Engineered for scale. Designed for reliability. Proven under real-world load.
We design backend systems that handle massive traffic, real-time processing, and enterprise-level complexity — without breaking, slowing down, or needing to be rewritten. Our architectures power fintech, telecom, SaaS, marketplaces, analytics platforms, and products where stability and performance are mission-critical.
High-load, fault-tolerant, and scalable backend systems:
We work with companies that cannot afford downtime, delays, or instability:
Systems built for millions of users and extreme concurrency.
Processing events in milliseconds.
Clean engineering, predictable behavior.
Built for speed, consistency, and massive data volumes.
Architectures designed for long-term growth — not short-term patches.
Optimized pipelines that stay fast at peak hours.
Failover, auto-recovery, and observability built into the core.
Avoid technical debt that slows teams down.
Containers, orchestration, monitoring, and automation pre-configured.
Enterprise-proven tools we use daily:
We design and operate high-load systems used in:
We combine event-driven architecture, Apache Kafka for high-throughput message streaming, horizontally scalable microservices, and optimized database layers. Systems are designed with CQRS patterns, outbox patterns for consistency, and careful partitioning to distribute load across multiple nodes. Load testing validates performance before production deployment.
With proper architecture, Kafka pipelines can achieve end-to-end latency under 10ms for most use cases. We optimize consumer groups, use Kafka Streams for stateful processing, implement efficient serialization, and minimize network hops. For ultra-low latency requirements, we use in-memory processing with Redis and direct database connections.
We implement circuit breakers, rate limiting, graceful degradation, and backpressure handling at multiple layers. Kafka consumer groups are configured with appropriate fetch sizes and processing rates. Downstream services use queues and buffering to handle spikes. Monitoring and alerting catch issues before they cascade.
We design stateless services that can scale horizontally, use connection pooling, implement caching layers (Redis), optimize database queries, and use load balancers. Kubernetes autoscaling adjusts pod count based on CPU, memory, and custom metrics. Database read replicas distribute query load.
Microservices allow independent scaling of components (e.g., payment processing vs. analytics), better fault isolation, and technology diversity. However, they add complexity. We evaluate based on team size, traffic patterns, and business requirements. For many high-load systems, a modular monolith with clear boundaries can be more maintainable initially, with migration to microservices as needed.
We'll analyze your current infrastructure, performance bottlenecks, and scalability risks — and propose the right architecture for your next stage of growth. Let's build a system that never slows down.
Talk to the teamH-Studio provides high-load backend development and system architecture services for companies across Europe. We design and implement backend systems that handle millions of events per second, process real-time data streams, and scale horizontally to support enterprise-level traffic. Our team specializes in event-driven architectures, microservices, distributed systems, and high-performance APIs built with Java, Kotlin, Spring Boot, Apache Kafka, PostgreSQL, and ClickHouse.
We work with fintech platforms, SaaS products, marketplaces, analytics platforms, and real-time consumer applications that require zero-downtime reliability, predictable performance under load, and long-term maintainability. Our backend engineering services include architecture design, performance optimization, database tuning, infrastructure setup, and ongoing maintenance — from first MVP to enterprise-scale deployments.