Avoid an excessive DOM size
The greater the amount of nodes that are defined in HTML, the greater the time spent processing and rendering each element.
The greater the amount of nodes that are defined in HTML, the greater the time spent processing and rendering each element.
Most web experiences require a lot of work from the user's browser. The greater the length of the chains and the larger the download sizes, the more significant the impact on page load performance and the energy required to render a page.
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Data protection through encryption is a crucial aspect of our security measures. However, the encryption process can be resource-intensive at multiple levels.
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.
Accessing a web page usually retrieves a HTML file from the web server. The HTML may then reference additional resources that the browser has to download.
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.
Ideally, the stored pixel dimensions are exactly the same, or smaller, as the display size in pixels so that no bandwidth or storage space is wasted.
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.
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Demand for resources depends on user load at any given time. However, most applications run without taking this into consideration. As a result,resources are underused and inefficient.
By default, Kubernetes scales workloads based on CPU and RAM utilization. In practice, however, it's difficult to correlate your application's demand drivers with CPU and RAM utilization. Scaling your workload based on relevant demand metrics that drive scaling of your applications, such as HTTP requests, queue length, and cloud alerting events can help reduce resource utilization, and therefore also your carbon emissions.
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Many attacks on cloud infrastructure seek to misuse deployed resources, which leads to an unnecessary spike in usage and cost.
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.
The carbon emissions of a software system depends on the power consumed by that software, but also on the Carbon intensity of the electricity it is powered on. For this reason, running energy-efficient software on carbon intensive electricity grid, might be inefficient to reduce its global carbon emissions. Carbon aware time scheduling, is about scheduling workloads to execute, when electricity carbon intensity is low.
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When making calls across process boundaries to either databases or file systems or REST APIs, relying on synchronous calls can cause the calling thread to become blocked, putting additional load on the CPU
Modern applications need to communicate with other applications on a regular basis. Since these other applications have their own deployment schedule, downtimes and availability, the network connection to these application might have problems. If the other application is not reachable, all network requests against this other application will fail and future network requests are futile.
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.
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