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AWS Lambda Explained: Serverless for Beginners
AWS Lambda runs your code in response to events without servers to manage. This beginner's guide explains the handler, events and triggers, what an execution environment is and why initialisation code runs once, the limits that shape what Lambda is for, how billing works, and where it fits in data pipelines.
Lambda vs Kappa Architecture Explained
Lambda and Kappa architectures compared: Lambda's batch, speed and serving layers, Kappa's single replayable stream, a simulation on a week of real taxi trips in which Lambda's two code paths disagree by 982 trips until the nightly batch runs, how Kappa recomputes by replaying the log, and where lakehouses fit.
AWS Glue vs EMR vs Lambda for ETL
Glue, EMR and Lambda can each run ETL code on AWS, and they are built for very different sizes of job. This comparison sets out the hard limits of each, how data volume, control and operations decide the choice, how each is billed, and why most real pipelines end up using two or three of them together.
Event-Driven Pipelines with Lambda and S3
An event-driven pipeline starts work the moment a file arrives in S3. This guide explains S3 event notifications, writes a Lambda handler that validates and converts a real file, and runs it twice on the same event to show idempotency. It also covers encoded keys, loops, failure handling, and when to add a queue.
Lambda Functions, map, filter and reduce in Python
Lambda, map, filter and reduce explained by what they are good for: key functions for sorting and max, map and filter as lazy one-shot iterators, why reduce is usually replaced by a built-in, the operator module, and the loop-variable trap that makes every lambda return the same value.