Bringing up a Kafka-based Ordering Service
===========================================

.. _kafka-caveat:

Caveat emptor
-------------

This document assumes that the reader knows how to set up a Kafka cluster and a
ZooKeeper ensemble, and keep them secure for general usage by preventing
unauthorized access. The sole purpose of this guide is to identify the steps you
need to take so as to have a set of Hyperledger Fabric ordering service nodes
(OSNs) use your Kafka cluster and provide an ordering service to your blockchain
network.

For information about the role orderers play in a network and in a transaction
flow, checkout our :doc:`orderer/ordering_service` documentation.

For information on how to set up an ordering node, check out our :doc:`orderer_deploy`
documentation.

For information about configuring Raft ordering services, check out :doc:`raft_configuration`.

Big picture
-----------

Each channel maps to a separate single-partition topic in Kafka. When an OSN
receives transactions via the ``Broadcast`` RPC, it checks to make sure that the
broadcasting client has permissions to write on the channel, then relays (i.e.
produces) those transactions to the appropriate partition in Kafka. This
partition is also consumed by the OSN which groups the received transactions
into blocks locally, persists them in its local ledger, and serves them to
receiving clients via the ``Deliver`` RPC. For low-level details, refer to `the
document that describes how we came to this design <https://docs.google.com/document/d/19JihmW-8blTzN99lAubOfseLUZqdrB6sBR0HsRgCAnY/edit>`_.
**Figure 8** is a schematic representation of the process described above.

Steps
-----

Let ``K`` and ``Z`` be the number of nodes in the Kafka cluster and the
ZooKeeper ensemble respectively:

1. At a minimum, ``K`` should be set to 4. (As we will explain in Step 4 below,
   this is the minimum number of nodes necessary in order to exhibit crash fault
   tolerance, i.e. with 4 brokers, you can have 1 broker go down, all channels
   will continue to be writeable and readable, and new channels can be created.)

2. ``Z`` will either be 3, 5, or 7. It has to be an odd number to avoid
   split-brain scenarios, and larger than 1 in order to avoid single point of
   failures. Anything beyond 7 ZooKeeper servers is considered overkill.

Then proceed as follows:

3. Orderers: **Encode the Kafka-related information in the network's genesis
   block.** If you are using ``configtxgen``, edit ``configtx.yaml``. Alternatively,
   pick a preset profile for the system channel's genesis block—  so that:

  * ``Orderer.OrdererType`` is set to ``kafka``.
  * ``Orderer.Kafka.Brokers`` contains the address of *at least two* of the Kafka
    brokers in your cluster in ``IP:port`` notation. The list does not need to be
    exhaustive. (These are your bootstrap brokers.)

4. Orderers: **Set the maximum block size.** Each block will have at most
   ``Orderer.AbsoluteMaxBytes`` bytes (not including headers), a value that you can
   set in ``configtx.yaml``. Let the value you pick here be ``A`` and make note of
   it —-- it will affect how you configure your Kafka brokers in Step 6.

5. Orderers: **Create the genesis block.** Use ``configtxgen``. The settings you
   picked in Steps 3 and 4 above are system-wide settings, i.e. they apply across the
   network for all the OSNs. Make note of the genesis block's location.

6. Kafka cluster: **Configure your Kafka brokers appropriately.** Ensure that every
#Kafka broker has these keys configured:

   * ``unclean.leader.election.enable = false`` — Data consistency is key in a
     blockchain environment. We cannot have a channel leader chosen outside of
     the in-sync replica set, or we run the risk of overwriting the offsets that
     the previous leader produced, and —as a result— rewrite the blockchain that
     the orderers produce.

       * ``min.insync.replicas = M`` — Where you pick a value ``M`` such that
         ``1 < M < N`` (see ``default.replication.factor`` below). Data is
         considered committed when it is written to at least ``M`` replicas
         (which are then considered in-sync and belong to the in-sync replica
         set, or ISR). In any other case, the write operation returns an error.
         Then:

         * If up to ``N-M`` replicas —out of the ``N`` that the channel data is
           written to become unavailable, operations proceed normally.

         * If more replicas become unavailable, Kafka cannot maintain an ISR set
           of ``M,`` so it stops accepting writes. Reads work without issues.
           The channel becomes writeable again when ``M`` replicas get in-sync.

   * ``default.replication.factor = N`` — Where you pick a value ``N`` such
     that ``N < K``. A replication factor of ``N`` means that each channel will
     have its data replicated to ``N`` brokers. These are the candidates for the
     ISR set of a channel. As we noted in the ``min.insync.replicas section``
     above, not all of these brokers have to be available all the time. ``N``
     should be set *strictly smaller* to ``K`` because channel creations cannot
     go forward if less than ``N`` brokers are up. So if you set ``N = K``, a
     single broker going down means that no new channels can be created on the
     blockchain network — the crash fault tolerance of the ordering service is
     non-existent.

