Overview

The Kafka Transport Adapter (hereinafter Kafka TA) provides the FIXEdge server connectivity to the Kafka distributed streaming platform. 

Internally, its implementation uses the Kafka Consumer and Producer APIs. The broker API version must be 0.10.0.0 or higher.  v version >= 0.10.0.0ersion >= 0.10.0.0

The Kafka TA acts as a FIXEdge plugin and establishes a connection to a Kafka single instance or a Kafka cluster. The adapter supports TLS connectivity.

The Kafka TA transfers FIX messages in raw or serialized formats from the FIXEdge Server to the Kafka platform and vice versa.

The Kafka TA performance is close to Kafka's native speed of processing. The average reading/writing rate of FIX messages is 30,000 per second or higher. This number refers to the overall throughput capacity for the FIXEdge server with the Kafka TA (from FIX session to Kafka server).

The Kafka TA automatically reconnects to Kafka if the connection to a message broker was unexpectedly terminated. Reconnection behavior can be configured by parameters TransportLayer.KafkaTA.reconnect.backoff.ms and TransportLayer.KafkaTA.reconnect.backoff.max.ms.

Multiple instances of the Kafka TA can be configured using one library instance, inside one instance of FIXEdge. 

During FIXEdge server termination, the Kafka TA employs graceful termination, ensuring that message processing operations are executed correctly, completely, and without message loss. When the FIXEdge server fails and nongraceful termination occurs, messages will be retrieved from persistent message storage.

FIFO (First In First Out) ordering is guaranteed, meaning that the order in which messages were sent and received will be maintained upon the termination of the server instance.

Concept

The Kafka TA is intended to communicate FIX messages to other applications using the Kafka streaming platform as middleware.

Communication is provided between the FIXEdge server and a Kafka broker or cluster on the FIXEdge side.

The Kafka TA allows integration with Kafka via the Consumer/Producer API. FIXEdge clients, configured either as producers or consumers, push and pull messages to/from brokers housed in Kafka that organize and store messages according to topics. Brokers commit messages to disk storage for a customizable period of time or space, configurable according to the topic. Topics are further broken down into partitions, with each partition acting as a separate commit log. A broker administrator keeps track of consumers reading partitions by assigning offsets, thereby providing guaranteed-ordering. These features facilitate easy scaling and event replay, as well as the building of fault-tolerant systems.

The Kafka TA differentiates from other Transport Adapters in providing custom serialization/deserialization and durable message storage.

The schema below represents an interaction between FIXEdge and a customer's infrastructure via the Kafka solution.

Basic elements of the Kafka connectivity model

• Producer = publisher, the sender of messages
• Consumer = subscriber, the reader of messages
• Message/event = a single unit of data
• Broker = a server forming a storage layer containing one or more topics
• Topic = ordered collection of events that are organized and stored in a durable way
• Partition = buckets located within topics across which messages are distributed
• Commit log = a record of changes that is committed to disk and can be replayed by consumers
• Guaranteed ordering = a guarantee that a consumer of a given topic-partition will always read that partition's events in exactly the same order as they were written
• Offset = tracking feature that helps consumers remember its position when last reading a partition

Client behavior

When several clients (either one Producer or one Consumer, or both one Producer and one Consumer) are configured for the Kafka TA, all of them establish a connection to the Kafka platform when FIXEdge starts its work.
If one of the clients fails to establish a connection, the remaining clients are not affected by this failure.

Delivery

When the Kafka TA sends a message, it is first put into persistent storage, and then sent through the producer API to a Kafka broker. Once the Kafka platform sends a confirmation that the message was received, the Kafka TA marks the Kafka platform’s acknowledgement that the message was delivered in the persistent storage. These two steps implement a delivery guarantee. If the message couldn't be sent it will remain stored in the persistent storage. Once the FIXEdge server starts and Kafka connection is reestablished, any unsent messages in the persistent message storage will be processed before other runtime messages. After delivery, messages remain stored in the persistent message storage. 

Message ordering:

• FIX messages sent to Kafka via the Producer API are sent in the same order as the messages that FIXEdge sends to the client.
• FIXEdge fetches FIX messages via the Consumer API in the same order that messages arrive at a particular Kafka topic.
• The Kafka TA services discipline is FIFO (First In First Out) in the scope of one Kafka partition (for messages that come from one client).

