🦀 krafka

A pure-Rust, async-native Apache Kafka client. No librdkafka, no C toolchain, no unsafe, no panics — enforced by the compiler, not by convention. Protocol parity with Apache Kafka 4.3, checked in CI against Kafka's own schemas.

✨ Why krafka

Pure Rust, and it stays that way. No librdkafka, no C toolchain, no cross-compilation surprises. The optional zstd feature is the single exception, and it is opt-in.

The safety posture is enforced by the compiler. unsafe_code = "deny" crate-wide, plus panic, unwrap and expect denied across the whole crate. A malformed broker response cannot panic the process, and every allocation from untrusted input is bounded twice — by the declared count and by the bytes actually available.

Protocol currency is a build failure, not a bug report. Every API version is tracked against Apache Kafka 4.3 — Fetch v18 (KIP-1166), Produce v13, Metadata v13, DescribeLogDirs v5 (KIP-1066), DescribeQuorum v2 (KIP-836/853) — and CI diffs krafka's version table against Kafka's own message schemas. ApiVersions is negotiated rather than pinned, so a 3.9 broker gets 3.9-era versions with no configuration.

Correctness where it is hardest. KIP-320 truncation detection on all three legs — Fetch and ListOffsets and persisted through OffsetCommit, so it survives restarts and rebalances. KIP-447 zombie fencing with a transaction state machine that refuses the KAFKA-17754 abort-after-commit-timeout hazard. OUT_OF_ORDER_SEQUENCE_NUMBER verified head-of-line before any rewind, so a silent gap raises a fatal error instead of reporting success.

Per-partition ordering is structural, not a setting you can get wrong. The producer has exactly one send path, and it keeps exactly one batch per partition on the wire, dispatched in the order batches were sealed. Sequence order and wire order cannot diverge, so there is no max.in.flight.requests.per.connection ≤ 5 rule to remember, a retry cannot reorder a partition, and Arc<Producer> shared across a hundred tasks is simply correct. Different partitions still proceed concurrently.

What is in the box

Clients	Producer — one send path that batches at every linger setting including 0, with compression, idempotence, transactions and tombstones (null keys and values are Option end to end) · Consumer (classic and KIP-848 server-side assignment with validated revoke-before-assign reconciliation) · ShareConsumer (KIP-932 at Kafka 4.2 parity, incl. KIP-1222 Renew and KIP-1206 ShareAcquireMode) · full AdminClient
Security	rustls TLS/mTLS with hot certificate reload (KIP-1288) · SASL PLAIN, SCRAM-SHA-256/512, OAUTHBEARER · built-in OIDC provider for client_credentials (KIP-768) and RFC 7523 client assertions (KIP-1258), with no cryptography dependency added · AWS MSK IAM · every mechanism composes with TLS through one with_tls, asserted reachable over both SASL_PLAINTEXT and SASL_SSL at compile time
Consistency	Every client shares one configuration surface and one operational surface (close, rebootstrap, update_seed_brokers, refresh_tls, metrics) — asserted at compile time, builders included. One builder per client, with build_config() to validate without a broker and build() to validate and connect, both through the same validator. The transactional producer mirrors the plain one setter for setter, minus the two settings transactions fix (acks, idempotent)
Tuning	Per-codec compression levels (Gzip 0–9, Zstd through 22) validated against the selected codec at build time, so a level set on a codec that has none is rejected rather than ignored — on the plain and the transactional producer alike
Transport	One TransportConfig on every builder — pass the same instance to every client that shares a network path: TCP keepalive, response ceiling, in-flight cap, idle eviction, file-descriptor cap · KIP-227 incremental fetch sessions · SOCKS5
Observability	Lock-free counters, gauges and latency histograms with bounded per-topic cardinality · Prometheus export · producer interceptors and dead-letter queues on both producers, over the single send path, with a per-record RecordContext carrying a span or timer from on_send to a terminal callback that fires for every record on_send saw · OAUTHBEARER token-fetch counters and expiry gauge · OpenTelemetry semantic conventions
Hardening	Secret zeroization · constant-time comparison (subtle) · decompression-bomb limits · decode-loop bounds · RFC 3986 path encoding on every outbound HTTP target · CI forbids any credential-bearing type from deriving Debug
Testing	2 350+ tests · 6 cargo-fuzz targets · proptest round-trips across the protocol layer · an in-process fake broker with fault injection that serves the full transaction protocol — KIP-360 fencing, commit/abort markers, read_committed isolation, TV1 and KIP-890 TV2 — so even exactly-once tests need no Docker

