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FIFO vs. LIFO: Which Queueing Strategy Is Better for Availability and Latency?

DZone

In this post, we'll explore both strategies through a simple simulation in Colab, allowing you to see the impact of changing parameters on system performance. After all, as the saying goes: " I hear and I forget, I see and I remember, I do and I understand. You can find the details in this Colab.

Strategy 141
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Plan Your Multi Cloud Strategy

Scalegrid

A well-planned multi cloud strategy can seriously upgrade your business’s tech game, making you more agile. Key Takeaways Multi-cloud strategies have become increasingly popular due to the need for flexibility, innovation, and the avoidance of vendor lock-in. They can also bolster uptime and limit latency issues or potential downtimes.

Strategy 130
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How to Optimize CPU Performance Through Isolation and System Tuning

DZone

CPU isolation and efficient system management are critical for any application which requires low-latency and high-performance computing. To achieve this level of performance, such systems require dedicated CPU cores that are free from interruptions by other processes, together with wider system tuning.

Tuning 246
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Low Overhead Continuous Contextual Production Profiling

DZone

In order to gain insight into these problems, we gather a range of metrics and logs to monitor the utilization of system resources such as CPU, memory, and application-specific latencies. It is worth noting that this data collection process does not impact the performance of the application.

Latency 246
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Using Pausers in Event Loops

DZone

Typically in low-latency development, a trade-off must be made between minimizing latency and avoiding excessive CPU utilization. In a typical application stack, multiple threads are used for servicing events, processing data, pipelining, and so on. Description of the Problem.

Latency 130
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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal. In this testing strategy, we execute a copy (replay) of production traffic against a system’s existing and new versions to perform relevant validations. This approach has a handful of benefits.

Traffic 339
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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