✦ Fine-tuned Qwen3-32B · 10/10 quality score

Enterprise Kafka expertise,
available via API

Ask any Kafka question. Get production-grounded answers covering consumer groups, rebalancing, lag monitoring, Schema Registry, security, Kubernetes deployment, and multi-region replication.

25
Years enterprise Kafka delivery
10/10
Quality test score
1,610
Expert Q&A training examples
<2s
Average response time

Every layer of the Kafka stack

From producer tuning to multi-region DR — grounded in real enterprise patterns, not documentation summaries.

Producer & Consumer Tuning

linger.ms, batch.size, buffer.memory, max.poll.interval.ms, fetch latency, JMX metrics.

🔄

Consumer Group Rebalancing

EAGER vs COOPERATIVE protocols, static membership, session timeout vs poll interval, JMX diagnostics.

📊

Lag Monitoring & Alerting

records-lag-max, kafka_consumergroup_lag, Prometheus alert rules, catch-up strategies.

🔗

Schema Registry & Avro

Compatibility modes (BACKWARD/FORWARD/FULL), schema evolution, data contracts, CEL rules.

🔒

Security

SASL/OAUTHBEARER, SCRAM-SHA-512, mTLS, ACLs, RBAC, Confluent Platform Secrets Management.

🌍

Multi-Region Replication

MirrorMaker 2 vs Cluster Linking, RPO/RTO trade-offs, active-active setup, offset translation.

☸️

Kafka on Kubernetes

Confluent for Kubernetes (CFK), operator patterns, resource sizing, rolling upgrades, DR.

🔌

Kafka Connect

JDBC, HTTP, Elasticsearch, Azure, PubSub connectors. Sizing tasks.max, poll intervals, error handling.

One endpoint. Any Kafka question.

Standard OpenAI-compatible chat API — works with any HTTP client or SDK.

curl
Python
Response
curl -sS -X POST https://api.kafkaexpert.ai/chat \
  -H "Authorization: Bearer sk-kafka-expert-YOUR-KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [{
      "role": "user",
      "content": "A consumer group is rebalancing every 5 minutes. What is causing it and how do I fix it?"
    }]
  }'
import openai

client = openai.OpenAI(
    api_key="sk-kafka-expert-YOUR-KEY",
    base_url="https://api.kafkaexpert.ai"
)

response = client.chat.completions.create(
    model="kafka-expert",
    messages=[{
        "role": "user",
        "content": "What JMX metrics indicate a Kafka producer is hitting buffer.memory limits?"
    }]
)
print(response.choices[0].message.content)
// Response to: "A consumer group is rebalancing every 5 minutes. What is causing it?"

"A rebalance every 5 minutes exactly is the signature of max.poll.interval.ms=300000
(the default) being exceeded. When the consumer's processing loop takes longer
than 300,000ms between consecutive poll() calls, the client proactively sends
LeaveGroup and triggers a rebalance.

Diagnosis: search consumer logs for:
  Max poll interval (300000ms) exceeded by ... ms — revoking assignment

Fix options:
1. Reduce max.poll.records (default 500 → try 50):
   max.poll.records=50

2. Increase max.poll.interval.ms if processing legitimately takes longer:
   max.poll.interval.ms=600000

3. Move slow processing to an async thread — keep poll() on the main thread.

This is entirely a processing-speed issue. It is not related to network
connectivity, broker availability, or session.timeout.ms (which is controlled
by the background heartbeat thread)."

Simple, transparent pricing

7-day free trial on all paid plans. Cancel any time.

Trial
Free
7 days, no card required
  • 100 API calls
  • 100,000 tokens
  • All Kafka topics covered
  • Priority support
  • Usage analytics
Request trial key
Starter
£100 / mo
For individual engineers & small teams
  • 1,000 API calls / month
  • 1,000,000 tokens / month
  • All Kafka topics covered
  • Email support
  • Usage analytics dashboard

Need higher volume or a custom SLA? Get in touch →

Built on 25 years of enterprise Kafka delivery across retail, financial services, and classified platforms at Accenture and CapGemini.
Fine-tuned on real production runbooks, JMX dashboards, and architecture reviews — not documentation summaries.

Common questions

Is this OpenAI-compatible?

Yes. The API follows the OpenAI chat completions format — set base_url to https://api.kafka-expert.com and model to kafka-expert. Any client that supports OpenAI works: Python openai SDK, JavaScript, curl, LangChain, etc.

What model is this based on?

Kafka Expert is a LoRA adapter fine-tuned on top of Qwen3-32B (NVFP4), running on a dedicated NVIDIA GB10 GPU. Thinking mode is disabled — answers are direct and production-focused, not verbose chain-of-thought.

What Kafka topics does it cover?

The model is trained on 1,610 expert Q&A examples covering: producer/consumer configuration and tuning, consumer group rebalancing, lag monitoring and alerting, Schema Registry (Avro, JSON Schema, Protobuf), Kafka Connect, MirrorMaker 2, Confluent Cluster Linking, SASL/OAUTHBEARER security, Confluent for Kubernetes (CFK), and multi-region replication patterns.

How do I get my API key?

Subscribe above — you'll receive your API key by email within a few minutes. For trial access, click "Request trial key" and you'll get a key valid for 7 days with 100,000 tokens.

What happens when I hit my monthly limit?

You'll receive an email warning at 80% usage. At 100%, requests return a 429 with a clear error message. You can upgrade your plan at any time to increase your quota — contact [email protected].

Can I use this for CI pipelines or internal tooling?

Absolutely — the API key is a standard Bearer token you can set as a CI environment variable. The Pro tier (5,000 calls/month) is sized for team use in Slack bots, internal knowledge bases, and automated code review tools.