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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. <code> 127.0.0.1:6379> <code> 127.0.0.1:6379>

Metrics 130
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How to Assess MySQL Performance

HammerDB

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.

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Five Data-Loading Patterns To Improve Frontend Performance

Smashing Magazine

Every unnecessary bit of JavaScript code you bundle and serve will be more code the client has to load and process. On your first try, you can use it as a benchmark for optimizations later. How will you serve blazingly fast code, then? On design systems, UX, web performance and CSS/JS. Active Memory Caching.

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Towards multiverse databases

The Morning Paper

Therefore, frontend code is responsible for permission checks and privacy-preserving transformations that protect user’s data. Such a design rules out an entire class of application errors, protecting private data from accidentally leaking. Implementing this as a joint partially-stateful dataflow is the key to doing this safely.

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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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The Return of the Frame Pointers

Brendan Gregg

Apart from library code, maybe your application doesn't have frame pointers either, in which case everything is broken. Only in extreme circumstances does the cost (in processor time and I-cache footprint) translate to a tangible benefit - circumstances which usually resort to hand-coded assembly anyway.

Java 145
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Upcoming of the learned data structures

Abhishek Tiwari

This has far-reaching implications how future data systems and algorithms will be designed. They demonstrated that neural nets based learned index outperforms cache-optimized B-Tree index by up to 70% in speed while saving an order-of-magnitude in memory.