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.