you read that for more details.

  1. Start a Container
docker run -p 7201:7201 -p 7203:7203 --name m3db -v $(pwd)/m3db_data:/var/lib/m3db quay.io/m3db/m3dbnode:v1.0.0
  1. Create a Placement and Namespace
#!/bin/bash
curl -X POST http://localhost:7201/api/v1/database/create -d '{
  "type": "local",
  "namespaceName": "default",
  "retentionTime": "12h"
}' | jq .
  1. Ready a Namespace
curl -X POST http://localhost:7201/api/v1/services/m3db/namespace/ready -d '{
  "name": "default"
}' | jq .
  1. Write Metrics
#!/bin/bash
curl -X POST http://localhost:7201/api/v1/json/write -d '{
  "tags": 
    {
      "__name__": "third_avenue",
      "city": "new_york",
      "checkout": "1"
    },
    "timestamp": '\"$(date "+%s")\"',
    "value": 3347.26
}'
  1. Query Results

Linux

curl -X "POST" -G "http://localhost:7201/api/v1/query_range" \
  -d "query=third_avenue" \
  -d "start=$(date "+%s" -d "45 seconds ago")" \
  -d "end=$( date +%s )" \
  -d "step=5s" | jq .  

macOS/BSD

curl -X "POST" -G "http://localhost:7201/api/v1/query_range" \
  -d "query=third_avenue > 6000" \
  -d "start=$(date -v -45S "+%s")" \
  -d "end=$( date +%s )" \
  -d "step=5s" | jq .

Contributing

You can ask questions and give feedback in the following ways:

M3 welcomes pull requests, read contributing guide to help you get setup for building and contributing to M3.


This project is released under the Apache License, Version 2.0.

m3em's People

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m3em's Issues

Make m3em agents better suited for long term deployments

The current implementation of m3em was targeted at short-lived, transient clusters. This PR lists the things we should address if we want to make it more robust for long running clusters (in no particular order):

(1) Currently, the remote agents heartbeat to a coordinator periodically. If they aren’t able to heartbeat for a defined duration, they timeout and reset themselves to an un-initialised state, i.e. kill any running process, delete local data.

(2) Declarative state modelling: currently the flow control is modelled procedurally, i.e. a coordinator is given a list of remote agents, and it sends instructions to remote agents like "transfer file", "execute file", and so on. We’ll need to change this to be declarative to allow for more robust control

(3) Fault tolerant master: currently the coordinator initialises the connections with the remote agents and must stay alive for the duration of a test run. If the coordinator goes down, it is not able to recover the state of the running agents based on heartbeats. We should allow it to do so.

(4) Durable state: We do not persist expected state of the nodes anywhere. Persisting it in a durable store (etcd would be fine) is necessary for fault tolerance.

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