The connectivity mechanism preserves FIX messages even if critical situations occur, such as:

• FIXEdge server is terminated
• Kafka TA crashes or does not start due to invalid configuration
• FIX Session is terminated non-gracefully
• message broker is down
• network disorder occurs

The Kafka TA provides an at least once delivery guarantee, (as opposed to only once). This means that messages are guaranteed to be delivered at least once, with the possibility of duplicates. 

Persistent Message Storage

Kafka TA persistent FIX messages in text format are stored as a file saved to a disk using memory mapping.

Storage is unlimited but should not exceed disk capacity.

All messages passing through the system are kept in the persistent message storage.

The TransportLayer.<KafkaNameTA>.Cleanup parameter provides the capability to cleanup the persistent message storage.

Committing to the Kafka platform 

The TransportLayer.KafkaTA.<Session>.Consumer.Commit parameter provides three strategies that dictate how commit messages (acknowledgements of messages received) are sent to the Kafka platform.

To choose the best strategy for prioritizing either speed or reliability for commit messages, refer to the table below (options are shown in descending order):

The three strategies are described in more detail here:

Message handling

The Kafka TA employs the following messaging handling methods:

• Sync message handling

  • Receiving messages in the Kafka TA from the Kafka platform is regarded as sync messaging.
  • Messages are not saved to any storage but become available at the FIXEdge Business Layer.  
  • Messages arrive at the FIXEdge Business Layer in the same order as they had arrived to the Kafka topic they were fetched from.

• Async message handling

  • Sending messages from the Kafka TA to the Kafka platform is regarded as async messaging.
  • Messages are saved to persistent message storage.

Configuration steps

Given that FIXEdge has already been installed in the user's environment, use the following steps to step up the Kafka TA:

1. Enable a transport adapter to be used by FIXEdge:
   In the ‘Transport Layer Section’ of the FIXEdge.properties, add the Kafka TA to the list of supported adapters:
   

   TransportLayer.TransportAdapters = TransportLayer.KafkaTA

   Note: If you use other transport adapters, just add TransportLayer.KafkaTA to the end of the list:
   

   TransportLayer.TransportAdapters = ..., TransportLayer.KafkaTA

2. Configure the Kafka TA by adding the Kafka TA section to the FIXEdge.properties file:
   

   TransportLayer.KafkaTA.Description = Kafka Transport Adaptor
   TransportLayer.KafkaTA.DllName = bin/KafkaTA-vc10-MD-x64.dll
   TransportLayer.KafkaTA.Sessions = Kafka
    
   TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9092
   TransportLayer.KafkaTA.Kafka.FIXVersion = FIX44
   
   TransportLayer.KafkaTA.Kafka.Consumer.Commit = Auto
   TransportLayer.KafkaTA.Kafka.Consumer.Topics = outputTopic
   TransportLayer.KafkaTA.Kafka.Consumer.group.id = ID
   
   TransportLayer.KafkaTA.Kafka.Producer.Topic = topic

   Note: Sample settings can be copied to the FIXEdge.properties file from the KafkaTA.properties file (located in the doc folder of the FIXEdge distribution package).
   
   

3. Configure rules for message routing from the Kafka TA.
   The Kafka TA Client is referred to the Business Layer (BL) by the ClientID name specified in the FIXEdge.properties file.  For a Kafka Business Layer configuration sample, refer to the Configuration sample sub-section.
   
   
4. Restart the FIXEdge server to apply the changes.

Configuring multiple adapter instances

Multiple instances of the Kafka TA can be used during one library instance, inside one instance of FIXEdge. 

To run multiple instances of the Kafka TA, each new instance must be assigned a new name and new session names. The name assigned to the new adapter instance must be consistent across parameters relating to that instance. New session names must be unique across all existing instances of the adapter. Topic names do not need to be unique.

