Observability is a hot Subject right now, stirring a great deal of debate among IT admins. This report brings some clarity and will shed some light on the topic – “What is the difference between monitoring & observability?”.
Enterprise IT is complex as IT infrastructure solutions are delivered from enormous datacenters located at remote locations. Companies consume these services across layers of platforms and infrastructure services, as distributed functions like containers and microservices. Consumers expect rapid feature improvements through new releases via the world wide web (www).
To fulfil these needs, IT service providers and business organizations need to streamline performance and improve stability and predictability of backend IT infrastructure operations–involving the inherent complexity of their IT systems. To do so, they have to track and closely observe metrics and datasets associated with infrastructure functionality so as to maximize the system’s performance & efficiency.
Observability is the ability to infer internal conditions of a system based on system’s external outputs. In control theory, observability follows a direct conceptual mapping to controllability, that’s the capability to control the internal states of a system by controlling outside inputs. In practice, nevertheless, controllability is hard to evaluate mathematically; therefore, system observability is the method for evaluating outputs to achieve conclusions about the internal states of the machine.
In enterprise IT, infrastructure components are distributed functions through abstract layers of virtualization & application/software. This environment makes it hard and impractical to analyse and compute system controllability.
Rather, monitor and common practice is to observe infrastructure performance charts and logs to comprehend the operation of hardware systems and components. Advanced log analytics and AI (AIOps) evaluate events and incidents associated with hardware performance so as to predict the potential effects on system dependability. Then, your IT team can proactively adopt corrective measures to reduce the effect on end-users.
What is monitoring?
Network monitoring is the ability to infer a system’s internal condition. It can also be defined as the actions involved with observability: observing the quality of system performance over a period. Network monitoring describes the functionality, wellness, and related characteristics of system’s internal conditions. In business IT, monitoring refers to the procedure for distributing infrastructure log metrics information into actionable and meaningful insights.
Monitoring of a system includes the infrastructure log and performance characteristics associated with components that can be inferred as metrics. Network Monitoring tool analyse the infrastructure metrics to provide actionable insights.
What Makes Application Observability Important?
To run any application process, there has to be some form of comments in the code. It doesn’t make any sense to push changes without knowing if they make matters worse or better. To the rescue comes Monitoring & Observability as part of the Pyramid of Power, and Analysis to provide actionable intelligence.
Despite its current popularity, observability is not at all new. Logging has been around since the dawn of programming, which makes implementation visible by writing out messages that are useful.
Of course, it’s possible to track a service endpoint, for instance, even if it does not make itself observable, by simply calling it at every 10 seconds and measure success, failure & response times (also known as synthetic monitoring).
The most difficult kind of observability is distributed tracing within and between programmed IT services. Making use of this form of observability in an effective and efficient way requires strong expertise and an understanding of the underlying principles of distributing requests that flow between providers.
The Relationship Between Tracking & Observability
Simply put, observability is when data is made accessible from within the system which you want to track has been achieved. Tracking is the actual task of showing and collecting this information. There is one more important term when using the” observability v/s monitoring” conversation and that term is “investigation”.
If you are observable, then I’ll understand you.
Once you’ve made the system observable, and once you’ve collected the data using a network monitoring tool, you must perform analysis either manually or mechanically. Without meaningful analysis you have fallen short of the whole purpose of creating and performing tracking in the 1st place. The greater your analysis capabilities, the more valuable your investments at observability & tracking become.
Observability & Monitoring with Motadata
Motadata is soon going to launch its AI powered network monitoring tool which includes observability platform along with application performance management (APM), baselining, forecasting, predictive analytics, anomaly detection etc. Like Gartner, which reports a whopping 25% increase in the number of end user inquiries on AIOps platforms, we at Motadata have been receiving increased interest from our customers & partner community who’re getting challenged everyday with the increasing complexity as well as volumes of machine data that is beyond the human’s scope to manage. In our last blog we outlined some of the features which will be a part of the next release. Stay tuned for more updates!