Broker versions: krafka requires Apache Kafka 3.9+; protocol versions below that baseline have been removed. Features needing a newer broker (KIP-848 consumer groups, KIP-932 share groups, KIP-1066 cordoned log dirs) say so where they are documented and fail with a clear UnknownApiVersion rather than silently degrading. The Docker integration suite runs against every supported minor in one command (just integration-matrix, Kafka 3.9 → 4.3).

Redpanda works out of the box: every API version is negotiated, and transactions fall back to KIP-890 TV1 automatically (Redpanda has no server-side TV2) — pinned by a dedicated smoke suite (just integration-redpanda). APIs Redpanda does not implement (share groups, log-dir admin) fail fast with UnknownApiVersion, same as against an older Kafka.

🚀 Quick Start

cargo add krafka
cargo add tokio --features full

# For AWS MSK IAM authentication with the full SDK credential chain:
cargo add krafka --features aws-msk

Producer

use krafka::producer::Producer;
use krafka::error::Result;

#[tokio::main]
async fn main() -> Result<()> {
    let producer = Producer::builder()
        .bootstrap_servers("localhost:9092")
        .client_id("my-producer")
        .build()
        .await?;

    // Send a message
    let metadata = producer
        .send("my-topic", Some(b"key"), Some(b"Hello, Kafka!"))
        .await?;

    // A null value is a tombstone: on a compacted topic it deletes the key.
    producer.send("my-topic", Some(b"key"), None).await?;
    
    println!("Sent to partition {} at offset {}", 
             metadata.partition, metadata.offset);

    producer.close().await;
    Ok(())
}

Consumer

use krafka::consumer::{Consumer, AutoOffsetReset};
use krafka::error::Result;
use std::time::Duration;

#[tokio::main]
async fn main() -> Result<()> {
    let consumer = Consumer::builder()
        .bootstrap_servers("localhost:9092")
        .group_id("my-consumer-group")
        .auto_offset_reset(AutoOffsetReset::Earliest)
        .build()
        .await?;

    consumer.subscribe(&["my-topic"]).await?;

    loop {
        let records = consumer.poll(Duration::from_secs(1)).await?;
        for record in records {
            if let Some(ref value) = record.value {
                println!(
                    "Received: topic={}, partition={}, offset={}, value={:?}",
                    record.topic,
                    record.partition,
                    record.offset,
                    String::from_utf8_lossy(value)
                );
            }
        }
    }
}

Admin Client

use krafka::admin::{AdminClient, NewTopic};
use krafka::error::Result;
use std::time::Duration;

#[tokio::main]
async fn main() -> Result<()> {
    let admin = AdminClient::builder()
        .bootstrap_servers("localhost:9092")
        .build()
        .await?;

    // Create a topic
    // `new` validates the topic name, so it returns a Result.
    let topic = NewTopic::new("new-topic", 6, 3)?
        .with_config("retention.ms", "604800000");

    admin.create_topics(vec![topic], Duration::from_secs(30), false).await?;

    // List topics
    let topics = admin.list_topics().await?;
    println!("Topics: {:?}", topics);

    Ok(())
}

Transactional Producer

For exactly-once semantics across multiple partitions:

use krafka::producer::TransactionalProducer;
use krafka::error::Result;

#[tokio::main]
async fn main() -> Result<()> {
    let producer = TransactionalProducer::builder()
        .bootstrap_servers("localhost:9092")
        .transactional_id("my-transaction")
        .build()
        .await?;

    // Initialize transactions (once per producer)
    producer.init_transactions().await?;

    // Atomic transaction
    producer.begin_transaction()?;
    producer.send("topic-a", Some(b"key"), Some(b"value1")).await?;
    producer.send("topic-b", Some(b"key"), Some(b"value2")).await?;
    producer.commit_transaction().await?;

