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How to Scale Elasticsearch to Solve Your Scalability Issues

DZone

With the evolution of modern applications serving increasing needs for real-time data processing and retrieval, scalability does, too. However, the process for effectively scaling Elasticsearch can be nuanced, since one needs a proper understanding of the architecture behind it and of performance tradeoffs.

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency.

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This article outlines the key differences in architecture, performance, and use cases to help determine the best fit for your workload. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is RabbitMQ?

Latency 147
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Efficient Multimodal Data Processing: A Technical Deep Dive

DZone

Handling multimodal data spanning text, images, videos, and sensor inputs requires resilient architecture to manage the diversity of formats and scale.

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Foundation Model for Personalized Recommendation

The Netflix TechBlog

This scenario underscored the need for a new recommender system architecture where member preference learning is centralized, enhancing accessibility and utility across different models. Yet, many are confined to a brief temporal window due to constraints in serving latency or training costs.

Tuning 200
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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 251
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Spring WebFlux: publishOn vs subscribeOn for Improving Microservices Performance

DZone

With the rise of microservices architecture , there has been a rapid acceleration in the modernization of legacy platforms, leveraging cloud infrastructure to deliver highly scalable, low-latency, and more responsive services. Why Use Spring WebFlux?