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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. Similarly, an increased throughput signifies an intensive workload on a server and a larger latency.

Metrics 130
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Towards a Reliable Device Management Platform

The Netflix TechBlog

When a new hardware device is connected, the Local Registry detects and collects a set of information about it, such as networking information and ESN. As such, we can see that the traffic load on the Device Management Platform’s control plane is very dynamic over time.

Latency 213
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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

‍A content delivery network (CDN) is a distributed network of servers strategically located across multiple geographical locations to deliver web content to end users more efficiently. A lower RTT indicates a faster network response time and happier end users. What is a CDN?‍A ‍What is CDN Architecture?

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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

A content delivery network (CDN) is a distributed network of servers strategically located across multiple geographical locations to deliver web content to end users more efficiently. A lower RTT indicates a faster network response time and happier end users. What is a CDN?‍A What is CDN Architecture?‍CDN

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New Network Fallacies

Tim Kadlec

I remember how, later on, a common question I would get in after giving performance-focused presentations was: “Is any of this going to matter when 4G is available?” ” The fallacy of networks, or new devices for that matter, fixing our performance woes is old and repetitive. This is nothing new.

Network 61
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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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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

There is no way to model how much more traffic you can send to that system before it exceeds it’s SLA. I presented this analysis of response time distributions talk in 2016 — at Microxchg in Berlin ( video ). Mu is the mean of each component, the latency. I’ve been thinking about this for a long time.

Lambda 98