Remove Benchmarking Remove Cache Remove Latency Remove Tuning
article thumbnail

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
article thumbnail

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
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

The evolution of single-core bandwidth in multicore processors

John McCalpin

For most high-end processors these values have remained in the range of 75% to 85% of the peak DRAM bandwidth of the system over the past 15-20 years — an amazing accomplishment given the increase in core count (with its associated cache coherence issues), number of DRAM channels, and ever-increasing pipelining of the DRAMs themselves.

article thumbnail

The Most Important MySQL Setting

Percona

If we were to select the most important MySQL setting, if we were given a freshly installed MySQL or Percona Server for MySQL and could only tune a single MySQL variable, which one would it be? To be fair, that is also true with PostgreSQL; it hasn’t been tuned either, and it, too, can also perform much better.

Tuning 133
article thumbnail

Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. These have inspired me to summarize another performance activity: evaluating benchmark accuracy. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

article thumbnail

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

The Morning Paper

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook , Cao et al., Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads.

article thumbnail

Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. These have inspired me to summarize another performance activity: evaluating benchmark accuracy. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?