TransportLayer.TransportAdapters = TransportLayer.Kafka1, TransportLayer.Kafka2

TransportLayer.Kafka1.Description = Kafka Transport Adaptor #1
TransportLayer.Kafka1.DllName = bin/KafkaTA-vc10-MD-x64.dll
TransportLayer.Kafka1.Sessions = Kafka_1
 
TransportLayer.Kafka1.Kafka_1.bootstrap.servers = localhost:9092
TransportLayer.Kafka1.Kafka_1.FIXVersion = FIX44

TransportLayer.Kafka1.Kafka_1.Consumer.Commit = Auto
TransportLayer.Kafka1.Kafka_1.Consumer.Topics = outputTopic
TransportLayer.Kafka1.Kafka_1.Consumer.group.id = ID
TransportLayer.Kafka1.Kafka_1.Producer.Topic = topic


TransportLayer.Kafka2.Description = Kafka Transport Adaptor #2
TransportLayer.Kafka2.DllName = bin/KafkaTA-vc10-MD-x64_2.dll
TransportLayer.Kafka2.Sessions = Kafka_2
 
TransportLayer.Kafka2.Kafka_2.bootstrap.servers = localhost:9093
TransportLayer.Kafka2.Kafka_2.FIXVersion = FIX44

TransportLayer.Kafka2.Kafka_2.Consumer.Commit = Auto
TransportLayer.Kafka2.Kafka_2.Consumer.Topics = outputTopic
TransportLayer.Kafka2.Kafka_2.Consumer.group.id = ID

TransportLayer.Kafka2.Kafka_2.Producer.Topic = topic

In the above example, there 2 separated instances of Kafka adapters:  "Kafka1" and "Kafka2". Session names are unique across all Kafka adapters

SSL Configuration Sample

listeners=PLAINTEXT://:9092,SSL://:9093
ssl.keystore.location=D:/SSL/kafka01.keystore.jks
ssl.keystore.password=123456
ssl.key.password=123456
ssl.truststore.location=D:/SSL/kafka.truststore.jks
ssl.truststore.password=123456
ssl.enabled.protocols=TLSv1.2,TLSv1.1,TLSv1

TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9093
TransportLayer.KafkaTA.Kafka.security.protocol = SSL
TransportLayer.KafkaTA.Kafka.ssl.ca.location = D:/SSL/root.pem

Configuration parameters

Connection to the Kafka platform can be established when the Kafka TA is properly configured with the Kafka IP address.

ERROR Session '<Session>': [Consumer/Producer]: <error_message>

Configuration sample

The samples below represent the Kafka TA's configuration with the minimal set of parameters required to run the adaptor:

Kafka TA configuration file:

#------------------------------------------------------------
# Transport Layer Section
#------------------------------------------------------------

# A comma separated list of identifiers of Transport Adapters should be loaded. 
TransportLayer.TransportAdapters = TransportLayer.KafkaTA

#------------------------------------------------------------
# The Kafka Transport Adaptor (KafkaTA) configuration file.
#------------------------------------------------------------

# Adaptor's name. Property is required 
TransportLayer.KafkaTA.Description = Kafka Transport Adaptor

# Contains path and name of the Kafka adaptor dll. Property is required 
TransportLayer.KafkaTA.DllName = bin/KafkaTA-vc10-MD-x64.dll

# List of adaptor sessions
TransportLayer.KafkaTA.Sessions = Kafka
 
# The following are parameters for each session
TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9092
TransportLayer.KafkaTA.Kafka.FIXVersion = FIX44

TransportLayer.KafkaTA.Kafka.Consumer.Commit = Auto
TransportLayer.KafkaTA.Kafka.Consumer.Topics = outputTopic
TransportLayer.KafkaTA.Kafka.Consumer.group.id = ID

TransportLayer.KafkaTA.Kafka.Producer.Topic = topic

Kafka Business Layer rules:

<FIXEdge>
    <BusinessLayer>

       <Rule>
            <Source>
                <FixSession SenderCompID="SC" TargetCompID="FE"/>
            </Source>
            <Action>
                <Send><Client Name="Kafka"/></Send>
            </Action>
        </Rule>
       <Rule>
            <Source>
                <Client Name="Kafka"/>
            </Source>
            <Action>
                <Send>
                    <FixSession SenderCompID="FE" TargetCompID="SC"/>
                </Send>
            </Action>
        </Rule>

        <DefaultRule>
            <Action>
                <DoNothing/>
            </Action>
        </DefaultRule>

    </BusinessLayer>
</FIXEdge>

Authentication Configuration

SSL certificate authentication

To configure SSL authentication, follow these steps:

