Remove Availability Remove Cache Remove Hardware Remove Latency
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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. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 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. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130
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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
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What is a Distributed Storage System

Scalegrid

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. Variations within these storage systems are called distributed file systems.

Storage 130
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Time to First Byte: What It Is and Why It Matters

CSS Wizardry

The first—and often most surprising for people to learn—thing that I want to draw your attention to is that TTFB counts one whole round trip of latency. The reason is because mobile networks are, as a rule, high latency connections. only to find that the resource they’re requesting isn’t in that PoP ’s cache.

Latency 269
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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., It’s a pretty impressive effort to pull together and make available in open source (not yet available as I write this) such a suite, and I’m sure explains much of the long list of 24 authors on this paper.

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Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)

ACM Sigarch

There are three common mechanisms to access remote memory: modifying applications, modifying virtual memory, and hardware-level cache coherence support. even lowered the latency by introducing a multi-headed device that collapses switches and memory controllers. The recently announced CXL3.0

Latency 52