    Ok(())
}

Authentication

Connect to secured Kafka clusters with SASL, SCRAM, OAUTHBEARER, or AWS MSK IAM — available on all client types:

use krafka::producer::Producer;
use krafka::consumer::Consumer;
use krafka::AdminClient;

// Producer with SASL_SSL + SCRAM-SHA-512 (the usual managed-Kafka listener)
use krafka::auth::{AuthConfig, TlsConfig};
let producer = Producer::builder()
    .bootstrap_servers("broker:9093")
    .auth(AuthConfig::sasl_scram_sha512_ssl("username", "password", TlsConfig::new()))
    .build()
    .await?;

// Any mechanism composes with TLS through `with_tls`
let auth = AuthConfig::sasl_scram_sha256("username", "password")
    .with_tls(TlsConfig::new().with_ca_cert("/etc/kafka/ca.pem"));

// Consumer with SASL/PLAIN
let consumer = Consumer::builder()
    .bootstrap_servers("broker:9092")
    .group_id("secure-group")
    .sasl_plain("username", "password")
    .build()
    .await?;

// Producer with SASL/OAUTHBEARER
let producer = Producer::builder()
    .bootstrap_servers("broker:9093")
    .sasl_oauthbearer("your-jwt-token")
    .build()
    .await?;

// Admin with AWS MSK IAM
let auth = AuthConfig::aws_msk_iam("access_key", "secret_key", "us-east-1");
let admin = AdminClient::builder()
    .bootstrap_servers("broker:9094")
    .auth(auth)
    .build()
    .await?;

📦 Modules

Module	Description
producer	Batching, compression, idempotence, transactions, partitioners
consumer	Consumer groups (classic + KIP-848), offsets, rebalancing, compacted-topic tables
share_consumer	KIP-932 share groups — queue semantics on a Kafka topic (share-groups, on by default; needs a Kafka 4.2+ broker)
admin	Cluster administration: topics, partitions, groups, configs, ACLs, quotas, tokens
client	KrafkaClient — one connection pool and metadata cache shared by several clients
auth	SASL PLAIN / SCRAM / OAUTHBEARER / AWS MSK IAM, TLS and mTLS
serdes	Serializer / Deserializer hooks applied on the way to and from the wire
interceptor	Producer and consumer hooks for tracing and enrichment
dlq	Dead-letter queues for records that exhaust their retries
metrics	Lock-free counters, gauges and latency histograms; Prometheus export
telemetry	KIP-714 broker-driven client telemetry and OTLP export (telemetry)
tracing_ext	OpenTelemetry semantic-convention fields for tracing spans
testing	In-process fake broker with fault injection (test-broker)
error	KrafkaError, ErrorCode, ProtocolErrorKind and retriability classification
util	Backoff policy, varint codecs, CRC32C, bootstrap-server parsing
prelude	One glob import for the common types (use krafka::prelude::*)

Three more modules are public but #[doc(hidden)] — protocol, network and metadata. They are reachable for advanced use (custom authenticators, raw record batches, benchmarks) but are not part of the stable API surface.

🗜️ Compression

krafka supports all Kafka compression codecs, individually feature-gated:

use krafka::producer::Producer;
use krafka::protocol::Compression;

let producer = Producer::builder()
    .bootstrap_servers("localhost:9092")
    .compression(Compression::Lz4)  // Fast compression
    .build()
    .await?;

Codec	Cargo Feature	Crate	Characteristics
Compression::Gzip	gzip	flate2	Best ratio, slower
Compression::Snappy	snappy	snap	Good balance
Compression::Lz4	lz4	lz4_flex	Fastest
Compression::Zstd	zstd	zstd	Best modern choice (requires C toolchain)

The default compression feature enables the pure-Rust codecs: gzip, snappy, and LZ4. Zstd remains available through the explicit zstd or compression-all feature because it requires a C toolchain via zstd-sys. To select only what you need:

# Only the codecs you need. `--no-default-features` also drops the default
# `ring` TLS backend, so a crypto backend must be named explicitly.
cargo add krafka --no-default-features --features lz4,snappy,ring

