Deploying with Docker

Steps:#

  1. Install SigNoz backend as instructed in this page
  2. Instrument your application as instructed in Instructions Page

1. Using Install Script#

If you are on Mac or any of the following linux distributions, using our install script should be the easiest way to get started:

  • Ubuntu
  • Debian
  • OpenSuse
  • CentOS
  • SUSE Linux Enterprise Server (SLES)
  • RedHat
  • Amazon Linux

If you are not on one of the above distributions or on Mac, please install directly using Docker Compose


  1. To clone the SigNoz repository and enter the new directory, run:
git clone https://github.com/SigNoz/signoz.git && cd signoz/deploy/

  1. To run SigNoz:

Check that you are in signoz/deploy folder. Now run

./install.sh

  1. You will be given choice to either chose Clickhouse or Kafka+Druid as the storage backend
👉 Two ways to go forward
1) ClickHouse as database (default)
2) Kafka + Druid setup to handle scale (recommended for production use)

Once ./install.sh runs successfully, the UI should be accessible at port 3000 on the domain you set up or the IP of your instance.


info

Wait for 2-3 mins for the data to be available to frontend. If you are running on local machine, checkout http://localhost:3000. You would want to open port 3000 to be accessible from outside world if you want to use public url of machine.



2. Using Docker Compose#

  1. To clone the SigNoz repository and enter the new directory, run:
git clone https://github.com/SigNoz/signoz.git && cd signoz/deploy/

  1. You can chose either ClickHouse or Druid as the datastore. You need to have docker-compose correctly setup before running this.

Production Settings for Kafka + Druid setup#

A standard instance of SigNoz needs around 8GB of memory. The setup uses docker-compose.yaml file at deploy/docker/druid-kafka-setup

If you are interested in configuring S3 deep storage for production usage, check out this section


How to instrument your own applications#

The current docker-compose.yaml includes sample application (HotR.O.D) that generates tracing data. To see your own application data, follow the steps below

Checkout Instrumentation Section


Having issues running SigNoz?#

Checkout Troubleshooting Section

Deep Storage with S3 for Kafka+Druid Setup#

Checkout Configuration Section