CASA Software reveals top five reasons SA businesses require AIOps-observability

Michael Brink, CTO, CASA Software.

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According to CASA Software, the demands of today’s digital economy augmented by the increasing complexity of modern application architectures have made the role of IT operations more challenging. 

Michael Brink, CTO of CASA Software, notes AI and machine learning have emerged as a means of relieving some of the manual interventions required. “A recent survey of more than 100 IT professionals found respondents overwhelmingly believe AI for IT operations (AIOps) is the future of IT operations, with increased automation and faster remediation among the key benefits. It should be noted that these days, the term AIOps is used interchangeably with observability,” he says.

Reason number one:

Proliferation of monitoring tools makes analytics challenging.

New distributed and microservice-style architectures are expected to introduce more complexity and present new monitoring challenges. The use of disparate tools makes it extremely difficult to obtain end-to-end visibility across the entire business service or application and it makes it near impossible to be able to quickly correlate and analyse multiple application performance metrics to solve complex emerging problems before they impact end-user experience. According to Gartner, domain-based monitoring tools provide insight into issues within their own realm, but typically are unable to present a holistic view across a digital service. Infrastructure and operations leaders need to use AIOps and digital experience monitoring to deliver a primary, single pane of analysis across all domains underlying the service.

Collecting and correlating data from disparate sources so it can be effectively analysed is the first step in enabling AIOps. Having these end-to-end insights across the entire application stack, from back-end infrastructure to customer behaviour and performance, will help you to ensure the optimal customer experience, every time.

Reason number two:

The sheer volume of alerts Is becoming unmanageable. With thousands of monthly alerts that need to be managed, coupled with dwindling resources, it’s no wonder the use of AI and machine learning is becoming a necessity. AIOps can help reduce the impact of these issues by decreasing downtime, monitoring tool sprawl as well as the time expended on analysing alerts.

Reason number three:

Delivering superior user experiences requires predictive analytics. The reality is that in the digital age, every business is one poor user experience away from a lost customer, making it understandable why businesses place such a premium on supplying a superior customer experience. According to the survey, delivering superior user experiences with predictive analytics is among the top three most important business outcomes. In light of this, it is hardly surprising that predictive analytics is the most sought-after AIOps capability.

AIOps makes complex automated decisions by collecting and analysing data. By leveraging this data, it can predict probable future events that may impact availability and performance and even proactively remediate those before they become an issue. These predictive analytics go beyond what is possible by humans alone and help make the case for AIOps adoption.

Reason number four:

The expected benefits of AIOps are enormous. Additionally, IT professionals believe AIOps will lead to increased efficiency, faster remediation, improved user experience and reduced operational complexity. This is expected to be largely obtained through AIOps automation of data analysis, root cause and predictive insights across the entire toolchain.

How can AIOps and machine learning help increase automation across your toolchain? According to the survey, 97% of IT professionals believe that AIOps will deliver actionable insights to help automate and enhance overall IT operations functions.

You can:

• Automate the analysis of the event with faster production of log and metric data and more accurate root cause analysis.
• Receive predictive insights that are informed by the entire toolchain, not just one tool or data source.
• Break down silos within the toolchain.
• Reduce human resources needed for time-consuming analysis and remediation.

Reason number five:

As monitoring and data analytics challenges mount, AIOps will play a key role in enabling new efficiencies for ITOps teams. The overwhelming majority of survey respondents (90%) agree that AIOps is very important for the future of IT operations. In addition, 97% of executives are investing in building or launching big data and AI initiatives. Businesses that want not merely to survive but to rather thrive in today’s digital economy must consider the use of AI in IT operations.

Brink concludes: “Now is the time to start assessing and implementing AIOps-powered solutions to drive the superior user experiences your customers have come to expect. To learn more about AIOps, contact CASA Software. Our highly experienced and skilled team of technology professionals are ready to advise on how to kick-start your AIOps journey.”