CloudFabrix simplifies and unifies IT operations using AIOps
First things first. Observability is inherent as a principle to a system and not something that is instilled. Here, we address observability as an open source-based solution in the context of insightful monitoring within the ITOM landscape.
ITOM is now in the middle of addressing the needs of the expanding and dynamic nature of IT infrastructure as a function. It is no longer about being a monolithic computing stack. It is now beyond monitoring discrete infrastructure elements.
Simple systems are smart enough to run a diagnosis and correct it on their own. But, native-cloud businesses with micro-service architecture and distributed systems are complex.
System admins and ITops analysts were the eyes of systems, services, and apps. It circled around ticketing, resolution, and people dependency. Complex systems depending on people increased the level of failure.
Now, ITOM is about observability that creates a proactive and transparent among complex and modern ecosystems.
Observability provides deeper operational visibility that brings an organization-wide sense of customer experience. For digital transformation and cloud adoption, observability is one of the essential and critical pillars. The monitoring workload is also shifted to development. Apart from these, a few trends make observability a necessity for complex structures.
Observability has been able to respond to these trends. Teams love it, and Observability is slowly gaining attention in the software world. It is able to effectively enable engineers to deliver excellent customer experiences with software despite the complexity of the modern digital enterprise. It is helping modern software teams. On the whole, it has proven to:
Observability, across different use cases, is able to provide full visibility into rapidly scaling infrastructure and applications, anomaly detection, and metrics. It is not yet another monitoring tool.
Monitoring as a tool has detected problems and anomalies in applications. Troubleshooters used to also gain insights into capacity requirements and performance trends over time. But, monitoring would be useless if these systems are not externalized enough.
Observability as a next-generation monitoring mechanism can measure how a system’s internal state can infer external outputs. It develops organizational capabilities of monitoring and analyzing events, along with KPIs and other data. Observability yields actionable insights.
Observability is applied in the following use cases:
With growing complexity, the above use cases hint at the need for inclusion of observability with AIOps.
Traditional AIOps could not be applied for all use cases that challenged the ITOM landscape. It served the immediate purpose but with a high investment of resources and a longer time to value.
AIOps 2.0 with observability in a box provides a quick turnaround with easy implementation. It brings an outcome-driven approach for metrics, events, logs, traces, and alerts.
Traditional ITOM comes with data centers geographically distributed. This adds to the alert noise and ticket volume. The problem resolution time is extended with reactive operations and lack of ability to preempt outages.
CloudFabrix’s Observability-in-a-Box solution is built using open source and open telemetry components. It draws data from across different data streams coming from servers, databases, applications, tools, and services through turn-key integrations across the full DevOps stack. It also includes a lightweight agent deployed that gets automatically provisioned on the host operating systems.
It just gets better with more trained data and resolution models. It uses asset and model intelligence to correlate alerts where connected data relies on feeding information. Recommendations about adding new servers reduce the workload while leveraging the capabilities of Edge AI.
Observability is about providing a unified view across IT operations and systems, which is tied to your business KPIs. AIOps is a part of Observability. AIOps 2.0 is all about intelligence. This element of intelligence is impossible without the insights drawn by observability.
We are referring to:
So, rather than telling you where the problem is, AIOps with observability will tell you where the problem is, how it is solved, and what should be done to avoid it later. This continuous feed of intelligence is only possible when AIOps come together with observability.
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