Remove Hardware Remove Latency Remove Systems Remove Tuning
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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. These measures are especially important for high-frequency trading systems, where split-second decisions on buying and selling stocks must be made.

Tuning 246
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52
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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. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130
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Best Practices for a Seamless MongoDB Upgrade

Percona

MongoDB is a dynamic database system continually evolving to deliver optimized performance, robust security, and limitless scalability. Improved performance : MongoDB continually fine-tunes its database engine, resulting in faster query execution and reduced latency. Ready to supercharge your MongoDB experience?

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Save Money in AWS RDS: Don’t Trust the Defaults

Percona

I’ll show you some MySQL settings to tune to get better performance, and cost savings, with AWS RDS. The innodb_io_capacity_max parameter was set to 2000, so the hardware should be able to deliver that many IOPS without major issues. Want to save money on your AWS RDS bill?

AWS 124
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Towards a Reliable Device Management Platform

The Netflix TechBlog

Complementing the hardware is the software on the RAE and in the cloud, and bridging the software on both ends is a bi-directional control plane. System Setup Architecture The following diagram summarizes the architecture description: Figure 1: Event-sourcing architecture of the Device Management Platform.

Latency 213
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A case for managed and model-less inference serving

The Morning Paper

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. Managed here means that the system automates resource provisioning for models to match a set of SLO constraints (cf. autoscaling).