- Install SigNoz backend as instructed in this page
- Instrument your application as instructed in Instructions Page
- To clone the SigNoz repository and enter the new directory, run:
- To run SigNoz:
Check that you are in
signoz/deploy folder. Now run
This should install a tiny instance setting which runs with 4GB of memory. This is just for demo/testing purpose and not to be used in production.
To test if everything is fine, run the following command
Output should look like this ( Should have 14 image names as shown below )
./install.sh runs successfully, the UI should be accessible at port 3000 on the domain you set up or the IP of your instance.
Wait for 2-3 mins for the data to be available to frontend. If you are running on local machine, checkout
You would want to open port 3000 to be accessible from outside world if you want to use public url of machine.
A standard instance of SigNoz needs around 8GB of memory. The
docker-compose.yaml file at
deploy/docker/ can handle around 100RPS or 5K events/sec. Email at firstname.lastname@example.org or join Slack for help in setting this up.
docker pswill show all containers created by SigNoz. Check if
historicalcontainers are running. They do not come up if there is a memory problem. You may want to increase alloted memory.
- If you are still facing issues, try re-running
./install.sh. This will retry installing containers which failed the first time.
- If you are facing issues like
Request failed with status code 400in frontend, then open
http://localhost:8888or port 8888 on your IP .This is druid console. Check if Datasource named
flattened_spanshas come up. If there is no Ingestion Supervsor running, then run
./install.shagain to bring them up.
- If you couldn't spot issues, feel free to join our slack community or shoot an email at email@example.com. We are generally always there.
You need to check the memory allocated to docker. Follow below steps:
a) Choose the Docker menu whale menu > Preferences from the menu bar and configure the runtime options described below.
b) Choose Resources from Preferences Menu and change Memory to 3GB
docker-compose.yaml includes sample application (HotR.O.D) that generates tracing data. To see your own application data, follow the steps below