1. Make sure the Kafka broker and adaptor are configured for SSL connection

2. Set client authentication as "required" in the server.properties file

   Example Expand source

   listeners=PLAINTEXT://:9092,SSL://:9093
   ssl.keystore.location=D:/SSL/kafka01.keystore.jks
   ssl.keystore.password=123456
   ssl.key.password=123456
   ssl.truststore.location=D:/SSL/kafka.truststore.jks
   ssl.truststore.password=123456
   ssl.enabled.protocols=TLSv1.2,TLSv1.1,TLSv1
   ssl.client.auth = required

3. Provide ssl.key details in the FIXEdge.properties file

   Example Expand source

   TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9093
   TransportLayer.KafkaTA.Kafka.security.protocol = SSL
   TransportLayer.KafkaTA.Kafka.ssl.ca.location = D:/SSL/root.pem
   TransportLayer.KafkaTA.Kafka.ssl.key.location = D:/SSL/kafka01.pem
   TransportLayer.KafkaTA.Kafka.ssl.key.password = 123456

SASL_PLAIN authentication

To configure SASL_PLAIN authentication:

1. Use the following files and corresponding settings to configure the Kafka broker

   server.properties file Expand source

   listeners=PLAINTEXT://:9092,SASL_PLAINTEXT://:9093
   advertised.listeners=PLAINTEXT://:9092,SASL_PLAINTEXT://:9093
   sasl.enabled.mechanisms=PLAIN
   authorizer.class.name=kafka.security.auth.SimpleAclAuthorizer
   allow.everyone.if.no.acl.found=true
   
   sasl.jaas.config= \ 
   org.apache.kafka.common.security.plain.PlainLoginModule required \
       username="admin" \
       password="admin-secret" \
       user_admin="admin-secret";

2. Use the following file and corresponding settings to configure the Kafka TA:

   FixEdge.properties file Expand source

   TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9092
   TransportLayer.KafkaTA.Kafka.security.protocol = SASL_PLAINTEXT
   TransportLayer.KafkaTA.Kafka.sasl.mechanism=PLAIN
   TransportLayer.KafkaTA.Kafka.sasl.username=admin
   TransportLayer.KafkaTA.Kafka.sasl.password=admin-secret

SASL_SSL authentication

This is a combination of an SSL connection with client authentication and SASL_PLAIN authentication.

To configure SASL_SSL authentication:

1. Use the following files and corresponding settings to configure the Kafka broker

   server.properties file Expand source

   listeners=PLAINTEXT://:9092,SASL_SSL://:9093
   advertised.listeners=PLAINTEXT://:9092,SASL_SSL://:9093
   ssl.keystore.location=D:/SSL/kafka01.keystore.jks
   ssl.keystore.password=123456
   ssl.key.password=123456
   ssl.truststore.location=D:/SSL/kafka.truststore.jks
   ssl.truststore.password=123456
   ssl.enabled.protocols=TLSv1.2,TLSv1.1,TLSv1
   ssl.client.auth = required
   sasl.enabled.mechanisms=PLAIN
   authorizer.class.name=kafka.security.auth.SimpleAclAuthorizer
   allow.everyone.if.no.acl.found=true
   
   sasl.jaas.config= \ 
   org.apache.kafka.common.security.plain.PlainLoginModule required \
       username="admin" \
       password="admin-secret" \
       user_admin="admin-secret";

2. Use the following file and corresponding settings to configure the Kafka TA:

   FixEdge.properties file Expand source

   TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9093
   TransportLayer.KafkaTA.Kafka.security.protocol = SSL
   TransportLayer.KafkaTA.Kafka.ssl.ca.location = D:/SSL/root.pem
   TransportLayer.KafkaTA.Kafka.ssl.key.location = D:/SSL/kafka01.pem
   TransportLayer.KafkaTA.Kafka.ssl.key.password = 123456
   TransportLayer.KafkaTA.Kafka.sasl.mechanism=PLAIN
   TransportLayer.KafkaTA.Kafka.sasl.username=admin
   TransportLayer.KafkaTA.Kafka.sasl.password=admin-secret

SASL_GSSAPI authentication

To configure SASL_GSSAPI authentication:

