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Streaming Data Platform Services for Enterprise

Build an enterprise streaming platform that survives the third use case.

Logiciel builds and operates streaming data platforms for large enterprises. Kafka, Confluent, MSK, Kinesis, Pub/Sub and Flink, packaged with schema management, exactly-once semantics, governance and on-call. We work alongside data platform, integration and product teams to make real-time data a stable foundation for analytics, AI and operations.

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Why Enterprise Streaming Platforms Get Stuck

Most enterprise streaming platforms work for the first use case and stall on the third.

  • The first team picks a stack that does not fit the next teams.
  • Schema management is informal, so consumers break with every producer change.
  • Exactly-once semantics are assumed, not designed.
  • There is no shared platform layer, so each team builds their own ops practice.
  • Costs grow quickly without a streaming-specific FinOps practice.
  • The platform reports problems but nobody actually responds.

What You Get When You Work With Logiciel on Enterprise Streaming

We give enterprise data platform teams a streaming platform they can offer as a service.

  • A reference streaming architecture that fits enterprise scale and operating reality.
  • Schema management with a registry and contracts, not informal coordination.
  • Exactly-once and idempotency patterns designed at the architecture level.
  • A platform layer with shared components for producers, consumers, observability and governance.
  • A FinOps practice tied to teams and use cases.
  • A managed operating layer with monitoring, on-call and incident response.

Enterprise Streaming Platform Solutions Built for Production

We cover the streaming platform areas that recur in large enterprises.

Kafka and Confluent Platform Engineering

Self-managed Kafka, Confluent Platform and Confluent Cloud implementations with shared platform components.

AWS MSK and Azure Event Hubs

MSK, Azure Event Hubs, Google Pub/Sub and equivalent managed streaming platforms.

Kinesis and Cloud-Native Streaming

Kinesis Data Streams, Kinesis Firehose and equivalent cloud-native streaming patterns.

Flink and Stream Processing

Apache Flink, Kinesis Data Analytics, ksqlDB and Spark Structured Streaming for stream processing.

Schema Management and Contracts

Schema registry implementation, contract testing and version management.

Change Data Capture

CDC pipelines from operational systems using Debezium, Fivetran, AWS DMS and similar tools.

Streaming Platform Governance

Governance, access control, lineage and audit for streaming data platforms.

Streaming Observability and On-Call

Monitoring, observability and on-call for streaming platforms with KPIs tied to business impact.

Engagement Models Designed for Streaming Data Platform Services for Enterprise Delivery

Dedicated Streaming Platform Squad

A long-running team of streaming platform engineers, data engineers and reliability engineers embedded in your data platform function.

Streaming Platform Advisory and Staff Augmentation

Senior streaming platform engineers who reinforce your in-house team during specific phases.

Outcome-Based Streaming Engagements

Fixed-scope engagements, for example a Kafka platform build, a CDC rollout or a Flink streaming application.

Enterprise Streaming Platform Services We Deliver

Streaming Platform Strategy and Architecture

Reference architectures, maturity assessments and multi-year roadmaps for enterprise streaming platforms.

Kafka and Confluent Platform Engineering

Self-managed Kafka, Confluent Platform and Confluent Cloud implementations.

MSK, Event Hubs and Pub/Sub Implementation

Managed streaming platform implementations on AWS, Azure and Google Cloud.

Stream Processing with Flink and ksqlDB

Apache Flink, Kinesis Data Analytics, ksqlDB and Spark Structured Streaming for stream processing.

Schema Management and Data Contracts

Schema registry implementation, contract testing and version management.

Change Data Capture Implementation

CDC pipelines from operational systems using Debezium, Fivetran, AWS DMS and similar tools

Streaming Platform Governance

Governance, access control, lineage and audit for streaming data platforms.

Streaming Observability and On-Call

Monitoring, observability and on-call for streaming platforms with KPIs tied to business impact.

Streaming Data Platform Services for Enterprise Insights & Frameworks

Patterns from our delivery teams that have run through real enterprise streaming deployments.

Enterprise Streaming Platform Reference Architecture

A reference architecture for enterprise streaming platforms covering producers, consumers, schema, processing, governance and observability.

Data Contract and Schema Pattern for Streaming

A practical pattern for schema management and data contracts across enterprise streaming platforms.

Our Streaming Data Platform Services for Enterprise Framework

1. Discovery and Streaming Assessment

We assess current streaming use, target use cases, integration points and operating practice.

2. Reference Architecture and Operating Model

We design the streaming architecture, schema strategy, platform layer and operating model.

3. Platform Build

We build the platform layer in code, with shared components, observability and governance.

4. Use Case Onboarding

We onboard the first producers, consumers and stream processing applications with SLAs and contracts.

5. Operate and Improve

We move into a steady-state operating model with monitoring, on-call and continuous improvement.

Accelerate Streaming Data Platform Services for Enterprise

Ready to put Streaming Data Platform Services for Enterprise on production-software footing? Partner with Logiciel to design, build and operate Streaming Data Platform Services for Enterprise that engineering, security and business teams can all defend.

Plan your enterprise streaming platform

Frequently Asked Questions

We cover strategy, architecture, build, deployment and operations for Streaming Data Platform Services for Enterprise, aligned with your business priorities and operating constraints.

Most engagements reach a working pilot within 4-8 weeks, while larger rollouts run across phased waves over several months.

Yes. We integrate with cloud platforms, CRMs, ERPs, EHR, OT systems, analytics tools and other operational infrastructure depending on the use case.

Yes. We offer milestone-based pricing once scope, KPIs and delivery requirements are agreed.

You retain ownership of all workflows, integrations, prompts, infrastructure, systems and implementation assets.

We implement governance frameworks, observability, access controls, audit trails and compliance-aligned deployment practices.

We tune infrastructure, automate resource management, optimise deployment workflows and report operational cost back to teams and product lines.

Yes. We run managed operations with SRE, observability, on-call and continuous improvement.