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What is a Schema Payload Validation Policy Interceptor?

Avoid outages from missing or badly formatted records, ensure all messages adhere to a schema.

This interceptor also supports validating payload against specific constraints for AvroSchema and ProtoBuf

This is similar to the validations provided by JsonSchema, such as:

  • Number: minimum, maximum, exclusiveMinimum, exclusiveMaximum, multipleOf
  • String: minLength, maxLength, pattern, format
  • Collections: maxItems, minItems

This interceptor also supports validating payload against specific custom constraints expression, which uses a simple language familiar with devs is CEL (Common Expression Language)

This interceptor also supports validating payload against specific custom metadata.rules object in the schema using CEL, too.

View the full demo in realtime​

You can either follow all the steps manually, or watch the recording

Review the docker compose environment​

As can be seen from docker-compose.yaml the demo environment consists of the following services:

  • gateway1
  • gateway2
  • kafka-client
  • kafka1
  • kafka2
  • kafka3
  • schema-registry
  • zookeeper
cat docker-compose.yaml

Starting the docker environment​

Start all your docker processes, wait for them to be up and ready, then run in background

  • --wait: Wait for services to be running|healthy. Implies detached mode.
  • --detach: Detached mode: Run containers in the background
docker compose up --detach --wait

Creating virtual cluster teamA​

Creating virtual cluster teamA on gateway gateway1 and reviewing the configuration file to access it

# Generate virtual cluster teamA with service account sa
token=$(curl \
    --request POST "http://localhost:8888/admin/vclusters/v1/vcluster/teamA/username/sa" \
    --header 'Content-Type: application/json' \
    --user 'admin:conduktor' \
    --silent \
    --data-raw '{"lifeTimeSeconds": 7776000}' | jq -r ".token")

# Create access file
echo  """
bootstrap.servers=localhost:6969
security.protocol=SASL_PLAINTEXT
sasl.mechanism=PLAIN
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='sa' password='$token';
""" > teamA-sa.properties

# Review file
cat teamA-sa.properties

Creating topic topic-json-schema on teamA​

Creating on teamA:

  • Topic topic-json-schema with partitions:1 and replication-factor:1
kafka-topics \
    --bootstrap-server localhost:6969 \
    --command-config teamA-sa.properties \
    --replication-factor 1 \
    --partitions 1 \
    --create --if-not-exists \
    --topic topic-json-schema

Review the example json schema schema​

Review the example json schema schema

cat user-schema-with-validation-rules.json

Let's register it to the Schema Registry​

curl -s \
  http://localhost:8081/subjects/topic-json-schema/versions \
  -X POST \
  -H "Content-Type: application/vnd.schemaregistry.v1+json" \
  --data "{\"schemaType\": \"JSON\", \"schema\": $(cat user-schema-with-validation-rules.json | jq tostring)}"

Review invalid payload​

Review invalid payload

cat invalid-payload.json

Let's send invalid data​

Perfect the Json Schema serializer did its magic and validated our rules

cat invalid-payload.json | jq -c | \
    kafka-json-schema-console-producer \
        --bootstrap-server localhost:6969 \
        --producer.config teamA-sa.properties \
        --topic topic-json-schema \
        --property schema.registry.url=http://localhost:8081 \
        --property value.schema.id=1

Let's send invalid data using the protocol​

Unfortunately the message went through

MAGIC_BYTE="\000"
SCHEMA_ID="\000\000\000\001"
JSON_PAYLOAD=$(cat invalid-payload.json | jq -c)
printf "${MAGIC_BYTE}${SCHEMA_ID}${JSON_PAYLOAD}" | \
  kcat \
    -b localhost:6969 \
    -X security.protocol=SASL_PLAINTEXT \
    -X sasl.mechanism=PLAIN \
    -X sasl.username=sa \
    -X sasl.password=$(cat teamA-sa.properties | awk -F"'" '/password=/{print $4}') \
    -P \
    -t topic-json-schema

Let's consume it back​

That's pretty bad, you are going to propagate wrong data within your system!

kafka-json-schema-console-consumer \
    --bootstrap-server localhost:6969 \
    --consumer.config teamA-sa.properties \
    --topic topic-json-schema \
    --from-beginning \
    --skip-message-on-error \
    --timeout-ms 3000