1. Use the following files and corresponding settings to configure the Kafka broker

   server.properties file Expand source

   listeners=PLAINTEXT://:9092,SASL_PLAINTEXT://:9093
   advertised.listeners=PLAINTEXT://:9092,SASL_PLAINTEXT://:9093
   sasl.enabled.mechanisms=GSSAPI
   sasl.mechanism.inter.broker.protocol=GSSAPI
   sasl.kerberos.service.name=kafka
   
   listener.name.sasl_plaintext.gssapi.sasl.jaas.config=com.sun.security.auth.module.Krb5LoginModule required \
     useKeyTab=true \
     storeKey=true \
     keyTab="D:/SSL/kafka_server.keytab" \
     principal="kafka/kafka_server@example.com";

2. Use the following file and corresponding settings to configure the Kafka TA
   

   FixEdge.properties file Expand source

   TransportLayer.KafkaTA.Kafka.bootstrap.servers = localhost:9092
   TransportLayer.KafkaTA.Kafka.security.protocol = SASL_GSSAPI
   TransportLayer.KafkaTA.Kafka.sasl.mechanism=GSSAPI
   TransportLayer.KafkaTA.Kafka.sasl.kerberos.service.name=kafka

Logging

Kafka exhaustive logging means that any action with a configuration parameter is logged.

List of logged actions:

• Adapter initialization
• Parsing validation errors
• Configuration parameters
• Sent and received messages

The following levels of logging are used for Kafka:

• ERROR - is always ON
• INFO - can be optionally ON 
• WARN - can be optionally ON 
• DEBUG - is turned off by default and is used in critical cases

Any configuration event is logged in the "Kafka_TA" log category in the log file via the INFO messages. 

The table below specifies the most common logging messages for Kafka.

Logging setup for saving messages processed by Kafka to a separate file

Kafka TA logs different events with different categories.

• Category 'Kafka_TA' is used for lifecycle, session state change, and errors events
• Categories with Kafka TA session name specified in TransportLayer.KafkaTA.Sessions are used for logging messages passing through the Kafka endpoints.
  

The following example shows how to save Kafka-related logs for multiple sessions to a separate file FIXEdge1/log/Kafka.log.

In the case of configuration with 3 sessions

TransportLayer.KafkaTA.Sessions = KafkaConsumer, KafkaNewOrderProducer, KafkaCancelOrderProducer

There would be 3 new log categories: KafkaConsumer, KafkaNewOrderProducer, KafkaCancelOrderProducer. 

Therefore logging configuration is

Log.KafkaConsumer.Device = File
Log.KafkaConsumer.DebugIsOn = true
Log.KafkaConsumer.NoteIsOn = true
Log.KafkaConsumer.File.Name = ../FIXEdge1/log/Kafka.log

Log.KafkaNewOrderProducer.Device = File
Log.KafkaNewOrderProducer.DebugIsOn = true
Log.KafkaNewOrderProducer.NoteIsOn = true
Log.KafkaNewOrderProducer.File.Name = ../FIXEdge1/log/Kafka.log
 
Log.KafkaCancelOrderProducer.Device = File
Log.KafkaCancelOrderProducer.DebugIsOn = true
Log.KafkaCancelOrderProducer.NoteIsOn = true
Log.KafkaCancelOrderProducer.File.Name = ../FIXEdge1/log/Kafka.log

And configuration for routing life cycle events to the same file as Kafka sessions

Log.Kafka_TA.Device = File
Log.Kafka_TA.DebugIsOn = true
Log.Kafka_TA.NoteIsOn = true
Log.Kafka_TA.File.Name = ../FIXEdge1/log/Kafka.log

For example, KafkaConsumer session log:

2020-12-07 11:12:35,093 UTC   DEBUG   [KafkaConsumer]  20132  The message content:
       headers: ,
       key: ,
       partition Id: 0,
       value: 8=FIX.4.4|9=146|35=D|49=FIXEDGE|56=Sender|34=2|52=20201207-11:12:35.065|11=BTC/USD_LimitB_GTC|55=BTC/USD|54=1|60=20160401-15:15:58.080|38=0.15|40=2|44=630.1|59=1|10=226|

FIXEdge replace SOHs delimiters in FIX message with pipes '|' for better visibility in these logs

2021-06-09 17:44:49,522 UTC INFO [Kafka_TA] 34188 Kafka Adaptor v.0.1 started.

