Three monitoring stages on the observability road

Three monitoring stages on the observability road

To reach the advanced level of observability, it is necessary to monitor the evolution from reactive to proactive (or predictive), and finally to normative monitoring. Let us discuss what this evolution includes.

 

It is now generally accepted that monitoring is only a subset of observability. Monitoring shows that there is a problem with your IT infrastructure and applications, and observability helps you understand the cause, usually by analyzing logs, metrics, and tracking. In today's environment, a variety of data streams are needed to determine the "root cause" of performance issues, the holy grail of observability, including availability data, performance indicators, custom indicators, events, logs/tracking, and events. The observability framework is built from these data sources, and it allows operations teams to browse this data with confidence.

Observability can also determine what prescriptive actions are taken with or without manual intervention to deal with or even prevent critical business interruption scenarios. To reach the advanced level of observability, it is necessary to monitor the evolution from reactive to proactive (or predictive), and finally to normative monitoring. Let us discuss what this evolution includes.

Not a simple thing

First of all, if you look at the status quo of joint IT operations, you will find the challenges. Infrastructure and applications are scattered in staging, pre-production, and production environments. In the enterprise and in the cloud, IT operations teams are continuously involved to ensure that these environments are always available and meet business needs. The operations team must deal with multiple tools, teams, and processes. People are often confused about how many data streams are needed to implement an observability platform, and how to make the business and IT operations teams within the enterprise follow a framework to improve operational optimization over a period of time.

In order to mature the monitoring work, go beyond the indicator dashboard, and enter this observable state, it usually develops in three stages. Reactive, proactive (predictive) and prescriptive. Let's see what these are.

 

The first stage: Reactivity monitoring.

These are monitoring platforms, tools, or frameworks that set performance baselines or specifications, and then detect whether these thresholds have been breached and issue corresponding alarms. They help determine the optimal configuration needed to prevent the performance threshold from being reached. Over time, as more hybrid infrastructure is deployed or deployed to support more and more business services and expand the scope of the enterprise, the pre-defined baseline may change. This can cause poor performance to normalize, not trigger an alarm, and cause the system to completely crash. Then, companies look forward to proactive and predictive monitoring to alert them in advance of performance anomalies that may indicate an impending event.

 

The second stage: active/predictive monitoring.

Although these two words sound different, predictive monitoring can be considered a subset of active monitoring. Active monitoring enables companies to view signals from the environment, which may or may not be the cause of business service interruptions. This enables companies to prepare remedial plans or standard operating procedures (SOPs) to overcome zero priority incidents. One of the common ways to implement active monitoring is to provide a unified user interface for the "manager of the manager". The operations team can access all alarms from multiple monitoring domains to understand the "normal" behavior and "performance bottleneck" of their system. "behavior. When a certain behavior pattern matches an existing machine learning pattern, indicating a potential problem, the monitoring system triggers an alert.

 

Predictive monitoring uses dynamic thresholds for the newer technologies on the market without first-hand experience of how they should be implemented. These tools then understand the behavior of the indicator over a period of time and issue an alert when the standard deviation is noticed, which can lead to outages or performance degradation that end users will notice. You can take corresponding actions based on these alerts to prevent incidents that affect your business.

 

The third stage: Normative monitoring.

This is the final stage of the observability framework, and the monitoring system can learn from events and remediation/automation packages in the environment and understand the following.

• Which alarms occur most frequently, and what remedial actions are taken from the automation package for these alarms?
• Whether some of the triggered resources belong to the same data center, or the same problem seen in multiple data centers, may lead to misunderstanding of the configuration baseline.
• If an alert is seasonal, it can be ignored at a later stage without unnecessary automation.
• What remedial measures should be implemented for new resources introduced as part of vertical or horizontal expansion.
• The IT operations team needs appropriate algorithms to correlate and formulate these plans. This can be a combination of ITOM and ITSM systems’ feedback to the IT operation analysis engine to establish a standardized model.

Looking to the future

Monitoring is not observability, but a key part of it. Starting from reactive monitoring, it will tell you when the pre-defined performance threshold is breached. As you bring more infrastructure and application services online, monitoring needs to shift to proactive and predictive models that analyze larger sets of monitoring data and detect anomalies that may indicate potential problems before service levels and user experience are affected .

 

Then, the observability framework needs to analyze a series of data points in order to determine the most likely cause of the performance problem or interruption scenario within the first few minutes of detecting the anomaly, and then start working to remedy the problem before entering the war room/situation analysis call Performance issues. The end result is a better user experience, a system that is always available, and improved business operations.