ClickHouse is very popular database for storing telemetry data and running efficient queries on it.

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Use Cases

  • Clickhouse can handle all 3 signals (metrics, logs, traces) in one single database. less overhead to manage multiple databases.
  • Clickhouse is a columnar database, which is optimized for time-series immutable data like OpenTelemetry telemetry data.
  • Clickhouse is a distributed database, which can scale horizontally and handle large amounts of data with efficient storage and query performance.
  • Clickhouse is open-source and has a large community.

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Prerequisites

  • To use ClickHouse as a destination in Odigos, you need to have a ClickHouse deployment running somewhere and accessible from cluster where Odigos is running.
  • You should know the service endpoint where ClickHouse listens for incoming client connections.
  • If you haven’t already, create a database in ClickHouse where you want to store the telemetry data. the default database name is otel (configurable). To create it, run the following SQL command: CREATE DATABASE otel;
  • Understanding of how to maintain, scale, and optimize your self-hosted ClickHouse deployment, as well as how to fine tune setting based on your queries and use case.

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Schema

When using the ClickHouse destination with Odigos, logs metrics and traces are going to be “INSERT INTO” the ClickHouse database.

It is important to understand what schema is used, e.g. what table names are used, column names, data types, etc. Then you can run queries on this data, or modify and optimize it for your specific use case.

There are 2 modes of operation for ClickHouse destination in Odigos:

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Create Schema

In this option, the schema will be automatically created by odigos with reasonable defaults.

The benefit of this option is that you can see the value fast, without needing to apply and manage any schema yourself. The downside is that the schema may not be optimized for your specific use case, and may make changes more complicated.

To use it:

  • Odigos UI - When adding a new ClickHouse destination, select the Create Option under the Create Scheme field.
  • Destination K8s Manifest - Set the CLICKHOUSE_CREATE_SCHEME setting to value Create.

The schema which will be used by default can be found here.

  • Indexes - The default schema includes indexes for the data, including trace_id, resource and scope attributes, span/metric/log attributes etc.
  • TTL is set to 180 days. This means data will be kept in the database for this period of time and then deleted.
  • Partitioning - The default schema includes partitioning by day, which means data is stored in separate partitions for each day.
  • Order By - Optimized for trace queries on service_name + span_name + time, for logs on service_name + time, and for metrics on service_name + metric_name + attributes + time.

This option is not recommended for production workloads:

  • You may want to adjust the settings to better fit your use case, scale performance requirements, and costs.
  • Each new exporter will attempt to create the schema, which is less robust and harder to manage than a pre-created schema.

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Self Managed Schema

With this option, you are responsible for creating and managing the schema yourself.

To use it:

  • Odigos UI - In Create Scheme field, select the the Skip Option.
  • Destination K8s Manifest - Set the CLICKHOUSE_CREATE_SCHEME setting to value Skip.

The benefit of this option is that you have full control over the schema, and can optimize it for your specific use case.

How it works?

  • Browse to the default DDL example.
  • Copy the sql files to your local machine.
  • Make any changes you need to the schema.
  • Run the SQL files in your ClickHouse database to create the schema.

This option is recommended for production workloads:

  • You can optimize the schema for your specific use case, scale performance requirements, and costs.
  • You can manage the schema in a version control system, and apply changes in a controlled way.
  • Applying changes to the schema is more robust and easier to manage than attempting to create it on the fly with each new connection.

Important Settings:

  • Indexes - You may want to add or remove indexes based on your queries, to optimize performance and costs.
  • TTL - You may want to adjust the TTL based on your retention policy. If you need traces for auditing purposes, you may extend it to 365 days. For high-throughput, low-latency systems, you might want to reduce it to 90 days or even less.
  • Partitioning - partitioning by day is a good default, but in high throughput systems you may want to partition by hour or even minute. You may also consider partitioning by service_name, or other attributes.
  • Order By - You may want to adjust the order by clause based on your queries, so that common columns are used first in the query, to optimize performance.

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Configuration

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Endpoint

The ClickHouse endpoint is the URL where the ClickHouse server is listening for incoming connections. This is a required setting.

  • You can use http, tcp or clickhouse protocols
  • You can use insecure or secure connections (https:// or tcp://addr1:port?secure=true)
  • Can specify multiple host with port: http://addr1:port,addr2:port
  • Specify ClickHouse options with query parameters: http://addr1:port?dial_timeout=5s&compress=lz4

Please note you are using the correct port for your protocol, defaults are:

  • http: 8123
  • tcp: 9000
  • https: 9440

If you are not sure, use the http / https protocol, as they are more versatile and easier to configure.

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Credentials

If your ClickHouse server requires authentication, you can specify the username and password in the configuration. These are optional, keep empty if your ClickHouse server does not require authentication.

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Schema

  • Create Schema - Set to Skip if you manage your own schema, or Create to have Odigos create the schema for you. See Create Schema for more details.
  • Database Name (Required) - The name of the Clickhouse Database where the telemetry data will be stored. The default is otel. The Database will not be created when not exists, so make sure you have created it before.
  • Table Names - Allows you to customize the names of the tables where the telemetry data will be stored. The default is otel_traces for traces and otel_metrics for metrics.

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Adding a Destination to Odigos

Odigos makes it simple to add and configure destinations, allowing you to select the specific signals [traces/logs/metrics] that you want to send to each destination. There are two primary methods for configuring destinations in Odigos:

  1. Using the UI
    To add a destination via the UI, follow these steps:
    • Use the Odigos CLI to access the UI: Odigos UI
    odigos ui

  • In the left sidebar, navigate to the Destination page.

  • Click Add New Destination

  • Select ClickHouse and follow the on-screen instructions.

  1. Using kubernetes manifests

Save the YAML below to a file (e.g., destination.yaml) and apply it using kubectl:

kubectl apply -f destination.yaml

apiVersion: odigos.io/v1alpha1
kind: Destination
metadata:
  name: clickhouse-example
  namespace: odigos-system
spec:
  data:
    CLICKHOUSE_CREATE_SCHEME: <Create Scheme [Create, Skip]>
    # CLICKHOUSE_USERNAME: <Username>
    # Note: The commented fields above are optional.
    CLICKHOUSE_DATABASE_NAME: <Database Name>
    CLICKHOUSE_ENDPOINT: <Endpoint>
    CLICKHOUSE_LOGS_TABLE: <Logs Table>
    CLICKHOUSE_METRICS_TABLE: <Metrics Table>
    CLICKHOUSE_TRACES_TABLE: <Traces Table>
  destinationName: clickhouse
  # Uncomment the secretRef below if you are using the optional Secret.
  # secretRef:
  #   name: clickhouse-secret

  signals:
  - TRACES
  - METRICS
  - LOGS
  type: clickhouse

---
# The following Secret is optional. Uncomment the entire block if you need to use it.
# apiVersion: v1
# data:
#   CLICKHOUSE_PASSWORD: <base64 Password>
# kind: Secret
# metadata:
#   name: clickhouse-secret
#   namespace: odigos-system
# type: Opaque
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