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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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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 Here are a few examples.

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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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USENIX LISA2021 Computing Performance: On the Horizon

Brendan Gregg

AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. I also wrote about these topics in detail for my recent [Systems Performance 2nd Edition] book.

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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. Fault Tolerance If the underlying KafkaConsumer crashes due to ephemeral system or network events, it should be automatically restarted.

Latency 213
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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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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP