Scalegrid

JANUARY 12, 2024

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. This applies to both virtual machines and container-based deployments.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Scalegrid

FEBRUARY 8, 2024

Handling Large Volumes of Data Distributed storage systems employ the technique of data sharding or partitioning to handle immense quantities of information. By breaking up large datasets into more manageable pieces, each segment can be assigned to various network nodes for storage and management purposes.

Storage 130

Storage Systems Big Data Azure 130

Smashing Magazine

OCTOBER 31, 2023

Type 2: Full Real-User Monitoring (RUM) If CrUX offers one flavor of real-user data, then we can consider “full real-user data” to be another flavor that provides even more in the way individual experiences, such as specific network requests made by the page. The accuracy of observed data depends on how the test environment is set up.

Speed 97

Speed Google Website Metrics 97

All Things Distributed

MARCH 11, 2016

Failures are a given and everything will eventually fail over time: from routers to hard disks, from operating systems to memory units corrupting TCP packets, from transient errors to permanent failures. The importance of the network. Each of those workloads have unique requirements when it comes to the network.

AWS 144

AWS Hardware Retail Virtualization 144

Adrian Cockcroft

APRIL 5, 2023

Energy data at the entire machine or raw cloud instance level needs to be apportioned to virtual machines or cloud instances which run an operating system, and to pods, containers and processes running applications and background activities that consume CPU, memory and I/O resources.

Energy 52

Energy Metrics Cloud Operating System 52

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. Operating System (OS) settings Swappiness Swappiness is a Linux kernel setting that influences the behavior of the Virtual Memory manager when it needs to allocate a swap, ranging from 0-100.

Best Practices 52

Best Practices Design Tuning Database 52

Dotcom-Montior

NOVEMBER 24, 2021

There was a time when standing up a website or application was simple and straightforward and not the complex networks they are today. Web developers or administrators did not have to worry or even consider the complexity of distributed systems of today. Great, your system was ready to be deployed. Do you have a database?

Systems 74

Systems Monitoring Hardware Network 74

The Morning Paper

JUNE 30, 2019

The Great Dorset Steam Fair ’), which are a bit like a distributed denial of service attack on the road network as lots of very slow steam engines all converge on a given point. Processes (or in the case of System R, transactions) can also bump into each other when contending for shared resources. Hence convoys will occur.

Traffic 75

Traffic Latency Programming Scalability 75

Testsigma

SEPTEMBER 4, 2021

From game development to machine learning projects to neural networks to automation testing- everything is on the cloud. Obviously, the application will see a huge spike in traffic and testers would have already made the application scale-proof. Let’s forget that there is anything called ‘cloud’ existing in our network or organization.

Cloud 52

Cloud Testing Infrastructure Testing Tools 52

All Things Distributed

OCTOBER 2, 2017

The success of our early results with the Dynamo database encouraged us to write Amazon's Dynamo whitepaper and share it at the 2007 ACM Symposium on Operating Systems Principles (SOSP conference), so that others in the industry could benefit. This was the genesis of the Amazon Dynamo database.

Internet 128

Internet Internet AWS Performance 128