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Understanding Distributed Consensus Algorithms
A deep dive into how distributed systems achieve consensus, exploring Raft and Paxos algorithms. We examine the trade-offs between consistency and availability, and discuss practical implementation considerations for building resilient distributed applications.
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The Architecture of Modern ML Training Pipelines
Exploring the infrastructure required to train large-scale machine learning models, from data preprocessing and distributed training strategies to model serving and monitoring. Includes practical patterns for building reproducible training workflows.
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Zero-Downtime Database Migrations at Scale
Techniques and strategies for performing schema changes on production databases without service interruption. Covering backwards-compatible migrations, gradual rollouts, and handling edge cases when migrating large datasets.
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Building Observable Systems with OpenTelemetry
A practical guide to implementing comprehensive observability in microservices architectures using OpenTelemetry. Learn how to instrument your code for traces, metrics, and logs to gain deep insights into system behavior.
Sahar Banisafar
Data Scientist & Technical Writer