# Or every codec, including zstd:
cargo add krafka --features compression-all

TLS crypto backend

krafka uses rustls and needs exactly one crypto backend. ring is the default; rustls-aws-lc-rs selects aws-lc-rs instead, which is the better choice on AWS Graviton and in FIPS-oriented deployments:

cargo add krafka --no-default-features --features rustls-aws-lc-rs,compression

The two backends are additive, not mutually exclusive — a transitive dependency may well enable the other one, and Cargo would have no way to resolve a conflict if they were exclusive. When both are compiled in, aws-lc-rs deterministically wins. krafka always selects the provider explicitly rather than letting rustls infer it from crate features, so the combination cannot produce a runtime panic. Installing a process-wide provider with CryptoProvider::install_default() overrides the choice for the whole application, krafka included.

🛠️ Development

Tasks are driven by just. The justfile is the single source of truth for what the checks are — CI calls the same recipes, so a check cannot pass locally and fail in CI because the two drifted apart.

just              # list every recipe
just ci           # everything CI runs, except the Docker-backed suites
just ci-full      # ci + supply-chain audit + Docker integration tests
just pre-commit   # the fast subset (fmt, clippy, check)
just install-hooks  # wire pre-commit into .git/hooks
just t <pattern>  # run one test by name, with output

just bench-baseline  # record the performance reference
just bench-check     # fail if the send path regressed >10% since then
just semver-check    # classify API changes against the last published release

Individual recipes mirror one CI job each: fmt-check, clippy, check, protocol-parity, secret-debug, test, test-ring, test-cross-platform, minimal-features, doc, deny, integration, msrv. just ci-job-parity asserts that pairing holds.

bench-check and semver-check sit outside just ci: both are slow and noisy on a shared runner, and pre-1.0 a detected API break is allowed rather than fatal.

Checks that exist because a review found what they now catch

tests/builder_surface.rs — a compile-time assertion that every client builder accepts a TransportConfig, offers a synchronous build_config() alongside the async build(), exposes refresh_tls(), and keeps metrics and version negotiation callable without an async context. Every line fails to compile if the method it names disappears.

It also asserts two matrices that a per-client check could not see. Every SaslMechanism must be constructible under both SASL_PLAINTEXT and SASL_SSL from the public API alone — SASL_SSL + SCRAM, the default secured listener on most managed Kafka offerings, was unreachable from outside the crate because the _ssl constructors were a hand-maintained list and SCRAM was missing from it. And both producer builders must expose the same configuration surface — the transactional one was missing seventeen setters, including the build_config() this file already promised for every client.

This replaced a Python parity script. krafka used to have two builders per client — 72 hand-maintained forwarding methods whose config half nothing outside the crate's own tests ever called — and the script checked that they stayed in sync. It found two real defects, then missed a third: both producer builders had a compression method, but only the unused one validated it, so .compression(Zstd) without the zstd feature built a producer that failed on its first send. A parity check compares surfaces; the divergence had moved underneath it. Deleting the duplication removed both the defect class and the need for the script, and Rust checks reachability better than a regex can.

just protocol-parity — the API version table is diffed against Apache Kafka's own message schemas: names and keys agree, MIN is still a version Kafka accepts, MAX neither overstates (claiming a version marked latestVersionUnstable) nor understates (declining a stable one), and the flexible-version boundary matches. This is how Fetch v17/v18 sat implemented, documented and unreachable for two Kafka releases.

It reads a vendored snapshot, so it needs no network and cannot flake. Track a newer Kafka release deliberately:

just refresh-protocol-snapshot 4.3   # rewrite the snapshot; review the diff
just protocol-parity                 # see what krafka must do about it

just ci-job-parity — every recipe in just ci has a CI job, one required check (ci-success) gates every job, and that check carries if: always().

The justfile being the source of truth has a blind spot: a recipe wired to no workflow is invisible from both sides, because each list is internally complete and neither is compared to the other. just integration-sasl ran in no workflow for its entire life, and just docs-test gated every compiled documentation snippet while no pull request ran it.

if: always() is not cosmetic: GitHub leaves a required check pending forever when its job never runs, and reads a skipped required check as success.

just bench-check — the send path has not regressed more than 10% against the recorded baseline, measured against the in-process fake broker.