     Based on what we've described above, the minimum allowed values for ``M``
     and ``N`` are 2 and 3 respectively. This configuration allows for the
     creation of new channels to go forward, and for all channels to continue
     to be writeable. #. ``message.max.bytes`` and ``replica.fetch.max.bytes``
     should be set to a value larger than ``A``, the value you picked in
     ``Orderer.AbsoluteMaxBytes`` in Step 4 above. Add some buffer to account
     for headers —-- 1 MiB is more than enough. The following condition applies:

     ::

         Orderer.AbsoluteMaxBytes < replica.fetch.max.bytes <= message.max.bytes

      (For completeness, we note that ``message.max.bytes`` should be strictly
      smaller to ``socket.request.max.bytes`` which is set by default to 100
      MiB. If you wish to have blocks larger than 100 MiB you will need to edit
      the hard-coded value in ``brokerConfig.Producer.MaxMessageBytes`` in
      ``fabric/orderer/kafka/config.go`` and rebuild the binary from source.
      This is not advisable.) #. ``log.retention.ms = -1``. Until the ordering
      service adds support for pruning of the Kafka logs, you should disable
      time-based retention and prevent segments from expiring. (Size-based
      retention —see ``log.retention.bytes``— is disabled by default in Kafka at
      the time of this writing, so there's no need to set it explicitly.)

7. Orderers: **Point each OSN to the genesis block.** Edit
   ``General.GenesisFile`` in ``orderer.yaml`` so that it points to the genesis
   block created in Step 5 above. While at it, ensure all other keys in that YAML
   file are set appropriately.

8. Orderers: **Adjust polling intervals and timeouts.** (Optional step.)

   * The ``Kafka.Retry`` section in the ``orderer.yaml`` file allows you to
     adjust the frequency of the metadata/producer/consumer requests, as well as
     the socket timeouts. (These are all settings you would expect to see in a
     Kafka producer or consumer.)

   * Additionally, when a new channel is created, or when an existing channel is
     reloaded (in case of a just-restarted orderer), the orderer interacts with
     the Kafka cluster in the following ways:

      * It creates a Kafka producer (writer) for the Kafka partition that
        corresponds to the channel. . It uses that producer to post a no-op
        ``CONNECT`` message to that partition. . It creates a Kafka consumer
        (reader) for that partition.

      * If any of these steps fail, you can adjust the frequency with which they
        are repeated. Specifically they will be re-attempted every
        ``Kafka.Retry.ShortInterval`` for a total of ``Kafka.Retry.ShortTotal``,
        and then every ``Kafka.Retry.LongInterval`` for a total of
        ``Kafka.Retry.LongTotal`` until they succeed. Note that the orderer will
        be unable to write to or read from a channel until all of the steps above
        have been completed successfully.

9. **Set up the OSNs and Kafka cluster so that they communicate over SSL.**
   (Optional step, but highly recommended.) Refer to `the Confluent guide <https://docs.confluent.io/2.0.0/kafka/ssl.html>`_
   for the Kafka cluster side of the equation, and set the keys under
   ``Kafka.TLS`` in ``orderer.yaml`` on every OSN accordingly.

10. **Bring up the nodes in the following order: ZooKeeper ensemble, Kafka
    cluster, ordering service nodes.**

Additional considerations
-------------------------

1. **Preferred message size.** In Step 4 above (see `Steps`_ section) you can
#also set the preferred size of blocks by setting the
``Orderer.Batchsize.PreferredMaxBytes`` key. Kafka offers higher throughput
#when dealing with relatively small messages; aim for a value no bigger than 1
#MiB.

2. **Using environment variables to override settings.** When using the
sample Kafka and Zookeeper Docker images provided with Fabric (see
``images/kafka`` and ``images/zookeeper`` respectively), you can override a
Kafka broker or a ZooKeeper server's settings by using environment variables.
Replace the dots of the configuration key with underscores. For example,
``KAFKA_UNCLEAN_LEADER_ELECTION_ENABLE=false`` will allow you to override the
default value of ``unclean.leader.election.enable``. The same applies to the
OSNs for their *local* configuration, i.e. what can be set in ``orderer.yaml``.
For example ``ORDERER_KAFKA_RETRY_SHORTINTERVAL=1s`` allows you to override the
#default value for ``Orderer.Kafka.Retry.ShortInterval``.

Kafka Protocol Version Compatibility
------------------------------------

Fabric uses the `sarama client library <https://github.com/Shopify/sarama>`_ and
vendors a version of it that supports Kafka 0.10 to 1.0, yet is still known to
work with older versions.

Using the ``Kafka.Version`` key in ``orderer.yaml``, you can configure which
version of the Kafka protocol is used to communicate with the Kafka cluster's
brokers. Kafka brokers are backward compatible with older protocol versions.
Because of a Kafka broker's backward compatibility with older protocol versions,
upgrading your Kafka brokers to a new version does not require an update of the
``Kafka.Version`` key value, but the Kafka cluster might suffer a `performance
penalty <https://kafka.apache.org/documentation/#upgrade_11_message_format>`_
while using an older protocol version.

Debugging
---------

Set environment variable ``FABRIC_LOGGING_SPEC`` to ``DEBUG`` and set
``Kafka.Verbose`` to ``true`` in ``orderer.yaml`` .

.. Licensed under Creative Commons Attribution 4.0 International License
https://creativecommons.org/licenses/by/4.0/
