9 docs tagged with "compute"

Service state refers to the in-memory or on-disk data required by a service to function. State includes the data structures and member variables that the service reads and writes. Depending on how the service is architected, the state might also include files or other resources stored on the disk. Applications that consume large memory or on-disk data require larger VM sizes, especially for cloud computing where you would need larger VM SKUs to support high RAM capacity and multiple data disks.

It's better to have one VM running at a higher utilization than two running at low utilization rates, not only in terms of energy proportionality but also in terms of embodied carbon. Two servers running at low utilization rates will consume more energy than one running at a high utilization rate. In addition, the unused capacity on the underutilized server could be more efficiently used for another task or process.

It's better to have one VM running at a higher utilization than two running at low utilization rates, not only in terms of energy proportionality but also in terms of embodied carbon. Two servers running at low utilization rates will consume more energy than one running at a high utilization rate. In addition, the unused capacity on the underutilized server could be more efficiently used for another task or process.

CPU usage and utilization varies throughout the day, sometimes wildly for different computational requirements. The larger the variance between the average and peak CPU utilization values, the more resources need to be provisioned in stand-by mode to absorb those spikes in traffic.

CPU usage and utilization varies throughout the day, sometimes wildly for different computational requirements. The larger the variance between the average and peak CPU utilization values, the more resources need to be provisioned in stand-by mode to absorb those spikes in traffic.

Many attacks on cloud infrastructure seek to misuse deployed resources, which leads to an unnecessary spike in usage and cost.

When resources are constrained during high-traffic events or when carbon intensity is high, more carbon emissions will be generated from your system. Adding more resources to support increased traffic requirements introduces more embodied carbon and more demand for electricity. Continuing to handle all requests during high carbon intensity will increase overall emissions for your system. Shedding traffic that is lower priority during these scenarios will save on resources and carbon emissions. This approach requires an understanding of your traffic, including which call requests are critical and which can best withstand retry attempts and failures.

Transport Layer Security (TLS) ensures that all data passed between the web server and web browsers remain private and encrypted. However, terminating and re-establishing TLS increases CPU usage and might be unnecessary in certain architectures.

Network and web application firewalls provide protection against most common attacks and load shedding bad bots. These tools help to remove unnecessary data transmission and reduce the burden on the cloud infrastructure, while also using lower bandwidth and less infrastructure.