Additional information about logging configuration can be found there: 

• FIXEdge logs format
• How to redirect FIX Antenna and/or FIXEdge logging to Syslog instead of files
• How to divide different categories and severities of log files into different files in the Logging section

Scheduling

The schedule settings regulate the work of Kafka TA Producer/Consumer. The schedule can be configured as a cron expression or directly tied up to FIXEdge.

If the cron expression is used for scheduling, the Producer/Consumer starts using Client's connection to the Kafka platform at a scheduled time. At a scheduled disconnection time, the Producer/Consumer stops using the Client's connection to Kafka.

If the schedule settings are directly tied up to FIXEdge, the Producer/Consumer starts using Client's connection to the Kafka platform at the moment when the FIXEdge server starts. When the FIXEdge server stops, the Producer/Consumer stops using the Client's connection to Kafka.

Scheduling is represented by the following properties:

• TransportLayer.KafkaTA.<Session>.ConnectTime
• TransportLayer.KafkaTA.<Session>.DisconnectTime

Refer to the table in the Configuration parameters section above.

Start and Stop operations for Kafka TA

FIXEdge C++ provides Start operation for Disconnected Kafka TA sessions and Stop operation for Connecting and Running Kafka TA sessions on request from the subscribed monitoring application.

Start operation

Start operation can be applied to Kafka TA sessions in the Disconnected state.

FIXEdge starts a particular Kafka TA session on the request from the subscribed monitoring application and if the operation has been applied replies with a successful response.

In case when there is no session with the requested name FIXEdge logs an error and replies to the subscribed monitoring application with an error response below: 

Can't find session with id <session_name>

Stop operation

Stop operation can be applied to Kafka TA sessions in the Running and Connecting states.

FIXEdge stops a particular Kafka TA session on the request from the subscribed monitoring application and if the operation has been applied replies with a successful response.

In case when there is no session with the requested name FIXEdge logs an error and replies to the subscribed monitoring application with an error response below: 

Can't find session with id <session_name>

The FIXEdge behavior in the case when Kafka TA Producer session is in the Disconnected state is determined by the RejectMessageWhileNoConnection parameter.

Custom serialization

When FIX messages are transferred in raw format (i.e. serialization is not applied), the Kafka TA implies a string containing the tag values has been converted to strings. 

A serialized format of communication is fully supported by the Kafka TA. Custom serialization implies specially designed external code and includes the serialization of all Kafka message parts:

• Key
• Value
• Header(-s)

Serialization on sending

When custom serialization is applied and FIXEdge sends the message to the particular Kafka topic, this message is serialized via the custom serializer and is sent to a particular Kafka topic via the Producer API. The following DEBUG message is logged in the client log category of the log file:

"The message content:
headers: <headers>,
key: <key>,
partition Id: <partition Id>,
value: <value>" 

Serialization on receiving

When custom serialization is applied and the new message arrives at the particular Kafka topic, this message is received by FIXEdge via the Consumer API. The following DEBUG message is logged in the client log category of the log file:

"The message content:
headers: <headers>,
key: <key>,
partition Id: <partition Id>,
value: <value>" 

The message is deserialized via the custom serializer.

Message key processing

In the case of default serialization, the Kafka TA produces a key using the value of the tag configured in the "KeyTag" parameter. The specified key is passed to the Kafka platform along with the message sent to the particular Kafka topic.

In the case of custom serialization, the custom plugin produces the key that is passed to the Kafka platform along with the message sent to the particular Kafka topic.

Custom partitioning

If custom partitioning is configured, the custom plugin produces the partition ID based on the tag values of a FIX message.

Message Content Wrapping

When FIXEdge sends a message to a particular Kafka topic and the BL Client is configured to work with XMLData (213), two flows are possible:

1.  The XMLData (213) field exists in the FIX message and is not empty.
   In this case, the XML message extracted from the XMLData (213) field is sent to the particular Kafka topic via the Producer API.
2.  The XMLData (213) field does not exist in the FIX message or is empty.
   In this case, the corresponding error is sent to the Business Layer and nothing is sent to a Kafka topic via the Producer API.

