BLOGS

From Blogs To Case Studies, Whitepapers, Podcasts & Beyond

Importance of User Experience in Product Adoption

Do you know what is the key factor in success of any app? Yes, user experience. This blog tells you why and how user experience impacts your app along with some important tips to improve it.

Latest Articles

Optimizing Databricks Spark jobs using dynamic partition pruning and AQE

Learn how to supercharge your Databricks Spark jobs using Dynamic Partition Pruning (DPP) and Adaptive Query Execution (AQE). This comprehensive guide walks through practical implementations, real-world scenarios, and best practices for optimizing large-scale data processing. Discover how to significantly reduce query execution time and resource usage through intelligent partition handling and runtime optimizations. Perfect for data engineers and architects looking to enhance their Spark job performance in Databricks environments.

Implementing custom serialization and deserialization in Apache Kafka for optimized event processing performance

Dive deep into implementing custom serialization and deserialization in Apache Kafka to optimize event processing performance. This comprehensive guide covers building efficient binary serializers, implementing buffer pooling for reduced garbage collection, managing schema versions, and integrating compression techniques. With practical code examples and performance metrics, learn how to achieve up to 65% higher producer throughput, 45% better consumer throughput, and 60% reduction in network bandwidth usage. Perfect for developers looking to enhance their Kafka implementations with advanced serialization strategies.

Designing multi-agent systems using LangGraph for collaborative problem-solving

Learn how to build sophisticated multi-agent systems using LangGraph for collaborative problem-solving. This comprehensive guide covers the implementation of a software development team of AI agents, including task breakdown, code implementation, and review processes. Discover practical patterns for state management, agent communication, error handling, and system monitoring. With real-world examples and code implementations, you'll understand how to orchestrate multiple AI agents to tackle complex problems effectively. Perfect for developers looking to create robust, production-grade multi-agent systems that can handle iterative development workflows and maintain reliable state management.

Designing event-driven microservices architectures using Apache Kafka and Kafka Streams

Dive into the world of event-driven microservices architecture with Apache Kafka and Kafka Streams. This comprehensive guide explores core concepts, implementation patterns, and best practices for building scalable distributed systems. Learn how to design event schemas, process streams effectively, and handle failures gracefully. With practical Java code examples and real-world architectural patterns, discover how companies like Netflix and LinkedIn process billions of events daily. Whether you're new to event-driven architecture or looking to optimize your existing system, this guide provides valuable insights into building robust, loosely coupled microservices.

Implementing Custom Instrumentation for Application Performance Monitoring (APM) Using OpenTelemetry

Application Performance Monitoring (APM) has become crucial for businesses to ensure optimal software performance and user experience. As applications grow more complex and distributed, the need for comprehensive monitoring solutions has never been greater. OpenTelemetry has emerged as a powerful, vendor-neutral framework for instrumenting, generating, collecting, and exporting telemetry data. This article explores how to implement custom instrumentation using OpenTelemetry for effective APM.

Implementing Custom Evaluation Metrics in LangChain for Measuring AI Agent Performance

As AI and language models continue to advance at breakneck speed, the need to accurately gauge AI agent performance has never been more critical. LangChain, a go-to framework for building language model applications, comes equipped with its own set of evaluation tools. However, these off-the-shelf solutions often fall short when dealing with the intricacies of specialized AI applications. This article dives into the world of custom evaluation metrics in LangChain, showing you how to craft bespoke measures that truly capture the essence of your AI agent's performance.