Reduce Noise and Speed Root Cause Analysis with Alarm Analytics: The importance of consolidated alarms across applications, infrastructure, and network


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In the world of software development, a high-quality user experience requires a product that is both highly available and highly reliable. And, with a plethora of options in every industry, today’s users demand a high-quality experience. With that in mind, development organizations must evaluate and implement modern processes and methodologies that support the development and maintenance of products with these qualities.

One such approach is AIOps. AIOps, or artificial intelligence for IT Operations, is an IT approach in which big data is leveraged in conjunction with machine learning algorithms to enable efficient and effective application and infrastructure support. AIOps is made easier with the use of a mature AIOps solution, such as Broadcom’s DX Operational Intelligence. In this blog, we will cover an overview of this platform and dive deeper into one of DX Operational Intelligence’s most important and groundbreaking capabilities, Alarm Analytics.

DX Operational Intelligence

DX Operational Intelligence utilizes machine learning and artificial intelligence to assist IT Operations teams in making faster and more informed decisions regarding user experience and system support.

DX Operational Intelligence works by ingesting both structured and unstructured data (e.g. logs, topology, metrics, alarms) from applications, infrastructure and networking components within an organization’s digital chain. This diverse data set is then correlated and analyzed by various machine learning algorithms to produce targeted analytics, yielding a deeper understanding of overall system health. In doing so, Broadcom’s platform provides insights across the entire digital chain in a centralized (or “single pane of glass”) fashion. It is this “single pane of glass” view that enables operational efficiencies in the processes of root cause analysis and incident remediation.

Consolidated Alarms Across the Stack: Alarm Analytics

One of the more critical capabilities furnished via DX Operational Intelligence is known as Alarm Analytics. Let’s consider how this feature functions and the distinct benefits an organization can attain from its usage.

Alarm Analytics

Traditionally speaking – application, infrastructure and networking components were all monitored in a siloed manner through the use of individual fault and performance monitoring tools. Due to the lack of a centralized monitoring platform, the monitoring alert data generated by these components required evaluation in a disconnected and separated fashion.

With Alarm Analytics, Broadcom’s solution streamlines the processes for performance monitoring and alarm evaluation. By leveraging the data lake utilized by DX Operational Intelligence, Alarm Analytics provides IT Ops teams with a consolidated view of alarm data across all system data sources. This consolidation results in access to correlated insights traversing an organization’s entire digital stack. With Alarm Analytics, IT personnel have access to built-in capabilities for viewing alarm data across device types, severity levels, services, and more, enabling these teams to derive as much value as possible from alert information.

The Benefits of Consolidated Alarms

So now that we know what Alarm Analytics is, it’s important to understand the specific benefits it brings to an IT organization. Consider the following.

  • Consolidation of alarm data reduces loss of context – When trying to locate the cause of a problem within a system, log and alert data can often prove critical. With that said, the distributed and complex nature of modern software environments often makes it difficult to identify the component responsible for the problem.

Traditionally, this has led to IT personnel jumping from monitoring tool to monitoring tool to try and find the source. Centralizing alarm data from the various components that make up the system eliminates the need for IT folks to constantly switch between monitoring platforms when an issue occurs, saving time and reducing the loss of context that (inevitably) occurs when doing so.


  • Correlation of alarm data reduces noise – One of the biggest challenges when utilizing alarm data is sifting through the “noise.” When not done effectively, organizations waste time and resources looking into low-quality alerts that are unrelated to a specific issue an IT team may be trying to evaluate.

Alarm Analytics helps to reduce this noise by correlating alarm data across the various products in the digital chain, clustering alarms to make it easier for IT personnel to root out alerts that are contextually irrelevant to the problem at hand. This, instead, allows IT Ops folks to focus more completely on only problematic and related alert data that requires further analysis.


  • Insights derived from correlated alarm data helps to accelerate the process for determining root cause – Root cause analysis is the process by which developers and IT personnel identify the cause of an issue within a system at the lowest level. Alert data often plays a crucial role in this process. More specifically, the insights derived from correlated alert data plays a crucial role in this process.

When IT teams manually analyze this data in a disconnected and decentralized fashion using multiple monitoring tools, the process of root cause analysis often proves to be lengthy and inefficient. In contrast, when alert data is centralized and machine learning models are leveraged to automate the analysis process, the root cause can be determined more quickly and with greater accuracy. Alarm Analytics does so, in part, by providing functionality to correlate alarm data in a manner that allows teams to apply context. This reduces the time it takes to identify and resolve the problem at hand, thereby limiting the impact that system quality issues have on the end user.

The Future of AIOps in IT Operations

As time goes on, the use of AI and machine learning will play a more significant role in IT operations (and for good reason). With AIOps – and, more specifically, centralized and correlated alarm data – IT organizations can save time and resources by reducing alert noise and increasing the efficiency of the root cause analysis process. In doing so, IT Ops personnel contribute to the production and maintenance of highly available and highly-reliable software, leading to more satisfied (and loyal) end users. And, in turn, helping to ensure business viability for years to come.


To learn more about DX Operational Intelligence and the various capabilities and benefits the solution offers, check out our new virtual tour.

Scott Fitzpatrick has over 5 years of experience as a software developer. He has worked with many languages, including Java, ColdFusion, HTML/CSS, JavaScript and SQL. Scott is a regular contributor at Fixate IO.


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