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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130
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Best practices and key metrics for improving mobile app performance

Dynatrace

Mobile applications (apps) are an increasingly important channel for reaching customers, but the distributed nature of mobile app platforms and delivery networks can cause performance problems that leave users frustrated, or worse, turning to competitors. Load time and network latency metrics. Minimize network requests.

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Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130
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Redis® Monitoring Strategies for 2024

Scalegrid

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. With these essential support systems in place, you can effectively monitor your databases with up-to-date data about their health and functioning status at all times.

Strategy 130
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Designing Instagram

High Scalability

The streaming data store makes the system extensible to support other use-cases (e.g. System Components. The system will comprise of several micro-services each performing a separate task. When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency.

Design 334
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 251