Enterprises are now operating in a world where data is streamed in real time from cloud-native applications, IoT devices, and AI-driven systems. But even with this shift, 88% of organizations still use REST APIs to connect services. Meanwhile, more than 72% of organizations have either already implemented or are planning to implement event-driven architectures to process real-time workloads more effectively for building event-driven microservices. This contrast highlights that many companies are struggling with architectures that rely on synchronous communication.
REST’s request/response model creates tight coupling between services, which means both sides must be up and responsive. It adds latency, complexity to error handling, and challenges to scaling, and it’s particularly difficult in industries like finance, healthcare, and industrial automation, where more than 70% of enterprises require real-time data processing to keep their competitive edge.”
Tymon Global (Best API integration solutions) have seen how REST-based architectures can limit agility, delay deployments, and complicate observability. Our experience shows that transitioning to event mesh architecture provides scalability, fault tolerance, and faster time-to-market, helping enterprises thrive in today’s fast-growing technological ecosystems.
Event mesh for decoupled and scalable services
Event mesh architecture is the backbone of modern microservices ecosystems. It enables services to publish and subscribe to events without having to be aware of each other’s location, availability, or state. This separation is essential for multi-region, multi-team, or multi-cloud systems. With event mesh, services are loosely coupled via topics, allowing events to flow reliably even in the face of network partitions. In contrast to traditional service meshes, event meshes are designed to broadcast, replay and route events, with fault tolerance as a core principle.
Gartner reports 72% of enterprises experienced increased system resilience as a result of implementing event-driven architectures, and 68% delivered features more rapidly. Event mesh architecture also enables observability with distributed tracing, schema versioning, and governance frameworks, minimizing operational overhead and maximizing compliance readiness.
Apache Kafka for high-throughput reactive microservices
Apache Kafka is now the de facto standard for high-throughput and durable data pipelines. Its distributed nature allows it to partition events across vendors and process them in parallel at scale without losing fault tolerance. Kafka’s core strengths are:
- Partitioned topics that enable workloads to scale out across many consumers.
- Replication that protects against data loss in the event of a network or node failure.
- Log compaction and retention for long-term storage, recovery, and backfilling.
- Streaming APIs such as Kafka Streams and ksqlDB for real-time analytics and data transformation.
Kafka is the backbone of systems that handle millions of messages per second, including fraud detection in financial services, operational monitoring in manufacturing, and telemetry pipelines in connected healthcare devices.
Tymon Global brings Kafka expertise to help clients take full advantage of Kafka to create event-driven systems that are resilient to extreme workloads and satisfy regulatory, compliance, and performance needs.
NATS for ultra-low-latency event-driven messaging
Kafka is known for its durability and throughput, but NATS event-driven microservices are optimized for scenarios where latency needs to be as low as possible. Built for microsecond-level messaging, NATS is a perfect fit for environments where every millisecond matters.
Key features include:
- Messaging with microsecond latency, perfect for edge computing, financial trading, and autonomous applications
- Easy-to-understand subject-based routing enables the definition of message flows without involving complex orchestration
- JetStream persistence, offering at-least-once delivery guarantees and replay capabilities while maintaining simplicity
- Security and observability are built into the protocol for efficiency.
NATS provides low overhead and instant message delivery in latency-sensitive workloads like real-time monitoring, IoT frameworks, and distributed control systems. Tymon Global helps clients deploy NATS-based messaging layers in high-speed environments for operational simplicity, performance, and fault tolerance.
Apache Kafka vs REST APIs in microservices architectures
System workload and business goals determine communication model choice. Kafka is best for distributed event streams that need scale and durability, while REST APIs are best for transactional workflows that need immediate feedback. Architectural decisions benefit from comparative analysis:
Feature or Use Case |
REST APIs |
Apache Kafka |
| Communication style | Synchronous request/response | Asynchronous publish/subscribe |
| Best suited for | Transactional workflows requiring immediate validation | High-volume, distributed event streams |
| Performance characteristics | Services block until a response is received | Handles millions of events with low latency |
| Scalability | Limited by connection pooling and orchestration | Partitioning enables distributed, parallel processing |
| Fault tolerance | Requires retries, circuit breakers | Built-in replication, fault tolerance, and replay capabilities |
| Compliance requirements | Limited support for auditing and data recovery | Supports durability, replay, and audit trails, ideal for regulated industries |
| Typical use cases | Simple service interactions, CRUD operations | Real-time analytics, telemetry ingestion, log aggregation |
| Scalability | Manages critical transactions | Handles bulk data pipelines efficiently |
Enterprises combine both technologies in practice, where Tymon Global helps clients design robust, efficient hybrid systems with REST APIs handling critical transaction requests and Kafka pipelines managing bulk event streams.
Observability and governance in event-driven systems
Observability, schema management, and error handling are needed in event-driven architectures. Event-driven systems without these components risk data inconsistencies and opaqueness.
Consider these best practices:
- Create domain-specific event taxonomies for user authentication, order processing, and sensor telemetry.
- Avoid version conflicts and backward compatibility with Avro or Protobuf schema registries.
- Use idempotent event handlers to avoid duplication and safely retry.
- Monitor observability pipelines in real time with Prometheus, OpenTelemetry, and centralized logging.
- Divide tasks to scale consumer groups and avoid bottlenecks.
- Compliance and transparency require governance models with event catalogs, security policies, and audit trails.
Tymon Global helps clients build resilient, maintainable systems through schema evolution, fault tolerance, and observability in every deployment.
Tymon Global’s expertise in event-driven transformations
Enterprise architecture transformation requires deep expertise, proven frameworks, and the ability to tailor solutions to complex environments, not just tools. Tymon Global delivers event-driven architectures that scale with business demands using decades of digital product engineering, cloud-native systems, and real-time data pipelines.
Our teams have implemented Kafka and NATS-based solutions in healthcare, finance, manufacturing, and IoT to help clients meet strict compliance, scale operations, and innovate faster.
This is why Tymon Global is ideal for event-driven transformation acceleration. Engineering excellence, observability-first designs, and sustainable governance frameworks underpin our approach.
Contact Tymon Global today to design and deploy scalable event mesh architectures that drive innovation and resilience.
Frequently Asked Questions
Q. What challenges do enterprises face when scaling with REST APIs
Enterprises face challenges like increased latency, complex error handling, and service dependencies that hinder scaling, especially in distributed or real-time environments.
Q. How does event-driven communication improve system reliability
Event-driven communication decouples services, allowing them to operate independently. This improves fault tolerance and enables systems to recover quickly from failures.
Q. What types of workloads benefit most from using Kafka and NATS together
Workloads that combine high-throughput data pipelines and latency-sensitive messaging, such as financial services, IoT networks, and real-time analytics, benefit most from Kafka and NATS working together.
Q. What best practices ensure the smooth deployment of event-driven systems
Defining event taxonomies, using schema versioning, implementing idempotent handlers, and integrating monitoring tools help ensure reliability, scalability, and compliance during deployment.
Q. Why is expert guidance critical when implementing event-driven architecturesExpert guidance helps avoid common pitfalls like schema conflicts, data loss, and performance bottlenecks, ensuring systems are resilient, maintainable, and aligned with regulatory standards.
