Observability

Oct 06, 2021

Observability is a concept that has started to gain recognition in the IT industry due to the development of many new technologies.

What is Observability?

Observability is a measure of how well the internal states of a system can be inferred from knowledge of its external outputs.

Systems, where this concept is applicable, are called ‘observable’.

Prior to the use of observability, the concepts of Monitoring and Application Performance Monitoring (APM) were used for the identification of issues in the system and for providing a solution.

These methods are time-consuming and not efficient for use in modern technology. Since observability, is acknowledged as a further developed version of the concepts of monitoring and APM, it is starting to gain recognition and is preferred more in the IT industry.


Observability and Monitoring

Since we have understood what observability is, a person might consider that this concept is identical to monitoring, but the answer is no.

These two concepts are not similar and consist of contrasting differences.

Monitoring is another concept used in computing that is defined as the process of gathering metrics about the operations of hardware and software in an IT environment to ensure everything functions as expected to support applications and services.

The following table indicates the differences between the two concepts of Observability and Monitoring.


Pillars of Observability

There are three different methods used for the collection of data used in observability.

These methods are:

  1. Logs
  2. Metrics
  3. Tracing

These data classes are called the ‘three pillars of observability’.

Logs – Logs is a data class that is a text record which consists of a timestamp indicating the time of each event and a context explaining the event.

Logs are used to obtain a record of the application and implementation of events in the system. This allows the developers to playback the log during instances of troubleshooting and debugging the system.

Logs consist of three formats: plain text, structure and binary. Plain text is considered the most widely used format.

Metrics – Metrics are a type of fundamental/numeric value that is measured over time for applications and the health of the system.

Metrics include data such as timestamp, name, KPI (Key Performance Indicator) and values.

Metrics are used to obtain the memory capacity of an application over a specific period or the latency of an application during high memory usage.

Metrics are structured, which makes it easier to optimize the required storage. Therefore, metrics can be stored for a longer time period.

Traces – Traces are used to record the complete architecture of each user request from the device and back to the user.

These requests are done from the user interface (UI) or a mobile application.Each operation and user request performed is called a ‘span’ that consists of encoded data. A trace consists of one or more spans which are used to identify the reason for a breakdown or a failure in the system.


Implementation of Observability

For the implementation and use of observability, suitable tools and applications are required for purposes such as collection of data.

Four components mainly used for this implementation process are stated below.

1)     Instrumentation – Instrumentation is a measuring tool. Data is collected from containers, services, applications, hosts or any other component present in the system. This component facilitates visibility among the entire infrastructure of the system.

2)     Data correlation – Data correlation functions in processing and correlating the collected data from the systems. Therefore, data correlation functions in enabling automated or selected custom data for visualizations of different time series.

3)     Incident Response – Incident response is a technology that functions in obtaining data regarding failures on technical skills and on-call schedules of the involved development teams.

4)     AIOps – AIOps (Artificial Intelligence for IT Operations) is a machine learning model. AIOps is used in automatically collecting, connecting and arranging incident data. Therefore, AIOps accelerates incident response in instances such as sorting of alert noise and detecting issues that will result in an impact on the system.


The Importance of Observability

Factors that contribute towards the importance of observability:

  • Observability helps developers to understand the system in a much better way.
    The use of observability provides deep visibility to the system, which is also faster. Therefore, this contributes and helps the developer to understand the system and its internal structure faster.

  • Observability helps the developers to figure out errors in the system much quicker.
    Therefore, it would also help the developer in solving the error efficiently. The identification of a problem and the debugging of a system with observability is more efficiently performed.

  • Observability reduces the time spent on meetings.
    Observability helps the developers save time that could be spent on meeting other people that were involved in the development of the system. There would be instances where the developer is required to meet other people involved in the process of system development for collection of information. This method of gathering required information is very time-consuming. Therefore, with observability, the developers do not need to meet the other people involved in this process. As a result, this helps the developers in saving time.

  • Observability helps the developers to accelerate their developing velocity.
    The key responsibility of a developer is to develop more systems. Since observability contributes towards saving time, it supports the developer in developing new ideas. Therefore, as a result, this advantage helps the developers in the IT industry in increasing their developing velocity.

The IT industry is with no doubt considered as a rapidly developing industry in the world. With the development of new technologies, time is one of the most crucial factors in the IT industry. Without a doubt, anyone would prefer a technology that allows them to save more time.

The reasons mentioned above clarifies why ‘observability’ is beginning to gain recognition and more acknowledgement in the industry.


References

Microsoft Academic. (2021). Microsoft Academic. [online] Available at: https://academic.microsoft.com/topic/36299963/publication/search?q=Observability&qe=And(Composite(F.FId%253D36299963)%252CTy%253D%270%27)&f=&orderBy=0. [Accessed 30 September 2021].

Splunk. (2021). What is Observability?. [online] Available at: https://www.splunk.com/en_us/data-insider/what-is-observability.html. [Accessed 30 September 2021].

IBM. (2021). What is observability?. [online] Available at: https://www.ibm.com/cloud/learn/observability. [Accessed 30 September 2021].

SearchITOperations. (2021). IT monitoring. [online] Available at: https://searchitoperations.techtarget.com/definition/IT-monitoring. [Accessed 01 October 2021].

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