Jun 3, 2021. By Aleena Mathew
The wave of digitization hit almost every aspect of IT systems. This change brought in the need for the IT team to completely shift from their traditional IT systems to adopting modern digital technology such as the cloud platform, serverless computing, edge computing, and so on. But the adoption of these new technologies brought in a lot of pain to the IT operators as they could not monitor the entire IT system holistically. They had to identify if there were any abnormalities in the IT system and take preventive actions accordingly. There may be manual efforts in some areas that led to a lack of productivity and high operations costs. The above situation became hard, and just the concept of monitoring will not be sufficient here. That's where the implementation of advanced observability termed AI-based observability came into the picture.
With issues that prolonged with the adoption of the digital era, the time of change in the concept of monitoring became a must, and that's where AI-based observability took its place. The implementation of observability brought in a new shift into the entire IT organizations. AI-based observability helped to achieve end-to-end visibility of the IT organization in the big picture. With observability in place, the data collection process became more simple and easy. This allowed IT operators to process data from multiple data sources, whether the data is structured or unstructured. Moreover, the analysis helped to correlate every business and IT metric that enabled them to identify meaningful insights. Apart from that, with observability, the process of AI-based anomaly detection was made possible. In this way, multivariate KPI and cross-domain log anomaly detection became easy. This methodology helped provide intelligent alerts and event detection that helped reduce false positives and proactively resolve any issues that occurred.
With the benefits in place, the issues faced with traditional monitoring were under control. But, having these systems in place did not show benefit in the long term. IT operators needed to change the structure continually and formatting to adjust to the emerging trends in data and other resources. This became a time-consuming and repetitive task. Observability-as-Code took its path from here.
Observability As Code:
The need for observability is significant with the increased use of microservices. Having multiple monitoring tools and dashboards to change based on requirements was very hectic. This is the reason for treating observability as a code.
Observability as Code enables DevOps teams with consistent practices to observe the state and behavior of the entire IT system in different environments. The implementation of observability-as-code facilitates faster and better deployment across the domain. The idea behind the concept of observability-as-code is that the development, deployment, configuration, and testing of each component in observability will be shared as a code and the outcomes of these phases such as alerts, events, and anomalies events. Having observability as a code enables the automation of most repetitive tasks that are done manually. This automation ensures that there are no manual errors that will occur during the configuration process. Moreover, as the observability is transformed into Code, there is much ease in deployment. Also, dashboards that are configured will provide intelligent alerts during integration and deployment (CI/CD). The observability-as-code enables to audit changes and roll back if any issues are found. Along with all these capabilities, we can identify actionable insights from metric data across all environments.
With the feature of observability as Code in place, IT operators can easily tackle the process of manually working on the configuration and implementation of components. All these repetitive tasks will be automated, where we can avoid configuration mistakes or long deployment times. Let's look into some of the benefits of observability-as-code.
Benefits of observability as code:
With observability-as-code, IT teams can use DevOps techniques to manage the observability lifecycle. Some of the benefits of this methodology are:
i. Automated and repeatable: The basic idea of observability as code is to construct all possible components as code. This helps in the automation of most repeatable tasks, such as the configuration, setup, debugging, and fixes. No manual attention is needed here for further configuration, and also manual error can be avoided. It helps in saving a lot of time.
ii. Effective DevOps team collaborations: As the development and integration come in an automated manner at the CI/CD part, the DevOps team collaborations are also improved.
iii. Enabling Dashboard-as-a-code: The main part of observability lies in having a dashboard interface to view these outcomes such as alerts, events, and anomalies. Having to refactor the dashboard for each change needed is a hectic task. Having them automated in the form code helps in the automation and ease of deployment.
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