Scalegrid

JANUARY 25, 2024

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

Metrics Monitoring Latency Cache 130

Dynatrace

JANUARY 26, 2021

Traditional computing models rely on virtual or physical machines, where each instance includes a complete operating system, CPU cycles, and memory. There is no need to plan for extra resources, update operating systems, or install frameworks. The provider is essentially your system administrator.

Serverless 243

Serverless Efficiency Lambda Azure 243

Percona

MARCH 23, 2023

Hardware Memory The amount of RAM to be provisioned for database servers can vary greatly depending on the size of the database and the specific requirements of the company. Operating system Linux is the most common operating system for high-performance MySQL servers.

Performance 123

Performance Hardware Tuning Storage 123

John McCalpin

APRIL 25, 2023

This metric is interesting because we don’t always have the luxury of parallelizing every application we run, and our operating systems almost always process each call (e.g., Stay tuned! buffer copies for filesystem access) with a single thread. Why is the single-core bandwidth increasing so slowly?

Benchmarking 97

Benchmarking Cache Latency Tuning 97

Percona

APRIL 17, 2023

In this blog post, we will discuss the best practices on the MongoDB ecosystem applied at the Operating System (OS) and MongoDB levels. The main objective of this post is to share my experience over the past years tuning MongoDB and centralize the diverse sources that I crossed in this journey in a unique place.

Best Practices 52

Best Practices Design Tuning Database 52

The Morning Paper

MAY 21, 2019

This boils down to a single digit µs latency toleration in the tail for far memory, and in addition to security and privacy concerns, rules out remote memory solutions. Thus we’re fundamentally trading (de)-compression latency at access time for the ability to pack more data in memory. ML-based auto-tuning. Evaluation.

Software 78

Software Software Google Hardware 78

O'Reilly Software

APRIL 4, 2018

Are there inherent time relationships in the messages that need to be preserved as they travel across the system? The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. What message process warranty level do we require? At least once? At most once? Exactly once?

Architecture 80

Architecture Scalability Google Operating System 80