Apache Spark Consulting Services

Deep Spark Streaming Expertise

Our data streaming engineers have designed and operated Apache Spark Structured Streaming platforms processing billions of events per day. We understand Spark internals — catalyst optimizer, shuffle management, state store backends, and micro-batch vs. continuous processing — not just the API surface.

Spark on Kubernetes

We specialize in deploying Apache Spark on Kubernetes — including the Spark Operator, dynamic resource allocation, spot instance strategies, and production-grade cluster management. Our Spark consulting services cover containerized deployments with full operational tooling for both streaming and batch workloads.

Spark for Regulated Industries

Banking, insurance, healthcare, and energy — we’ve deployed Spark in environments where data sovereignty, auditability, and compliance are non-negotiable. Our consulting approach is designed for enterprises with strict governance requirements.

Spark Streaming Performance Optimization

We optimize Spark Structured Streaming deployments for throughput, latency, and cost. Trigger intervals, state store tuning, watermark strategies, and shuffle optimization are architectural decisions — not afterthoughts.

Kafka + Spark Streaming Integration

Apache Kafka and Apache Spark are the backbone of many enterprise streaming platforms. Our Kafka developers and Spark engineers design end-to-end Kafka-Spark architectures with exactly-once semantics, schema governance, and CDC integration.

Spark-to-Flink Migration Advisory

Not every streaming workload belongs on Spark. We help you evaluate when Apache Flink is the better fit — and execute the migration when it makes sense. As experts in both Spark and Flink, we give you honest, technology-agnostic advice.

Consulting & Architecture

Expert Spark consulting on an hourly or project basis. Architecture assessments, proof-of-concept builds, migration planning, and streaming performance reviews.

• Architecture design & review
• Proof of concept development
• Batch-to-streaming migration planning
• Performance assessment & tuning
• Best-effort or SLA-based support & maintenance

Team Extension & On-Site Engineering

Embed our senior Spark engineers and Kafka developers directly in your project team. They work in your repositories, your processes, your standups — and bring years of hands-on production experience from enterprise Spark and streaming deployments across Europe. Not a body shop — our people come with deep platform knowledge built across dozens of deployments in regulated industries.

• Senior data streaming engineers with Spark & Kafka expertise
• On-site, remote, or hybrid — fully integrated in your workflows
• Long-term or project-based engagements
• Your codebase, your deadlines, our experience

24/7 Managed Spark Operations

Full operational ownership of your Spark platform with 24/7 monitoring, incident response, and proactive maintenance. We run your Spark infrastructure with defined SLAs — on Kubernetes, on-premises, in the cloud, or hybrid.

• 24/7 monitoring & alerting
• Guaranteed response times (4h / 8h / next business day)
• Capacity planning & autoscaling
• Proactive health checks & hardening
• Defined escalation paths & on-call rotation

Spark Architecture, Platform Design & Review

We design Spark platforms as shared infrastructure — multi-tenant, observable, and evolvable — and review existing architectures before they go to production. Whether you need a greenfield design or a second opinion on your current setup, we cover resource management, job scheduling, state store selection, and integration with your existing data platform.

Spark Structured Streaming Development

Our Spark developers build production-grade streaming applications using the Structured Streaming API. Windowed aggregations, stateful operations, stream-stream joins, and CDC pipelines — designed for correctness and low latency under real-world conditions.

Spark to Flink Migration

When streaming workloads outgrow Spark — when you need true event-at-a-time processing, large managed state, or sub-second latency — we migrate your pipelines to Apache Flink. As experts in both frameworks, we handle semantic equivalence testing, state migration, and gradual cutover strategies. No other Spark consulting firm offers this.

Spark Streaming Performance Engineering

Trigger interval tuning, state store optimization, shuffle reduction, and memory management. We diagnose and resolve performance issues in existing Spark Structured Streaming deployments — turning unstable micro-batch jobs into reliable, low-latency pipelines.

Spark on Kubernetes

Production-grade Spark on Kubernetes and OpenShift. Our consulting covers Spark Operator configuration, dynamic resource allocation, namespace isolation, GitOps workflows, and cost-optimized cluster design for containerized streaming and batch workloads.

Batch-to-Streaming Migration

Modernize legacy Spark batch pipelines into Spark Structured Streaming applications. We design incremental migration paths that let you move to real-time processing without rewriting everything at once — maintaining data consistency throughout the transition.