These are krafka-vs-krafka numbers. The harness holds a single lock and keeps its log in memory, so no figure it produces is quotable and none appears in this README. It is still the right tool for detecting a regression: a constant overhead cancels when you subtract two runs of it.

just secret-debug — no credential-bearing type may derive Debug. Debug is the quiet way secrets reach a log aggregator: a tracing field, an error context or a panic message that formats the enclosing struct is enough, and nobody has to log the secret deliberately. Two instances shipped before this check existed — the OIDC client secret, and SaslAuthenticateRequest.auth_bytes, which for SASL/PLAIN is \0username\0password in cleartext.

⚡ Performance Tuning

High Throughput Producer

use krafka::producer::{Producer, Acks};
use krafka::protocol::Compression;
use std::time::Duration;

let producer = Producer::builder()
    .bootstrap_servers("localhost:9092")
    .acks(Acks::Leader)
    .compression(Compression::Lz4)
    .batch_size(1048576)                  // 1MB batches
    .linger(Duration::from_millis(10))    // Allow batching
    .build()
    .await?;

Low Latency Consumer

use krafka::consumer::Consumer;
use std::time::Duration;

let consumer = Consumer::builder()
    .bootstrap_servers("localhost:9092")
    .group_id("low-latency")
    .fetch_min_bytes(1)
    .fetch_max_wait(Duration::from_millis(10))
    .build()
    .await?;

Transport tuning

Socket- and pool-level settings live on one TransportConfig, accepted by every builder (Producer, Consumer, AdminClient, TransactionalProducer, ShareConsumer, KrafkaClient). The defaults reproduce krafka's historical behaviour exactly, so this is opt-in.

use krafka::network::TransportConfig;
use krafka::consumer::Consumer;
use std::time::Duration;

let transport = TransportConfig::builder()
    // Beat the idle timeout of whatever NAT gateway or load balancer sits
    // between you and the brokers — the usual cause of "the consumer stops
    // receiving after exactly N minutes".
    .tcp_keepalive(Some(Duration::from_secs(30)))
    // Kafka returns at least one full record batch per partition even when it
    // exceeds fetch.max.bytes. Raise this above the topic's max.message.bytes
    // or that partition stalls permanently.
    .max_response_size(200 * 1024 * 1024)
    // Bound worst-case memory: the per-connection ceiling is
    // max_response_size × max_in_flight_requests.
    .max_in_flight_requests(5)
    // Bound file descriptors on a cluster whose broker count can jump.
    .max_connections(Some(64))
    // Re-read certificates from disk hourly (KIP-1288).
    .tls_reload_interval(Some(Duration::from_secs(3600)))
    .build()?;

let consumer = Consumer::builder()
    .bootstrap_servers("localhost:9092")
    .group_id("tuned")
    .transport(transport)
    .build()
    .await?;

TLS certificate rotation (KIP-1288)

Two paths, because rotation happens two ways:

// Event-driven: an inotify watch or a sidecar signal fired.
producer.refresh_tls().await?;

// Unattended: set `tls_reload_interval` above and krafka reloads on a timer.

Existing TLS sessions keep the certificates they handshaked with and are replaced as connections cycle. A reload that fails — a half-written PEM caught mid-rotation — is logged and the previous material stays active, so a non-atomic rotation converges on the next attempt instead of breaking every new connection in between.

🎯 Delivery Semantics

Pick the mode that matches what your data is worth.

Mode	Guarantee	Cost
acks=0	At-most-once. No durability — the record may never reach the log.	Lowest latency
acks=all + idempotence (default)	At-least-once, ordered and gap-free per partition. Batches for a partition are serialised in seal order; sequence numbers are monotonic and never reused.	One round trip to the ISR
Transactions + send_offsets_to_transaction	Exactly-once across a read-process-write cycle.	Transaction coordinator round trips

Under acks=0, RecordMetadata::confirmation reports Unacknowledged — do not mistake the returned metadata for a durability guarantee.

