• Developer guide
  • API reference

›Monitoring

Getting started

  • Introduction to Imply Polaris
  • Quickstart
  • Execute a POC
  • Create a dashboard
  • Navigate the console
  • Customize Polaris
  • Key concepts

Tables and data

  • Overview
  • Introduction to tables
  • Table schema
  • Ingestion jobs

    • Create an ingestion job
    • Ingest using SQL
    • Job auto-discovery
    • Timestamp expressions
    • SQL ingestion reference
    • Ingestion status reference
  • Data partitioning
  • Introduction to rollup
  • Replace data
  • Ingestion use cases

    • Approximation algorithms
    • Ingest earliest or latest value

Ingestion sources

  • Ingestion sources overview
  • Supported data formats
  • Create a connection
  • Ingest from files
  • Ingest data from a table
  • Ingest from S3
  • Ingest from Kafka and MSK
  • Ingest from Kinesis
  • Ingest from Confluent Cloud
  • Kafka Connector for Imply Polaris
  • Push event data
  • Connect to Confluent Schema Registry
  • Ingestion source reference

Analytics

  • Overview
  • Manage data cubes
  • Visualize data
  • Data cube dimensions
  • Data cube measures
  • Dashboards
  • Visualizations reference
  • Set up alerts
  • Set up reports
  • Embed visualizations

Querying

  • Overview
  • Time series functions

Monitoring

  • Overview
  • Monitoring dashboards
  • Monitor performance metrics
  • Integrate with Datadog
  • Integrate with Prometheus
  • Integrate with Elastic stack
  • Metrics reference

Management

  • Overview
  • Pause and resume a project

Usage and Billing

  • Billing structure overview
  • Polaris plans
  • Add a payment method
  • Monitor account usage

Security

    Polaris access

    • Overview
    • Invite users to your organization
    • Manage users
    • Permissions reference
    • Manage user groups
    • Enable SSO
    • SSO settings reference
    • Map IdP groups

    Secure networking

    • Connect to AWS
    • Create AWS PrivateLink connection

Developer guide

  • Overview
  • Security

    • Overview
    • Authenticate with API keys
    • Authenticate with OAuth
    • Manage users and groups
    • Restrict an embedding link
  • Migrate deprecated resources
  • Create a table
  • Upload files
  • Ingestion jobs

    • Create an ingestion job
    • Create a streaming ingestion job
    • Ingest using SQL
    • View and manage jobs

    Ingestion sources

    • Ingest from files
    • Ingest from a table
    • Get ARN for AWS access
    • Ingest from Amazon S3
    • Ingest from Kafka and MSK
    • Ingest from Amazon Kinesis
    • Ingest from Confluent Cloud
    • Push event data
    • Kafka Connector for Imply Polaris
    • Kafka Connector reference

    Ingestion use cases

    • Filter data to ingest
    • Ingest nested data
    • Ingest and query sketches
    • Specify data schema
    • Ingest Kafka metadata

    Analytics

    • Query data
    • Connect over JDBC
    • Link to BI tools
    • Query parameters reference
  • Update a project
  • API documentation

    • OpenAPI reference
    • Query API

    Migrations

    • Migrate from Hybrid

Product info

    Release notes

    • 2023
    • 2022
  • Known limitations
  • Druid extensions

Integrate with Datadog

This topic provides a sample configuration to set up Datadog to scrape performance metrics for your Polaris environment.

Prerequisites

  • Datadog environment. Configure Datadog to use a single Datadog Agent for scraping metrics from the Metrics API. You can reuse an existing Agent, install the Agent on an EC2 instance, or run the Agent somewhere else in your infrastructure. Refer to the Datadog documentation for instructions on how to configure the Agent to report to your Datadog account.
  • Datadog's OpenMetrics check. Refer to the OpenMetrics setup instructions to configure the OpenMetrics check for your Datadog Agent.
  • A Polaris API key with the AccessMetrics permission. See Authenticate with API keys to obtain an API key and assign service account permissions. For more information on permissions, visit Permissions reference.

Instructions

The following is an example configuration to ingest metrics into Datadog using the OpenMetrics check. Update the config file in ${datadog-agent}/conf.d/openmetrics.d/conf.yaml to match the example configuration. For more advanced use cases, refer to the Datadog documentation.

instances:
  # The endpoint to collect metrics about Polaris. Replace ORGANIZATION_NAME with the name of your organization.
  - openmetrics_endpoint: https://ORGANIZATION_NAME.api.imply.io/v1/metrics/export

    # The namespace added to all metrics. This can be changed.
    namespace: imply

    auth_type: basic
    username: apikey
    # Replace POLARIS_API_KEY with your API key. Ensure that the API key has the AccessMetrics permission.
    password: POLARIS_API_KEY

    # Ask Datadog to ingest all metrics reported by Polaris.
    # You may change this to ingest just a subset of metrics if you are not interested in the entire set.
    metrics: [.*]

    # Polaris updates metrics every minute, so this interval is set to 60 seconds.
    min_collection_interval: 60

Optional: You can test this integration locally with the following Docker command. Before running the command, create a file named conf.yaml in your working directory and copy the configuration into that file. Replace DD_API_KEY with your Datadog API key.

docker run -d --name dd-agent \
  -v /var/run/docker.sock:/var/run/docker.sock:ro \
  -v /proc/:/host/proc/:ro \
  -v /sys/fs/cgroup/:/host/sys/fs/cgroup:ro \
  -v ${PWD}/conf.yaml/:/etc/datadog-agent/conf.d/openmetrics.d/conf.yaml \
  -e DD_API_KEY=YOUR_DD_API_KEY \
  gcr.io/datadoghq/agent:7

Learn more

See the following topics for more information:

  • Monitor performance metrics
  • Metrics reference
← Monitor performance metricsIntegrate with Prometheus →
  • Prerequisites
  • Instructions
  • Learn more
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