Is AIOps Set to Bring Performance and Resilience to Complex Enterprise Tech Ecosystems?
Every year, enterprise IT spending sets new records as businesses attempt to win over customers with digital supremacy in both their consumer-facing and internal operations. Gartner predicts that nearly USD 4.6 trillion will be spent on enterprise IT initiatives in 2023.
From redefining their operational landscape to setting up new revenue streams, enterprises will continue to leverage technology as a key growth pillar. As more software fills the room, new challenges in operational complexity begin to occupy boardroom discussions across industries.
How Can Enterprise Tech Complexity Be Tamed?
The solution to containing and managing enterprise technology ultimately lies in developing a deeper understanding of how internal components behave within an application and subsequently developing a performance-oriented architecture to support critical growth. This is where AIOps can make a significant impact in guaranteeing better performance and resilience to complex enterprise tech ecosystems.
What Does AIOps Bring to the Table?
Let us explore four ways in which AIOps can transform the performance dynamics of enterprise applications today:
Contextual Analysis of Incidents
Occurrences of technical issues are a usual sight with any digital application, but the success of an organization’s digital initiatives depends on how well they can recover from the problem with minimal damage and disruption to the end-user experience. This is where AIOps has a significant impact.
With AIOps solutions, enterprises can deep dive into the inner echelons of an incident, understand the root cause by capturing background data intelligently, and provide the exact context behind its occurrence to decision-makers. This allows for faster resolution and minimal disruption of the service for end users.
Autonomous Remediation
Adding more to the previous point, AIOps tools provide a wealth of knowledge about failure incidents. Such insights can be used to model remedies which can then be automated for occurrences of incidents with similar behavior in the future. This ability of knowledge recycling allows enterprises to eventually move into a technology architecture that has the capacity for self-healing and ticketless maintenance.
Additionally, automated remediation allows engineers to concentrate on newer threats rather than having to reinvent the wheel for repeat incidents.
Unify Coverage
Traditional IT monitoring tools worked in siloes, with each instance handling a specific application or module. Over time, the enterprise technology stack has evolved into a complex web of interconnected and integrated ecosystems comprising networks, servers, applications, infrastructure, and much more. The conventional fault monitoring approach fails to recognize the challenge of dependencies within application architectures.
AIOps breathes a new lease of life into large and complicated enterprise technology streams by eliminating siloed monitoring and rather focusing on delivering a holistic end-to-end coverage of the entire IT landscape of the business. It allows a friction-free collaboration between different teams and allows them to jointly investigate and formulate action plans to manage incidents across integrated systems.
Event Agnostic Operations
In the past, monitoring and observability systems have relied on the highly system-specific acquisition and analysis of data within enterprise systems. They collect first-party data directly from system outputs which limits their ability to uncover the true cause of incidents as the IT ecosystem evolves and expands eventually.
AIOps brings forth an agnostic approach that caters to all incident events and collects data from systems spread across domains. It can bring about data from logs, traces, event controllers, monitoring tools, security frameworks, data exchanges, and pretty much all modular components within a large enterprise technology network. AIOps can then leverage artificial intelligence and machine learning to standardize, process, and build relationships between different data sets and ultimately provide more refined and granular insights across the length and breadth of the organization’s digital landscape.
This helps organizations to manage their large technology operations easily over a larger timeline — thanks to the ability to ingest and manage diverse data sets from even newer business systems they may eventually add to their operational kitty.
AIOps as the Key Pillar for Minimizing IT Complexity
Enterprise technology has grown so big today in its coverage of business functions that some companies find themselves in a situation where they need more people in IT than in their core business operations. The success of internet-powered digital channels depends heavily on their ability to scale up performance in alignment with consumer dynamics and demand. Complex enterprise technology stacks can derail efforts in this direction and can degrade performance significantly, resulting in bitter experiences for consumers.
AIOps become a core pillar in enabling enterprises to minimize their IT complexity while ensuring fault tolerance and resilience are never compromised. It doesn’t matter if you are an SME or a big corporation as modern IT stacks constantly evolve and add more systems to their arsenal in the quest to serve customers better.
Having a fundamental framework for AIOps established at the earliest is crucial for sustained evolution with disruption-free digital experiences. This is why appNeura designed the AI-powered Digital Experience Monitoring and APM – AIOps solutions to help enterprises:
- Predict app failures in advance
- Initiate remedies, and
- Eliminate disruptions to consumer experience across their digital channels.
Get in touch with us to know more.