Pakistan

Apache Kafka Integration

Kafka solves a specific scale problem

Kafka earns its operational complexity once you have multiple services that need to reliably pass a real volume of events between them, with the ability to replay history and handle multiple consumers reading the same stream independently. For simpler needs - a handful of services with modest message volume - a simpler message queue is often the more honest recommendation, and we'll say so before proposing Kafka just because it's a well-known name.

What we build

Kafka cluster setup and topic design, structured around your actual event types and consumer patterns
Producer/consumer integration into your existing services, with proper error handling and retry logic
Schema management for event payloads, so producers and consumers stay compatible as the system evolves
Monitoring for consumer lag and cluster health, so problems surface as alerts rather than silent processing delays

Our process

1. Confirm Kafka is the right tool

Based on your real event volume and number of services - if a simpler queue (or no queue at all) would serve you better, we say so directly.

2. Design topics and schemas

Matched to your actual event types, not a generic template that doesn't reflect your domain.

3. Build and test integration

Producer/consumer code tested against realistic throughput and failure scenarios (a consumer going down, a burst of events) before production.

4. Set up monitoring

Consumer lag and cluster health visibility from day one, not added after the first unnoticed processing delay.

Pricing

Rs 150,000-600,000 depending on number of topics/services and whether this is a managed cloud Kafka service or self-hosted cluster setup.

API Development · MLOps Pipeline · All services

Frequently asked questions

Do we actually need Kafka, or would a simpler queue work?

Depends on your real event volume and number of services - Kafka earns its complexity at genuine scale with multiple independent consumers. For simpler needs, we'll recommend a lighter message queue instead rather than propose Kafka by default.

Managed cloud Kafka or self-hosted?

Depends on your team's operational capacity and existing infrastructure - managed services reduce operational burden at a higher direct cost; self-hosting is cheaper at scale but needs real ops capacity.

How do you handle schema changes over time?

Schema management is built in from the start so producers and consumers stay compatible as your event structures evolve, rather than breaking silently on a change.

What happens if a consumer falls behind?

Consumer lag monitoring is set up from day one, surfacing as an alert rather than a silent processing delay you discover later.

Can this integrate with our existing services?

Yes - producer/consumer integration is built into your existing service codebase with proper error handling and retry logic.

What does it cost?

Rs 150,000-600,000 depending on scope and whether it's managed or self-hosted.

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