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

Implementing feature flags for controlled rollouts and experimentation in production

Discover how feature flags can revolutionize your software deployment strategy in this comprehensive guide. Learn to implement everything from basic toggles to sophisticated experimentation platforms with practical code examples in Java, JavaScript, and Node.js. The post covers essential implementation patterns, best practices for flag management, and real-world architectures that have helped companies like Spotify reduce deployment risks by 80%. Whether you're looking to enable controlled rollouts, A/B testing, or zero-downtime migrations, this guide provides the technical foundation you need to build robust feature flagging systems.

Implementing incremental data processing using Databricks Delta Lake's change data feed

Discover how to implement efficient incremental data processing with Databricks Delta Lake's Change Data Feed. This comprehensive guide walks through enabling CDF, reading change data, and building robust processing pipelines that only handle modified data. Learn advanced patterns for schema evolution, large data volumes, and exactly-once processing, plus real-world applications including real-time analytics dashboards and data quality monitoring. Perfect for data engineers looking to optimize resource usage and processing time.

Implementing custom embeddings in LlamaIndex for domain-specific information retrieval

Discover how to dramatically improve search relevance in specialized domains by implementing custom embeddings in LlamaIndex. This comprehensive guide walks through four practical approaches—from fine-tuning existing models to creating knowledge-enhanced embeddings—with real-world code examples. Learn how domain-specific embeddings can boost precision by 30-45% compared to general-purpose models, as demonstrated in a legal tech case study where search precision jumped from 67% to 89%.

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.