Defines a consumer group.

A consumer group coordinates the consumption of one or more topics across a set of cooperating member processes. Klife implements the new KIP-848 rebalance protocol introduced in Kafka 4.0, so partition assignment, heartbeats, and rebalances are handled by the broker coordinator and do not require any user-managed state machine.

Each use Klife.Consumer.ConsumerGroup defines one consumer group module. The module is started under your supervision tree and, once running, the broker coordinator assigns it topic-partitions. For each assigned partition, the group starts a dedicated consumer process that fetches records and delivers them to your handle_record_batch/4 callback.

Defining a consumer group

defmodule MyApp.MyConsumerGroup do
  use Klife.Consumer.ConsumerGroup,
    client: MyApp.MyClient,
    group_name: "my_group_name",
    topics: [
      [name: "my_topic_1"],
      [name: "my_topic_2"]
    ]

  @impl true
  def handle_record_batch(_topic, _partition, _group_name, records) do
    Enum.each(records, &IO.inspect(&1.value))
    :commit
  end
end

All options passed to use are merged with the options passed to start_link/1, with start_link/1 arguments taking precedence. This allows the most common configuration to live alongside the module definition while still enabling per-instance overrides at startup time.

Configuration options

• :client (atom/0) - Required. The name of the klife client to be used by the consumer group

• :topics (List of Klife.Consumer.ConsumerGroup.TopicConfig configurations) - Required. List of topic configurations that will be handled by the consumer group

• :group_name (String.t/0) - Required. Name of the consumer group

• :instance_id (String.t/0) - Value to identify the consumer across restarts (static membership). See KIP-345

• :rebalance_timeout_ms (non_neg_integer/0) - The maximum time in milliseconds that the kafka broker coordinator will wait on the member to revoke it's partitions The default value is 30000.

• :fetch_strategy ({:exclusive, fetcher_options} or {:shared, fetcher_name}) - Defines which Klife.Consumer.Fetcher is used by topics in this group that do not override the strategy in their own Klife.Consumer.ConsumerGroup.TopicConfig.

  • {:exclusive, fetcher_options}: starts a new fetcher dedicated to this group. fetcher_options follows Klife.Consumer.Fetcher configuration (:name is managed automatically and cannot be set here).
  • {:shared, fetcher_name}: reuses an existing fetcher (one already started by the client). All topics that do not override their strategy share it.

  Defaults to {:shared, <client default fetcher>}.

• :committers_count (pos_integer/0) - How many committer processes will be started for the consumer group The default value is 1.

• :default_topic_config (keyword/0) - Klife.Consumer.ConsumerGroup.TopicConfig that will serve as default for every topic on the group that does not explicitly set it. The default value is [].

  • :fetch_strategy ({:exclusive, fetcher_options} or {:shared, fetcher_name}) - Overrides the fetch strategy defined at the consumer group level for this topic.

    The override semantics differ slightly from the group-level option:

    • {:exclusive, fetcher_options}: starts a new fetcher dedicated to this single topic (not shared with other topics in the group).
    • {:shared, fetcher_name}: uses the given pre-existing fetcher only for this topic.

    If not set, the topic uses the fetcher selected by the consumer group's :fetch_strategy.

  • :isolation_level - May override the isolation level defined on the consumer group The default value is :read_committed.

  • :offset_reset_policy - Define from which offset the consumer will start processing records when no previous committed offset is found. The default value is :latest.

  • :fetch_max_bytes (non_neg_integer/0) - The maximum amount of bytes to fetch in a single request. Must be lower than fetcher config max_bytes_per_request. The default value is 1000000.

  • :max_queue_size (non_neg_integer/0) - The maximum number of record batches that the consumer can keep on its internal queue. Defaults to 5 if :handler_max_batch_size is :dynamic, otherwise defaults to 20.

  • :fetch_interval_ms (non_neg_integer/0) - Time in milliseconds that the consumer will wait before trying to fetch new data from the broker after it runs out of records to process.

    The consumer always tries to optimize fetch requests wait times by issuing requests before it's internal queue is empty (the current threshold is 1 batch). Therefore this option is only used for the wait time after a fetch request returns empty.

    The default value is 1000.

  • :handler_cooldown_ms (non_neg_integer/0) - Time in milliseconds that the consumer will wait before handling new records. Can be overrided for one cycle by the handler return value. The default value is 0.

  • :handler_max_unacked_commits (non_neg_integer/0) - Controls how many records can be waiting for commit confirmation before the consumer stops processing new records.

    When this limit is reached, processing pauses until confirmations are received.

