The emergence of AIOps for enterprises

Since the pandemic, businesses have aggressively adopted the digitalization of all their functions and processes leading to a multi-fold increase in the number of applications within an organization. Today on average, enterprises have 1000+ applications playing an integral part in running an enterprise business. Hence any impact on the applications, directly impacts the business. Moreover, this mesh of applications has made deployments much more complex to manage and monitor. While this much-required journey has enabled enterprises to embrace digitalization, it has put a lot of stress and challenges on the IT operations (ITOps) team who are responsible to ensure all applications and infrastructure adheres to the stated business service level agreement (SLA) and service level objective (SLO). 

Hence, AIOps (Artificial intelligence in IT operations) has become a need and is on its way to becoming pervasive in deployments across enterprises. Having the right AIOps strategy for enterprises is moving from a nice-to-have to a must-have list and is poised for rapid growth and maturity in near future.

AIOps: A Boon to ITOps 

To understand the importance of AIOps, let’s take an example from the financial sector which is highly regulated and mandates strict compliance norms for SLAs including high availability, reliability, performance, security, adherence to data governance laws.  The adoption of digitalization in the financial sector and modernization has resulted in complex interdependent constructs within applications and deployments. This requires the ITOps team to be highly vigilant and efficient, leaving less scope for tolerance of human errors. This is where AIOps plays a key role, enabling ITOps to manage deployments more efficiently leading to better business outcomes by integrating AIOps into DevOps and system management.

AIOps essentially is delivered as a framework or platform that involves creating a data pipeline and data lake by collecting the telemetry information of the entire deployment. It can then be used to generate ITOps related insights across the deployment stack by use of analytics and/or AI and ML techniques. AIOps applies to all components in a deployment stack– Applications, middleware/platform, server, network and storage – that needs an IT operation team to manage and administer it.

Infrastructure Ops is one of the key functions of ITOps. For illustration purposes, let’s take the example of storage infrastructure. ITOps for storage infrastructure plays a critical role in ensuring the SLA and SLO of the business applications, independent of it being software-defined storage running on the cloud or an actual primary storage array which is a part of hybrid cloud deployment. Consider an enterprise level B2C e-commerce service where latency and high availability are very sensitive to the business outcome. For such service to be able to meet its SLA it’s very vital for the underlying storage infrastructure which is hosting the application stack and its data to ensure it is delivering the committed SLA in terms of IOPS (input/output operations per second), throughput, latency, health, availability, and capacity. The continuous management and monitoring of this growing array of storage deployment, while ensuring compliance can be very stressful and challenging for the ITOps team. AIOps for storage management comes to the rescue by providing the following capabilities:

  • Anomaly detection to reduce mean time to recover 
  • Proactive support for storage arrays
  • Workload simulation and placement insights
  • Root cause determination insights
  • Automated remediation insights
  • Storage security posture monitoring and correlation
  • Forecast growth rates for better planning

AIOps will empower personnel beyond ITOps

A well-implemented AIOps for infrastructure management will not only benefit the on-the-ground ITOps team but also infrastructure and operation leaders and decision makers. They will have access to insights required for proactive resource planning, optimizing budget via insights on cost-optimized deployments, suggesting workloads migration strategies for hybrid cloud, plan asset management strategies, among others. It also benefits the security operations team with insights that help in better assessing risk and protecting corporate assets. It overall fosters collaboration between teams and enables them with the bandwidth to work on more innovative and strategic projects. Moreover, AIOps indirectly builds more confidence in the sales team on the business application allowing them to aggressively scale up the businesses. 

Finally, organizations must prepare for the AIOps transformation not only to ease and build efficiency in their IT operation but to also establish an advantage in today’s intensely competitive marketplace. Advantages of a well-rounded AIOps strategy for an enterprise can benefit various teams all converging towards business enhancement. However, it is important that business leaders understand that AIOps is not a magic wand and is still evolving with the promise of rapid growth and maturity. Hence, they must take that into consideration when strategizing and deploying AIOps in their enterprise.

The article has been written by Sandeep Patil, STSM, Master Inventor, IBM Storage and Mayur Shah, GM & Global head – Engineering, Offering development, DC – Hybrid cloud, Wipro Limited

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