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Architectural Insights: Designing Efficient Multi-Layered Caching With Instagram Example

DZone

Caching is a critical technique for optimizing application performance by temporarily storing frequently accessed data, allowing for faster retrieval during subsequent requests. Multi-layered caching involves using multiple levels of cache to store and retrieve data.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

Best Effort Regional Counter This type of counter is powered by EVCache , Netflix’s distributed caching solution built on the widely popular Memcached. Without an efficient data retention strategy, this approach may struggle to scale effectively. Efficient Aggregation: Each rollup consumer processes a batch of counters simultaneously.

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Distance-Based ISA for Efficient Register Management

ACM Sigarch

To create a CPU core that can execute a large number of instructions in parallel, it is necessary to improve both the architecturewhich includes the overall CPU design and the instruction set architecture (ISA) designand the microarchitecture, which refers to the hardware design that optimizes instruction execution.

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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. At inference time, when multi-step decoding is needed, we can deploy KV caching to efficiently reuse past computations and maintain lowlatency.

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Sustainable IT: Optimize your hybrid-cloud carbon footprint

Dynatrace

Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. Most approaches focus on improving Power Usage Effectiveness (PUE), a data center energy-efficiency measure. energy-efficient data centers—cloud providers—achieve values closer to 1.2. A PUE of 1.0

Cloud 264
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

In this post, we dive deep into how Netflix’s KV abstraction works, the architectural principles guiding its design, the challenges we faced in scaling diverse use cases, and the technical innovations that have allowed us to achieve the performance and reliability required by Netflix’s global operations.

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