International Scientific Journal of Engineering and Management

An International Scholarly || Multidisciplinary || Open Access || Indexing in all major Database & Metadata
The journal follows the UGC Guidelines and is evaluated for inclusion in the Web of Science
ISSN: 2583-6129

Impact Factor: 7.839

High-Throughput Event Ingestion with Kafka: Performance Optimization Strategies for Large-Scale Systems

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High-Throughput Event Ingestion with Kafka: Performance Optimization Strategies for Large-Scale Systems

Pradeep Kumar, pradeepkryadav@gmail.com

Performance Expert, SAP SuccessFactors, Bangalore India

Abstract

In large-scale event-driven systems, managing high-throughput event ingestion is critical to ensuring real-time data processing and scalability. Apache Kafka, a widely adopted distributed streaming platform, is designed to handle massive data streams but faces performance challenges related to resource utilization, partitioning, network congestion, and disk I/O bottlenecks. This research explores a comprehensive set of optimization strategies for Kafka, addressing these challenges through producer, broker, consumer, and infrastructure-level tuning.

Our methodology involves systematically testing and evaluating optimization techniques, including message batching, compression, partition configuration, replication factor adjustments, and network tuning. Additionally, we analyze hardware resource allocation and cluster scaling strategies to further enhance Kafka’s performance.

The results demonstrate significant improvements in throughput, with optimized configurations achieving up to a 60% increase in message ingestion rates compared to default settings. Latency reductions of up to 40% were observed under high-load scenarios, while CPU and memory utilization were optimized to maintain resource efficiency. These findings provide practical guidelines for organizations aiming to deploy Kafka in large-scale environments, enabling both short-term performance gains and long-term scalability.

 

Keywords

Kafka, event ingestion, optimization strategies, throughput, scalability, performance tuning, distributed systems.

 

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