    Set it to 0 to process records one batch at a time so each processing cycle must be fully committed before starting the next.

    The default value is 0.

  • :handler_max_batch_size - The maximum amount of records that will be delivered to the handler in each processing cycle. If :dynamic all records retrieved in the fetch request will be delivered as one single batch to the handler. If positive integer, retrieved records will be chunked into the provided size. The default value is :dynamic.

Topic configuration

Each entry of :topics is a Klife.Consumer.ConsumerGroup.TopicConfig. The group's :default_topic_config provides defaults applied to every topic that does not explicitly override them:

use Klife.Consumer.ConsumerGroup,
  client: MyApp.MyClient,
  group_name: "my_group",
  default_topic_config: [
    handler_max_unacked_commits: 100,
    offset_reset_policy: :earliest
  ],
  topics: [
    [name: "topic_a"],
    [name: "topic_b", offset_reset_policy: :latest]
  ]

Above, topic_a inherits both defaults, while topic_b overrides :offset_reset_policy and inherits :handler_max_unacked_commits.

Delivery semantics

Klife provides at-least-once delivery: every record is guaranteed to be delivered to handle_record_batch/4 at least once, but may be delivered more than once after a hard failure (member crash, network split, liveness timeout). Handlers must be idempotent to tolerate duplicates.

Graceful partition revocation does not cause reprocessing: the consumer waits for every in-flight record to be committed before releasing the partition. Reprocessing only occurs when the consumer is unable to commit before losing the assignment.

The window of records exposed to reprocessing is bounded by :handler_max_unacked_commits (a TopicConfig option):

• 0 (default): each batch must be fully committed before the next is delivered. Reprocessing on failure is limited to the records of the most recent in-flight batch.
• N > 0: up to N processed records may be waiting for commit at any time. This unlocks commit pipelining and higher throughput, but on a hard failure those records may be redelivered.

Retrying records

Klife's per-record :commit/:retry control on handle_record_batch/4 is more granular than what Kafka itself tracks: Kafka stores a single committed offset per partition for each consumer group, and on resume the consumer always picks up from there.

This gap leaves room for a misuse pattern where a batch returns :commit for a record and :retry for one with a lower offset in the same partition. For example, committing record 2 while asking record 1 to be retried. While the consumer is running, Klife keeps 1 in its in-process queue and re-delivers it on the next cycle. But if the consumer restarts or the partition is revoked before 1 is committed, the broker only knows about the commit of 2: the retry queue is lost and 1 would be silently skipped. To prevent this, Klife detects the pattern and raises.

To stay aligned with Kafka semantics, never retry a record whose offset is lower than any record committed in the same batch. When a record fails, choose one of:

• Retry the failing record together with every successful record after it, accepting that the successful ones will be reprocessed once the failing one eventually succeeds.
• Commit the failing record and route it elsewhere (e.g. a dead-letter topic) so processing can move forward.

Fetch strategies

Every partition consumer fetches records through a Klife.Consumer.Fetcher, and which fetcher serves a topic is decided in two layers: the consumer group's :fetch_strategy sets a default for all its topics, and any TopicConfig can override that default for itself.

The same two strategies, {:shared, fetcher_name} and {:exclusive, fetcher_options}, are accepted at both levels, but the scope of :exclusive differs:

• {:exclusive, opts} at the group level starts one new fetcher dedicated to the consumer group. Every topic that does not override the strategy shares it.
• {:exclusive, opts} at the topic level starts one new fetcher dedicated to that single topic, not shared with anything else.

{:shared, fetcher_name} behaves identically at both levels: it reuses an existing fetcher (one already started by the client) for whatever scope it is set on.

When the group's :fetch_strategy is unset, it falls back to {:shared, <client default fetcher>}, so topics in the group share the client's default fetcher with every other consumer of it.

Override at the group level when the entire group needs an isolated fetch pipeline (e.g. its own batchers or max_bytes_per_request). Override at the topic level when a single noisy or latency-sensitive topic should not share its fetcher with the rest of the group.

How many committers?

Offset commits are dispatched by dedicated committer processes shared across the partitions of the group. A single committer is enough for most workloads.

Before raising :committers_count, check whether the apparent bottleneck is committer dispatch or simply commit RTT pacing the handler, see Tuning for throughput. Raising :handler_max_unacked_commits decouples handler cadence from commit latency and resolves most apparent "commit bottleneck" symptoms without adding parallelism.

Increase :committers_count only when the committer process itself can't keep up, typically a group with many actively committing partitions where profiling shows the committer as the bottleneck. This comes at the cost of per-commit batching efficiency, since partitions are split across committers.