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Integration, APIs & event streaming / Confluent

Confluent & Apache Kafka Put event streams to work across the business.

Pragma Edge’s StreamX approach connects Confluent and Apache Kafka event streaming to real-time integration, application modernization and operational visibility.

THE NEXT CHAPTER / Confluent & Apache Kafka

Real-time is valuable when the event can be trusted.

Applications and AI workflows need timely context, but a faster pipeline does not resolve incompatible schemas, missing ownership or unclear replay behavior. Event-driven modernization needs to address the lifecycle of the data as well as its movement.

WHERE PRAGMA EDGE FITS

Connect the platform to the work.

Pragma Edge connects streaming design to operational use cases: order status, inventory changes, integration exceptions and asset signals. We scope event contracts, producers, consumers, recovery and the signals that show whether the flow is healthy.

WHAT PROGRESS LOOKS LIKE

Build the next step around evidence.

The result to work toward is an event foundation that teams can evolve safely. New consumers understand the contract, operations can identify lag, and recovery does not rely on blindly replaying business actions.

WHERE CONFLUENT & APACHE KAFKA FITS

The Confluent & Apache Kafka work behind the business outcome.

Pragma Edge’s StreamX positioning brings streaming into the connected enterprise. The useful unit of design is a complete event journey: producer, data contract, processing and consumer outcome. Establish ordering, retention and recovery requirements before scaling a stream.

Our Confluent & Apache Kafka services.

01

Event architecture & Kafka integration

Design topics, event contracts, producers and consumers around business events. Connect enterprise applications and source systems to the streaming architecture.

02

Data pipelines & stream processing

Build agreed ingestion and transformation paths, including change-data-capture use cases where applicable. Define schema evolution, replay and duplicate-handling rules.

03

Streaming operations & governance

Monitor lag, throughput, failures and downstream dependencies. Align topic access, retention and recovery procedures with the business use case.

PRAGMA EDGE / EXPERTISE IN ACTION

Build trusted event streams that applications and AI can use.

Where our specialists go deeper

Design event contracts, topic ownership, partition strategy and consumer behavior. Scope connectors, schema compatibility, replay, dead-letter handling and lineage for operational use cases.

Define success before delivery.

Baseline the measures relevant to your engagement, then compare results through implementation and operation.

Event freshness
consumer lag
schema failures
replay recovery
cost per workload
ILLUSTRATIVE USE CASE

Confluent & Apache Kafka in a business workflow.

An inventory change needs to update commerce, fulfillment and analytics. Publish the event once, govern its contract and monitor each consumer’s progress independently.

START YOUR ENGAGEMENT

Scope the Confluent & Apache Kafka work with our team.

Your current platform, version and deployment model
One representative workflow and its exceptions
The systems, teams and business commitments involved
The decision or improvement you want to make
Plan the next conversation →
CONNECTED EXPERTISE

Explore the adjacent work.

Move from the platform question to the product or service that supports your workflow.

Event Management & StreamingApplication IntegrationIANN MonitorIANN FileGPSAll supported technologies
PRAGMA EDGE / LET’S CONNECT

Start a conversation.

Tell us what you’re working on. We’ll help shape the next step.

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