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Metrics Flow Daemon Build Status Go Report

It is a small daemon that aggregates custom monitoring metrics collected from Google Dataflow workers that use metrics-flow library and exposes them to Prometheus.

How it works

Google Dataflow workers with metrics-flow plugged in pre-aggregate custom monitoring metrics using pipeline windowing functions and dump the results into a Google Pub/Sub topic. The metrics flow daemon polls a subscription to the topic, converts received metric update events to Prometheus format and exposes them through /metrics endpoint.

+------------+                                                      
| Dataflow 1 +----+                                                 
+------------+    |                                                 
                  |                                                 
+------------+    |                       +------------+            
| Dataflow i |----|->(Google Pub/Sub)---->|   mflowd   |            
+------------+    |                       +------------+            
                  |                              ^                  
+------------+    |                              |                  
| Dataflow N |----+                       +-------------+           
+------------+                            | Prometheus  |           
                                          +-------------+

Installation

% go get github.com/QubitProducts/mflowd

Build it from scratch

  1. Make sure you have dep installed (if you don't know how to install it, follow this link)
  2. make bootstrap
  3. make test
  4. make mflowd

Running

  1. Create a pub/sub topic you will use for publishing metrics from your Dataflow workers (if you don't have one already).

  2. Create a pull subscription to the topic

  3. Make sure you are authorized to use the subscription (if not sure, use gcloud auth login)

  4. Run the daemon

    % ./mflowd [-v] -p <port> -s pubsub <subscription_id>

Where

  • port is a port where /metrics endpoint will be exposed
  • subscription_path is a subscription identifier which usually looks like projects/<project_name>/subscriptions/<subcsciption_name>
  • use optional -v flag to run the daemon in verbose mode

Using Docker

You can easily build a "containerized" version of mflowd and run it on mesos or kubernetes.

Building

% make docker
% docker images | grep mflowd
mflowd                                             latest                                            e9cbac93f703
...

Running

Before you can run the image you need to set up a Google Cloud API service account to allow mflowd use the subscription you have created. So

  1. Create a service account for mflowd

  2. Create an empty directory on your host machine (say, % mkdir ~/.mflowd)

  3. Download the service account key in JSON format and put it to the created directory

  4. Finally run the countainer:

    % docker run -e "MFLOWD_SUB=<subscription_id>" -v $HOME/.mflowd:/etc/mflowd 'mflowd:latest'

Using docker-compose

You can also run both mflowd and prometheus docker images using docker-compose:

% cd ~/go/src/github.com/QubitProducts/mflowd
% mkdir gcp
# download your service account JSON key to gcp directory
% cat > .env
MFLOWD_SUB=<subscription_id>
MFLOWD_VERBOSE=0 # set to 1 to turn verbose mode on
^C
% docker-compose up

Follow http://localhost:9090 to get to Prometheus UI