Adding interceptor guard-schema-payload-validate​

Add Schema Payload Validation Policy Interceptor

cat step-13-guard-schema-payload-validate.json | jq

curl \
    --request POST "http://localhost:8888/admin/interceptors/v1/vcluster/teamA/interceptor/guard-schema-payload-validate" \
    --header 'Content-Type: application/json' \
    --user 'admin:conduktor' \
    --silent \
    --data @step-13-guard-schema-payload-validate.json | jq

Listing interceptors for teamA​

Listing interceptors on gateway1 for virtual cluster teamA

curl \
    --request GET 'http://localhost:8888/admin/interceptors/v1/vcluster/teamA' \
    --header 'Content-Type: application/json' \
    --user 'admin:conduktor' \
    --silent | jq

Let's send invalid data using the protocol again​

Perfect our interceptor did its magic and validated our rules

MAGIC_BYTE="\000"
SCHEMA_ID="\000\000\000\001"
JSON_PAYLOAD=$(cat invalid-payload.json | jq -c)
printf "${MAGIC_BYTE}${SCHEMA_ID}${JSON_PAYLOAD}" | \
  kcat \
    -b localhost:6969 \
    -X security.protocol=SASL_PLAINTEXT \
    -X sasl.mechanism=PLAIN \
    -X sasl.username=sa \
    -X sasl.password=$(cat teamA-sa.properties | awk -F"'" '/password=/{print $4}') \
    -P \
    -t topic-json-schema

Check in the audit log that message was denied​

Check in the audit log that message was denied in cluster kafka1

kafka-console-consumer \
    --bootstrap-server localhost:19092,localhost:19093,localhost:19094 \
    --topic _conduktor_gateway_auditlogs \
    --from-beginning \
    --timeout-ms 3000 \| jq 'select(.type=="SAFEGUARD" and .eventData.plugin=="io.conduktor.gateway.interceptor.safeguard.SchemaPayloadValidationPolicyPlugin")'

returns 1 event

{
  "id" : "d425a57d-2b48-45df-9f28-5365fd8c0e42",
  "source" : "krn://cluster=7LQ3kqW2T9-c-6VmovJgow",
  "type" : "SAFEGUARD",
  "authenticationPrincipal" : "teamA",
  "userName" : "sa",
  "connection" : {
    "localAddress" : null,
    "remoteAddress" : "/192.168.65.1:28612"
  },
  "specVersion" : "0.1.0",
  "time" : "2024-04-09T23:51:58.694086930Z",
  "eventData" : {
    "level" : "error",
    "plugin" : "io.conduktor.gateway.interceptor.safeguard.SchemaPayloadValidationPolicyPlugin",
    "message" : "Request parameters do not satisfy the configured policy. Topic 'topic-json-schema' has invalid json schema payload: hobbies must have 2 items, age must be greater than or equal to 18, email should end with 'example.com', #/hobbies: expected minimum item count: 2, found: 1, #/name: expected minLength: 3, actual: 1, #/email: [bad email] is not a valid email address, #/address/city: expected minLength: 2, actual: 0, #/address/street: expected maxLength: 15, actual: 56, street does not match expression 'size(street) >= 5 && size(street) <= 15', address does not match expression 'size(address.street) > 1 && address.street.contains('paris') || address.city == 'paris'', hobbies does not match expression 'size(hobbies) >= 2', name does not match expression 'size(name) >= 3', email does not match expression 'email.contains('foo')'"
  }
}

Let's now produce a valid payload​

cat valid-payload.json | jq -c | \
    kafka-json-schema-console-producer \
        --bootstrap-server localhost:6969 \
        --producer.config teamA-sa.properties \
        --topic topic-json-schema \
        --property schema.registry.url=http://localhost:8081 \
        --property value.schema.id=1

And consume it back​

kafka-json-schema-console-consumer \
    --bootstrap-server localhost:6969 \
    --consumer.config teamA-sa.properties \
    --topic topic-json-schema \
    --from-beginning \
    --skip-message-on-error \
    --timeout-ms 3000

Tearing down the docker environment​

Remove all your docker processes and associated volumes

  • --volumes: Remove named volumes declared in the "volumes" section of the Compose file and anonymous volumes attached to containers.
docker compose down --volumes

Conclusion

You can enrich your existing schema to add even more data quality to your systems!