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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.

