Cache Cloud Hardware Operating System 
Dynatrace
JANUARY 16, 2023
Modern, cloud-native computing is impossible to separate from containers and Kubernetes adoption. As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes moved to the cloud in 2022. Kubernetes moved to the cloud in 2022.
Scalegrid
FEBRUARY 8, 2024
Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel.
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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. By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way.
The Morning Paper
MAY 12, 2019
An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., In this paper we explore the implications microservices have across the cloud system stack. Hardware implications. Operating system and network implications.
The Netflix TechBlog
MARCH 8, 2021
They need specialized hardware, access to petabytes of images, and digital content creation applications with controlled licenses. One of our first partners for the Netflix Workstations is NetFX , a cloud-based VFX platform that enables vendors, artists, and creators worldwide to collaborate on Netflix VFX content.
The Netflix TechBlog
JUNE 4, 2019
When you’re running in the cloud your containers are in a shared space; in particular they share the CPU’s memory hierarchy of the host instance. However, the key insight here is that these caches are partially shared among the CPUs, which means that perfect performance isolation of co-hosted containers is not possible.
Percona
MAY 1, 2023
Key areas include: Configuration parameter tuning : This tuning involves altering variables such as memory allocation, disk I/O settings, and concurrent connections based on specific hardware and requirements. This not only results in cost savings by minimizing hardware requirements but also has the potential to decrease cloud expenses.
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