Oct 13, 2020. By Aleena Mathew
IT enterprise and software driven product development are increasing in a large scale. Most of the IT infrastructure services are provided from distant geographic locations. In which most of the services are distributed functions. As services are distributed, managing IT environment holistically is becoming a challenging task. Moreover meeting customer requirements and fulfilling their requisites is also important. To meet these end-user requirements, IT service providers and business organizations must streamline there performance . This helps to improve the stability of the IT infrastructure even though having a complex IT system. To achieve this, we need to closely observe and monitor the metrics and datasets or API which are related to the system performance.
In the past or in traditional times, IT systems were monitored with least capabilities which was just limited to maintain the availability and performance of the application and architecture. Systems where not capable of observing, rather they where for capturing, storing and presenting of data. This generally meant that human operators were responsible for providing an outcomes on data set and also for providing predictive analysis of data set. Human predictive analysis or outcomes are always not reliable, as there is a high risk of an error factor. Human errors can also be considered as a reason for data breach.
In the present scenario, availability and performance wont alone drive the business growth. Moreover, the human error factor should also be limited. Holistic approach should be brought in. Most enterprisers have identified the need for a change in monitoring IT systems, that is, moving from monitoring to observing. Moreover, many IT teams are also facing a great difficulty in overload of the large volumes of metrics. In many IT organizations, a huge volume of metrics are being generated, in which most of the metrics are not given proper attention, which may lead to severe problems. So, we need a next level of IT monitoring. That's where Observability makes the way. Lets settle up and understand what does this observability and monitoring means.
First, observability is not just a buzz word for monitoring. Second, observability isn’t just about collecting as many logs, events, metrics. Monitoring and observability are distinct concepts. Monitoring helps in understanding what is actually happening. Whereas Observability explains why something is happening and provides actionable insights. It collects monitoring data and enriches this data. Observability refers to the process in which IT system data is given a more meaningful inference. This inference can be achieved by the use of AI analytics. Much more, it helps in observing and tracking the normal behavior of the IT system and helps in identifying unwanted event which has occurred that eventually leads to the downtime of the system. Moreover, with the AI capability on board, the observability of the IT system is automated and unwanted manual intervention can also be avoided. Therefore, the more observable a system is, the more it will enable teams to understand, manage, and enhance its performance. With this observability in hand, IT teams can get a deep visibility of their system.
AI based Obseravability:
Algomox Cognitive Observe Manager (COM) is an AIOps capability that observes the health of different infrastructure elements, applications and services. It collects structured and unstructured data from different infrastructure sources including physical machines, virtual machines, containers, servers, databases, applications, and business services. It uses deep learning techniques to detect events, and anomalies, and complex event processing to pin point accurate IT problem.
The key insights of observability lie in the collection of log and KPI. We need these insights to be analyzed deeply and correlated together to identify any case of real time incidents or events. Identifying real time anomalies or events and charting them wont alone help. What really needs to be identified is, what actually caused the problem at first place and identify the incident. And that's what exactly Algomox (COM) does in observability. The platform helps in identifying root cause problem, that is, it does root cause analysis and identify the root problem and also recognize the incident, that is, incident recognition. When IT system management comes in a large picture, it is complicated to understand, what the actual issue is. It takes a lot of time and effort to understand the actual cause. By the use of the incident recognition mechanism the process of identifying the incident is saved up to a great extent. This also helps in speeding up the remediation process .
With the best and evolved capabilities of observability on board, which evolves around AI, a power packed combination of AIOps (AI for IT operations) and observability is provided, which is the path way for every IT enterprise.
To learn more about Algomox AIOps please visit our AIOps Platform Page.