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Collecting data metrics in real-time?

A metric can be defined as a single form of data that allows businesses to measure their

operations to achieve growth and optimize performance. Businesses collect data to organize and query through the data to form metrics that can help in achieving their goals. For instance, an e-commerce platform collects customer data to create metrics that represents user clicks on an ad campaign.

Metrics extract a value existing in a system at a specific point in time such as a number of

users logged in to a mobile application. Thus, metrics are collected once per second, per

minute, or at a regular interval to monitor a system over time. There are two categories of

metrics; work metrics and resource metrics. Both the categories are useful as per the

software infrastructure.

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Work Metrics

Work metrics stipulates the top hierarchy of the system to measure the useful output. Work

metrics are important for observability as they are big measures that allow the users to

respond to the issues of a system’s internal health and performance. The work metrics are

further divided into four subcategories:

Throughput – it is the amount of the work done on a system per unit time and it is usually

recorded as an absolute number.

Success – this represents the success rate of the work in percentage.

Error – this captures the number of errors in the result, also presented as the rate of error

per unit time. When there are various potential sources of error, the error metrics are

extracted separately from success metrics.

Performance – this quantifies the efficiency of the performance of a component. Latency is

the most common performance metrics that constitute the time required to finish a unit of

work. It is either represented as an average or percentile.

Resource Metrics

In the software infrastructure, most components serve as a resource to other systems. For

example, some resources are low level that includes CPU, disks, memory, and network

interfaces. For a higher level components like geolocation microservice or databases can be considered as a resource for another system that requires components to perform a task. Users must collect metrics from the following key areas:

Utilization – it is the percentage of time to indicate that a resource is busy or to show the

capacity of the resource under use.

Saturation – it measures the amount of work requested that cannot be catered by a

resource, usually queued.

Errors – it represents errors that are internal and cannot be observed in the work performed

by a resource.

Availability – it represents the time in percentage taken by a resource to respond to a

request. This metric is only well-defined for active and regularly checked resources.

There are some other metrics such as cache hits, or database locks that can help a complex system to be observable. Collecting data metrics in real-time can help enterprises in taking prompt actions for their software infrastructure on critical matters.

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