Blog
On Remote Work and Deep Thinking
Reflections on how remote work has changed the way we think, collaborate, and find meaning in our professional lives.
Read this on SubstackDeciphering Coupling in Software Architecture- Architecture Quantum Explored
Learn how independent deployability, functional cohesion, and coupling help define architecture quanta for robust distributed systems.
Read this on SubstackEthical Data Practices for Building Better Systems
A critical look at how data-intensive systems can impact society, exploring issues like predictive analytics, surveillance, biases, and the responsibilities of engineers.
Read this on SubstackBuilding Correct Systems in Distributed Environments
Explore strategies to build reliable and fault-tolerant systems while handling limitations in transactions, data corruption, and distributed coordination.
Read this on SubstackUnbundling Monolithic Databases for Flexibility
Learn how unbundling databases helps to achieve scalability and flexibility, combining specialized tools to meet modern data needs.
Read this on SubstackIntegrating Distributed Systems for Unified Data Pipelines
Explore the intricacies of data integration in distributed applications, including synchronizing specialized systems and maintaining correctness across diverse data sources.
Read this on SubstackUnifying Batch and Stream Processing for Modern Pipelines
Examine how unbounded data streams are processed in real-time applications, including operators, time reasoning, joins, and fault tolerance.
Read this on SubstackSynchronizing Databases with Real-Time Streams
Examine how streams integrate with databases through change data capture, event sourcing, and the immutability of state, enabling real-time system synchronization.
Read this on SubstackEnabling Reliable and Scalable Event Streams in Distributed Systems
Explore how messaging systems and partitioned logs enable reliable and scalable transmission of event streams within distributed systems.
Read this on SubstackAdvancing Beyond MapReduce- Modern Frameworks for Scalable Data Processing
Explore alternatives to MapReduce, including advanced dataflow engines and their benefits in efficiency, iterative graph processing, and high-level abstractions.
Read this on SubstackMapReduce and Distributed Filesystems- Foundations of Scalable Data Processing
Learn how MapReduce operates over distributed filesystems like HDFS, combining computation and storage for scalable data processing.
Read this on SubstackLeveraging Unix Tools for Efficient Batch Processing
Explore the power of Unix-based batch processing using tools like awk, sort, and grep, and how their design philosophy laid the foundation for modern big data processing.
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