Exactly-once

send_offsets_to_transaction takes a [ConsumerGroupMetadata], not a bare group ID. That metadata is what lets the group coordinator fence a zombie: an instance that was partitioned away, lost its partitions to a rebalance, and came back still holding a transaction. Without it the coordinator accepts the zombie's commit and it overwrites the position of the member that now owns the partition.

// Re-read for every transaction. The generation changes on every rebalance,
// so a cached value stops fencing at exactly the moment it matters.
let group_metadata = consumer
    .group_metadata()
    .await
    .ok_or("consumer has not joined the group yet")?;

producer.begin_transaction()?;
producer.send("out-topic", Some(b"key"), Some(b"value")).await?;
producer.send_offsets_to_transaction(&offsets, &group_metadata).await?;
producer.commit_transaction().await?;

See examples/exactly_once.rs for the full read-process-write loop.

🧩 Consumer Groups

Both rebalance protocols are supported, but they are no longer equals.

Prefer GroupProtocol::Consumer (KIP-848). It has been production ready since Apache Kafka 4.0: the coordinator computes assignments server-side, a rebalance reconciles incrementally instead of stopping every member, and a slow member affects only its own partitions. Apache Kafka 4.3 began deprecating the classic protocol (KIP-1274 phase 1 — warn in 4.3, default flips in 5.0, removed in 6.0), and krafka logs the same warning once per process when a group starts on it.

use krafka::consumer::{Consumer, GroupProtocol};

let consumer = Consumer::builder()
    .bootstrap_servers("localhost:9092")
    .group_id("my-group")
    .group_protocol(GroupProtocol::Consumer)   // KIP-848
    .build()
    .await?;

Classic remains the default for now, so that upgrading krafka is never itself a protocol migration: krafka supports Kafka 3.9 brokers, and KIP-848 needs 4.0 (or 3.7–3.9 with group.coordinator.new.enable=true). The two protocols cannot mix within one group on pre-4.0 brokers — move every member together, or upgrade the cluster first.

Four assignors ship: Range, RoundRobin, Sticky (eager), and CooperativeSticky. The default is the preference list [Range, CooperativeSticky], matching the Java client — every member advertises both, so a group moves from eager to cooperative rebalancing in a single rolling bounce rather than a full stop-the-world restart.

Cooperative rebalances enforce revoke-before-assign structurally: a partition moving between two live members is withheld from its new owner for one generation — the previous owner revokes it, then the follow-up rebalance delivers it — so two members of one group can never consume the same partition concurrently, and the new owner's committed-offset fetch cannot race the old owner's final commit.

Rebalances do not wait on your poll loop. The background group task keeps heartbeating through a rebalance and sends JoinGroup/SyncGroup itself, so a consumer that is idle or busy between poll() calls does not hold the rest of the group up. The new assignment is applied — and your rebalance listener called — on the next poll(), so callbacks and record delivery stay on one thread and an offset commit cannot race a revocation.

max.poll.interval.ms is still enforced: an application that genuinely stops polling leaves the group so its partitions are reassigned promptly, rather than holding them while a background task vouches for it. Static members (group.instance.id) instead keep their assignment until the session expires, so a restart can reclaim it.

📐 Scope

krafka speaks the client side of the Kafka protocol: 60+ API keys covering produce, fetch, group coordination, transactions, share groups, and administration, tracked against Apache Kafka 4.3.

Broker-internal APIs (LeaderAndIsr, UpdateMetadata, Vote, FetchSnapshot, BrokerHeartbeat, the share-group state persister, …) are deliberately absent — a client does not speak them. They are still named in the ApiKey enum, so an ApiVersions response from a modern broker decodes to something readable rather than Unknown(87).

Not implemented: StreamsGroupHeartbeat (KIP-1071, key 88). Its request carries the Streams application topology, which is group-wide state — a client with no Streams runtime cannot send a truthful one. Its sibling StreamsGroupDescribe (key 89) is implemented, as AdminClient::describe_streams_groups.

