pganalyze collector

This is a Go-based daemon which collects various information about Postgres databases as well as queries run on it.

All data is converted to a protocol buffers structure which can then be used as data source for monitoring & graphing systems. Or just as reference on how to pull information out of PostgreSQL.

It currently collects information about

• Schema
  • Tables (including column, constraint and trigger definitions)
  • Indexes
• Statistics
  • Tables
  • Indexes
  • Database
  • Queries
• OS
  • CPU
  • Memory
  • Storage

Installation

The collector is available in multiple convenient options:

• APT/YUM packages: https://packages.pganalyze.com/
• Docker sidekick service, see details further down in this file

Configuration (APT/YUM Packages)

After the package was installed, you can find the configuration in /etc/pganalyze-collector.conf

Adjust the values in that file by adding your API key (found in the pganalyze dashboard, use one per database server), and database connection credentials.

You can repeat the configuration block with a different [name] if you have multiple servers to monitor.

See https://pganalyze.com/docs/install for further details.

Setting up a Restricted Monitoring User

See https://pganalyze.com/docs/install/self_managed/01_create_monitoring_user (or the corresponding instructions for your platform) for details.

Example output

To get a feel for the data that is collected you can run the following command. This will show the data that would be sent (in JSON format), without sending it:

pganalyze-collector --dry-run

Don't hesitate to reach out to support@pganalyze.com if you have any questions about what gets sent, or how to adjust the collector data collection.

Docker Container (RDS)

If you are monitoring an RDS database and want to run the collector inside Docker, we recommend the following:

docker pull quay.io/pganalyze/collector:stable
docker run \
  --rm \
  --name pganalyze-mydb \
  -e DB_URL=postgres://username:password@my-instance-id.account.us-east-1.rds.amazonaws.com/mydb \
  -e PGA_API_KEY=YOUR_PGANALYZE_API_KEY \
  -e AWS_INSTANCE_ID=YOUR_RDS_DB_IDENTIFIER \
  quay.io/pganalyze/collector:stable

You'll need to set PGA_API_KEY, DB_URL, and AWS_INSTANCE_ID with the correct values.

Please also note that the EC2 instance running your Docker setup needs to have an IAM role that allows Cloudwatch access: https://pganalyze.com/docs/install/amazon_rds/03_setup_iam_policy

To get better data quality for server metrics, enable "Enhanced Monitoring" in your RDS dashboard. The pganalyze collector will automatically pick this up and get all the metrics.

We currently require one Docker container per RDS instance monitored.

If you have multiple databases on the same RDS instance, you can monitor them all by specifying DB_ALL_NAMES=true as an environment variable.

Docker Container (non-RDS)

If the database you want to monitor is running inside a Docker environment you can use the Docker image:

docker pull quay.io/pganalyze/collector:stable
docker run \
  --name my-app-pga-collector \
  --link my-app-db:db \
  --env-file collector_config.env \
  quay.io/pganalyze/collector:stable

collector_config.env needs to look like this:

PGA_API_KEY=$YOUR_API_KEY
PGA_ALWAYS_COLLECT_SYSTEM_DATA=true
DB_NAME=your_database_name
DB_USERNAME=your_database_user
DB_PASSWORD=your_database_password

The only required arguments are PGA_API_KEY (found in the pganalyze dashboard) and DB_NAME. Only specify PGA_ALWAYS_COLLECT_SYSTEM_DATA if the database is running on the same host and you'd like the collector to gather system metrics (from inside the container).

Note: You can add -v /path/to/database/volume/on/host:/var/lib/postgresql/data in order to collect I/O statistics from your database (this requires that it runs on the same machine).

Heroku Monitoring

When monitoring a Heroku Postgres database, it is recommended you deploy the collector as its own app inside your Heroku account.

Follow the instructions in the pganalyze documentation to add your databases to the collector.

Success/Error Callbacks

In case you want to run a script based on data collection running successfully and/or failing, you can set the success_callback and error_callback options:

[pganalyze]
...
error_callback=/usr/local/bin/my_error_script.sh

[mydb]
...

Note that the callback is executed in a shell, so you can use shell expressions as well.

The script will also have the following environment variables set:

• PGA_CALLBACK_TYPE (type of callback, error or success)
• PGA_CONFIG_SECTION (server that was processed, mydb in this example)
• PGA_SNAPSHOT_TYPE (type of data that was processed, currently there are full snapshots, as well as logs snapshots which contain only log data)
• PGA_ERROR_MESSAGE (error message, in the case of the error callback)

Helm Chart

You can install the Helm chart for the collector like the following:

helm repo add pganalyze https://charts.pganalyze.com/
helm install my-collector pganalyze/pganalyze-collector --values=myvalues.yml

You can find values for this chart using helm show values pganalyze/pganalyze-collector, or you can also find in the README in the Helm chart directory.

License

pganalyze-collector is licensed under the 3-clause BSD license, see LICENSE file for details.

Copyright (c) 2012-2023, Duboce Labs, Inc. (pganalyze)