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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.

Cache 161
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

Systems 226
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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. The streaming data store makes the system extensible to support other use-cases (e.g. System Components. Component Design. API Design. API Design. Data Models.

Design 334
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How DoorDash Rearchitected its Cache to Improve Scalability and Performance

InfoQ

DoorDash rearchitected the heterogeneous caching system they were using across all of their microservices and created a common, multi-layered cache providing a generic mechanism and solving a number of issues coming from the adoption of a fragmented cache. By Sergio De Simone

Cache 110
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 201
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. offers the Software Watchdog specifically designed for this purpose.

Metrics 130
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Geek Reading - Week of June 5, 2013

DZone

Simpler UI Testing with CasperJS ( Architects Zone – Architectural Design Patterns & Best Practices). Using MongoDB as a cache store ( Architects Zone – Architectural Design Patterns & Best Practices). Linux System Mining with Python ( Javalobby – The heart of the Java developer community). Hacker News).

Java 244