When Kafka sends an XML message to FIXEdge and the BL Client is configured to work with XMLData (213), the FIX message with 35=n (XML message, JSON plain text, etc.) is received by FIXEdge, the XMLData (213) field is filled in with the received XML message, and the XMLDataLen (212) field is filled in with the received message length.

Kafka Adapter Monitoring

The Kafka Transport Adapter is integrated with a FIXICC monitoring feature.

The adapter provides information about the following indicators:

Troubleshooting

Transport Adaptor 'KafkaTA' has failed to initialize

If the adapter fails to start up, there is an issue with a configuration parameter.

To resolve this issue, the configuration parameter specified in the error message must be corrected. Check the log for error messages.

Example

In this example, the path specified to the adapter dll is the incorrect one:

2020-11-25 15:51:39,019 UTC INFO [FixLayer_Version] 20936 Module 'FixLayer' version 0.2.1.5 was loaded.
2020-11-25 15:51:39,019 UTC INFO [Engine] 20936 Custom AdminApplication is registered.
2020-11-25 15:51:39,024 UTC ERROR [TransportLayer] 20936 Transport Adaptor 'KafkaTA' has failed to initialize: Error loading DLL 'd:\FIXEdge\bin\KafkaTA-vc10-MD-x64.dll'.
. The specified module could not be found. (Error code = 126)
2020-11-25 15:51:39,024 UTC INFO [TransportLayer] 20936 Module 'TransportLayer' version 0.1.1.5 was loaded.

The session wasn't created

If one session doesn’t load successfully during start-up while others are created successfully, there is an issue with a configuration parameter. 

To resolve this issue, the configuration parameter specified in the error message must be corrected. Check the log for error messages.

Example

In this example, two sessions ('Kafka' and 'Kafka2') are configured, and one was not created successfully.

In the first session, the wrong parameter, 'protocol', was used instead of the correct parameter, 'security.protocol', and the session was not created.

In the log file, an ERROR message saying, "Failed to set protocol..." appears instead of an INFO message saying, "Session 'Kafka': was created successfully".

Adapter not sending or receiving messages

If sessions have been created successfully, but the adapter isn’t sending or receiving messages to/from the Kafka server, this issue has most likely occurred due to a problem with the connection. 

If the adapter can’t connect to the Kafka server, it will continue to make connection attempts in given intervals until a reason for the error is established. Until this is done, the TA will not be able to send or receive messages. If the default level of logging doesn't explain the reason, you need to enable a deeper level of logging.

To establish what the error is, you must enable the DEBUG logging as follows:

1. Open the FIXEdge.properties file
2. Set the parameter Log.DebugIsOn = True

Once this is done, the log will show error messages stating previous connection attempts and the reason for the error. To resolve this issue, correct the configuration issue specified in the error message.

Example

In this example, the wrong server port, 9093 (for SSL connection), is configured instead of the correct one, 9092 (for PLAINTEXT connection).

With DEBUG logging enabled, we can see that the adapter is permanently trying to connect to the server, as well as an error message specifying the configuration issue.

