Distributed Tracing
Overview
Observability is an important aspect of microservice-oriented applications. One of the key ingredients for observability is distributed tracing.
It is necessary to provide additional precautions when an application writes a record to a database that is later processed by Debezium. The active trace is effectively demarcated by the write to the database. If you want to include Debezium data in your application tracer, you must pass the trace metadata to Debezium.
You can add tracing support to Debezium through the OpenTelemetry specification.
Installation
To enable traceability in Debezium, you must install the required OpenTelemetry API packages on your Kafka Connect cluster, together with the OpenTelemetry SDK.
There are three main methods for installing OpenTelemetry on Kafka Connect, each having its advantages:
- Manual installation
-
Offers more control and customization.
- Docker installation
-
Provides easier integration.
- Strimzi installation
-
Presents a ready-to-use solution on Kubernetes that includes all of the necessary OpenTelemetry components.
Manual installation of OpenTelemetry
A manual installation provides greater control and customization.
Installing the OpenTelemetry API
Install the following packages to the Kafka Connect classpath:
You can download the OpenTelemetry packages directly from the Maven repository, or retrieve the packages by using the Maven dependency plugin to ensure version compatibility.
Using the Maven Dependency Plugin
-
Create a POM file similar to the one in the following example. In your version of the file, specify the version of the OpenTelemetry package that you want to use.
<?xml version="1.0"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>group.id</groupId> <artifactId>artifact-id</artifactId> <version>0.0.1</version> <properties> <version.opentelemetry.api>1.23.1</version.opentelemetry.api> <version.opentelemetry.kafka.clients.2.6>1.23.0-alpha</version.opentelemetry.kafka.clients.2.6> </properties> <dependencies> <dependency> <groupId>io.opentelemetry</groupId> <artifactId>opentelemetry-api</artifactId> <version>${version.opentelemetry.api}</version> </dependency> <dependency> <groupId>io.opentelemetry.instrumentation</groupId> <artifactId>opentelemetry-kafka-clients-2.6</artifactId> <version>${version.opentelemetry.kafka.clients.2.6}</version> </dependency> </dependencies> </project>
-
In the directory that contains the
pom.xml
file, run the following command to download all dependencies (including transitives) to a specified directory (for example,./lib
)mvn dependency:copy-dependencies -DoutputDirectory=./lib
Installing the OpenTelemetry SDK
After you install the API, install the OpenTelemetry SDK. Install the OpenTelemetry SDK on your Kafka connect cluster by using the Java agent for automatic instrumentation.
Using Docker to install OpenTelemetry
Prefer this installation method if you want to use Docker for local development or testing.
The OpenTelemetry API dependencies are installed in the Debezium Kafka Connect container image.
The JAR files are downloaded to a separate directory.
By default, the JAR files are not added to the class path.
To add the JAR files to the class path, set the environment variable ENABLE_OTEL
to true
.
You must also install the OpenTelemetry Java agent.
Using Strimzi to install Open Telemetry
Strimzi provides a way to deploy an Apache Kafka cluster on Kubernetes.
The Strimzi Kafka image includes all of the necessary OpenTelemetry components.
If you want to view the OpenTelemetry components that are available in the Strimzi image, examine the compose file that is provided in the Debezium Outbox example.
Configuring OpenTelemetry
For information about how to configure OpenTelemetry, see the OpenTelemetry documentation.
Debezium was tested with a Debezium Kafka Connect image, and a Strimzi distribution that included the following configuration settings:
|
ActivateTracingSpan SMT
The main implementation point of tracing in Debezium is ActivateTracingSpan
SMT.
In this case, the application writing to a database is responsible for providing the tracing span context.
The writer must inject the span context into a java.util.Properties
instance that is serialized and written to the database as a distinct field of the table.
If the span context is not provided then the SMT will create a new span. In this case, Debezium operations together with metadata will be traced but will not be connected to business transaction traces to enable end-to-end tracing.
When this SMT is invoked with a message then it will:
-
extract the parent span context if present in the message
-
create the event
db-log-write
span context with the start timestamp set to the database log write timestamp -
insert fields from
source
block into the span as tags -
create the processing
debezium-read
span as a child ofdb-log-write
span with the start timestamp set to the processing time of the even -
insert fields from envelope such as
op
into the processing span as tags -
injects the processing span context into message headers
Kafka Producer tracing
Optionally it is possible to enable tracing at the Kafka producer level. If you enable tracing in the Kafka producer, when messages are written to the Kafka broker, the producer extracts the Debezium processing span context from the Kafka message headers, creates a new child span, and then records information about the write operation to the broker. Then it injects the new span into the message headers so a consumer of the message can restore the trace and resume end-to-end tracing.
The interceptor cannot propagate the traceability context if the Kafka instrumentation is enabled. The interceptor simply propagates the traceability context before delegating the instrumentation to the OpenTelemetry SDK.
Enabling end-to-end traceability
-
Download and install the debezium-interceptor to the Kafka Connect classpath.
-
Disable the automatic OpenTelemetry instrumentation at the Kafka producer and consumer by setting the value of
otel.instrumentation.common.default-enabled
tofalse
.
Configuration options
Configuration property |
Type |
Default |
|
string |
tracingspancontext |
|
string |
debezium-read |
|
boolean |
false |
Outbox Extension
The Debezium Quarkus extension for implementing the outbox pattern provides the additional functionality necessary for tracing context propagation out-of-the-box.
Specifically, it provides the tracingspancontext
field in the outbox table, which is used for passing the tracing span context from a service using the outbox extension to the Debezium connector.
When an outbox event is emitted, the extension will:
-
create a new
outbox-write
span as a child of current active span -
inject the span context into that
java.util.Properties
instance that is serialized into thetracingspancontext
column -
write the record into the database
The tracing integration in the outbox extension is automatically enabled if the quarkus-opentelemetry
extension is present.
If you want to disable tracing support for the outbox extension despite the presence of the quarkus-opentelemetry
extension,
set the option quarkus.debezium-outbox.tracing.enabled=false
in the Quarkus application.properties
file.
Event Router SMT
The Event Router SMT acts as an Outbox extension counterpart, it executes the same steps as the ActivateTracingSpan
SMT, and is used instead of it.