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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.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges. It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Caching them at the other end: How long should we cache files on a user’s device? Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download. Read the complete test methodology.

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5.5 mm in 1.25 nanoseconds

Randon ASCII

That meant I started having regular meetings with the hardware engineers who were working with IBM on the CPU which gave me even more expertise on this CPU, which was critical in helping me discover a design flaw in one of its instructions , and in helping game developers master this finicky beast. To the left of that is one of the CPU cores.

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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.

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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

CDNs cache content on edge servers distributed globally, reducing the distance between users and the content they want.‍CDNs use load-balancing techniques to distribute incoming traffic across multiple servers called Points of Presence (PoPs) which distribute content closer to end-users and improve overall performance.

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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

CDNs cache content on edge servers distributed globally, reducing the distance between users and the content they want.‍CDNs CDN architecture also focuses on caching, load balancing, routing, and optimizing content delivery, which can be measured by: cache offloading and round-trip time (RTT).‍RTT