2020-11-25 16:22:54,533 UTC   DEBUG   [Kafka_TA]  5808  Session 'Kafka': Producer: librdkafka ERROR: [thrd:app]: rdkafka#producer-2: localhost:9093/bootstrap: Disconnected while requesting ApiVersion: might be caused by incorrect security.protocol configuration (connecting to a SSL listener?) or broker version is < 0.10 (see api.version.request) (after 197ms in state APIVERSION_QUERY)
2020-11-25 16:22:54,534 UTC   DEBUG   [Kafka_TA]  10912  Session 'Kafka': Consumer: librdkafka ERROR: [thrd:localhost:9093/bootstrap]: 1/1 brokers are down
2020-11-25 16:22:54,534 UTC   DEBUG   [Kafka_TA]  22440  Session 'Kafka': Consumer: librdkafka ERROR: [thrd:app]: rdkafka#consumer-1: localhost:9093/bootstrap: Disconnected while requesting ApiVersion: might be caused by incorrect security.protocol configuration (connecting to a SSL listener?) or broker version is < 0.10 (see api.version.request) (after 1086ms in state APIVERSION_QUERY)
2020-11-25 16:22:54,761 UTC   DEBUG   [Kafka_TA]  10912  Session 'Kafka': Consumer: librdkafka ERROR: [thrd:localhost:9093/bootstrap]: 1/1 brokers are down
2020-11-25 16:22:55,033 UTC   DEBUG   [Kafka_TA]  24160  Session 'Kafka': Producer: librdkafka ERROR: [thrd:localhost:9093/bootstrap]: 1/1 brokers are down
2020-11-25 16:23:07,261 UTC   DEBUG   [Kafka_TA]  22440  Session 'Kafka': Consumer: librdkafka ERROR: [thrd:app]: rdkafka#consumer-1: localhost:9093/bootstrap: Disconnected while requesting ApiVersion: might be caused by incorrect security.protocol configuration (connecting to a SSL listener?) or broker version is < 0.10 (see api.version.request) (after 1ms in state APIVERSION_QUERY, 4 identical error(s) suppressed)
2020-11-25 16:23:07,261 UTC   DEBUG   [Kafka_TA]  10912  Session 'Kafka': Consumer: librdkafka ERROR: [thrd:localhost:9093/bootstrap]: 1/1 brokers are down
2020-11-25 16:23:15,441 UTC   DEBUG   [Kafka_TA]  24160  Session 'Kafka': Producer: librdkafka ERROR: [thrd:localhost:9093/bootstrap]: 1/1 brokers are down
2020-11-25 16:23:15,442 UTC   DEBUG   [Kafka_TA]  5808  Session 'Kafka': Producer: librdkafka ERROR: [thrd:app]: rdkafka#producer-2: localhost:9093/bootstrap: Disconnected while requesting ApiVersion: might be caused by incorrect security.protocol configuration (connecting to a SSL listener?) or broker version is < 0.10 (see api.version.request) (after 1ms in state APIVERSION_QUERY, 4 identical error(s) suppressed)

Messages are not delivered with the log stating: "Message processing failed"

The Kafka TA consumer receives a message but the message isn't delivered anywhere (for example, in a FIX session) and FixEdge.log states:

• "No BL rules found for message with ClientID '<client id>', executing DefaultRule."
• "Message processing failed"

2020-11-25 16:35:36,545 UTC DEBUG [Kafka_TA] 21964 Session 'Kafka2': Consumer: Receiving the message: 8=FIX.4.49=15235=D49=SC56=FE34=252=20201125-16:35:35.936212=4213=test11=BTC/USD_LimitB_GTC55=BTC/USD54=160=20160401-15:15:58.08038=0.1540=244=630.159=110=078
2020-11-25 16:35:36,545 UTC DEBUG [BL_RoutingTable] 21964 No BL rules found for message with ClientID 'Kafka2', executing DefaultRule.
2020-11-25 16:35:36,546 UTC DEBUG [CC_Layer] 21964 BL has processed a message. Number of client IDs for delivery :0. Number or FIX sessions for delivery :0.. Number or sources identifiers for delivery :0.

2020-11-25 16:35:36,546 UTC DEBUG [Kafka_TA] 21964 Session 'Kafka2': Consumer: Message processing failed

In order for this information to be recorded in the logs, the user should enable DEBUG logging by setting Log.DebugIsOn = true in FIXEdge.properties.

Root cause

This happens if the business logic is not configured for handling the message from the adapter or if message processing doesn't fit rule conditions.

Solution

• Check if there is a logic processing message from the Kafka TA Consumer.
  For example:

  BL_Config.xml

  		<Rule Description="Route order events from Kafka Consumer Adapter to active FIX-session">
  			<Source>
  				<Client Name="KafkaConsumer"/>
  			</Source>
  			<Action>
  				<Send>
  					<FixSession/>
  				</Send>
  			</Action>
  		</Rule>

• Check whether the message was filtered by rule conditions.
  If the message was filtered, extend the rules/conditions.

Kafka server can't start because all log dirs have failed

Starting the kafka-server-start script has failed with the following error: 

ERROR Shutdown broker because all log dirs in d:\tmp\kafka-logs have failed

Root cause

One of the possible reasons is that the Kafka logs are corrupted due to an unexpected shutdown.

Solution

Backup the Kafka and zookeeper logs according to the path in the error message (for this example it's d:\tmp\) for future investigation if needed.

Clean log dir by the specified log directories and restart the service.