Remove Benchmarking Remove Cache Remove Efficiency Remove Network
article thumbnail

Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. All these contribute significantly towards ensuring smooth functioning.

Metrics 130
article thumbnail

MySQL Key Performance Indicators (KPI) With PMM

Percona

We will also discuss related configuration variables to consider that can impact these KPIs, helping you gain a comprehensive understanding of your MySQL server’s performance and efficiency. Query performance Query performance is a key performance indicator (KPI) in MySQL, as it measures the efficiency and speed of query execution.

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

Five Data-Loading Patterns To Improve Frontend Performance

Smashing Magazine

The resource loading waterfall is a cascade of files downloaded from the network server to the client to load your website from start to finish. It essentially describes the lifetime of each file you download to load your page from the network. You can see this by opening your browser and looking in the Networking tab.

article thumbnail

Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130
article thumbnail

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. ASPLOS’19. Distributed tracing and instrumentation.

article thumbnail

Upcoming of the learned data structures

Abhishek Tiwari

Apart from indexes, super efficient sorting and join operations are some major areas come to my mind with immediate benefits of using learned data structure. They demonstrated that neural nets based learned index outperforms cache-optimized B-Tree index by up to 70% in speed while saving an order-of-magnitude in memory.

article thumbnail

Fixing a slow site iteratively

CSS - Tricks

Google’s industry benchmarks from 2018 also provide a striking breakdown of how each second of loading affects bounce rates. Using a network request inspector, I’m going to see if there’s anything we can remove via the Network panel in DevTools. In DevTools, the Network inspector helps us see what the first webpage is doing too.

Cache 92