Schema registries are out of scope, as they are for every comparable client — Java's kafka-clients has none, librdkafka has none, franz-go keeps pkg/sr out of kgo. A registry is a different service with a different protocol, auth model and release cadence. krafka provides the hook (serdes::Serializer / Deserializer, the equivalent of Java's key.serializer); pair it with schemreg for Confluent, AWS Glue or Apicurio, and Avro / Protobuf / JSON codecs. See the Cookbook.

Tokio is the async runtime.

Authentication

SASL/PLAIN, SASL/SCRAM-SHA-256/512 (with RFC 5929 channel binding), SASL/OAUTHBEARER (with proactive token refresh, a built-in OIDC client_credentials provider and KIP-1258 client assertions behind the oauth-oidc feature), AWS MSK IAM, and mTLS.

GSSAPI/Kerberos is outside the scope of this client.

🧪 Testing Against a Fake Broker

Enable the test-broker feature to get an in-process Kafka broker your tests can drive directly. Real Producer/Consumer/AdminClient instances connect to it over a real TCP socket, so you exercise the actual client — no Docker, no containers, and failure modes you cannot reproduce against a healthy cluster.

use krafka::testing::{Control, FakeBroker};
use krafka::protocol::ApiKey;
use krafka::error::ErrorCode;

let broker = FakeBroker::start().await?;

// Make the next CreateTopics land on a non-controller and assert the client
// refreshes metadata and retries instead of surfacing the error.
broker.on(ApiKey::CreateTopics, |_| Control::Error(ErrorCode::NotController));

let admin = AdminClient::builder()
    .bootstrap_servers(broker.bootstrap_servers())
    .build()
    .await?;

Control covers Error, Delay, DelayThen, Disconnect, Silence, CorruptRecords and pass-through. The cluster is mutable mid-test (set_leader, bump_leader_epoch, set_group_coordinator, set_controller, set_broker_online), and set_api_versions makes the broker advertise an older API range so the client's degradation branches are reachable.

It serves the produce/fetch path, both group protocols — classic and KIP-848 with real revoke-before-assign reconciliation — DescribeGroups and StreamsGroupDescribe, KIP-932 share groups with the share-partition state machine, KIP-584 feature administration, and the full transaction protocol.

Transactions are modelled end to end, which is what makes exactly-once testable without a cluster: InitProducerId returns a stable producer ID per transactional ID with an epoch that rises on every re-initialisation (KIP-360 fencing), EndTxn writes real commit and abort control batches, offsets staged by TxnOffsetCommit apply only on commit, and a read_committed fetch stops at the last stable offset and reports aborted transactions so the consumer's own filtering runs for real. set_transaction_version(2) finalizes the transaction.version feature and the client negotiates KIP-890 TV2 from it — the same route a real cluster takes — so both protocols are reachable.

broker.set_transaction_version(2);
// ...run a transaction through a TransactionalProducer...
assert_eq!(broker.request_count(ApiKey::AddPartitionsToTxn), 0);

See the Testing guide for what it does and, just as importantly, what it deliberately does not model.

⬆️ Upgrading

krafka is pre-1.0: a minor bump may carry breaking changes, and every one is listed in the Breaking section of that release in CHANGELOG.md.

📚 Documentation

Full documentation: hupe1980.github.io/krafka · API reference: docs.rs/krafka · Release history: CHANGELOG.md

Start here	Clients	Integration	Operations	Reference
Getting Started	Producer	Authentication	Metrics	Protocol Support
Cookbook	Consumer		Performance	Architecture
Configuration	Share Consumer	Interceptors	Testing
	Admin Client		Error Handling

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🎮 Examples

Run the examples with:

# Producer example
cargo run --example producer

# Consumer example
cargo run --example consumer

# Advanced consumer example (pause/resume, seek, manual commits)
cargo run --example consumer_advanced

# Admin client example
cargo run --example admin

# Transactional producer example
cargo run --example transactional_producer

# Exactly-once read-process-write (KIP-447 zombie fencing)
cargo run --example exactly_once

# Authentication examples (SASL, SCRAM, MSK IAM)
cargo run --example authentication

🤝 Contributing

Contributions are welcome!

📄 License

Licensed under either the MIT License or the Apache License 2.0, at your option.