Author: Ranjit Rajagopalan
The quest for modernisation has led to an increasingly hybrid IT landscape.
Modern applications are more likely to run on a myriad of nodes, pods and containers, using the services of a public cloud provider. At the same time these applications must integrate with critical legacy software hosted within an on-premise infrastructure. Network topology adds another layer of complexity to IT Operations (ITOps), with a combination of physical and virtual networks operating different protocols.
ITOps teams are left with the unenviable task of servicing this complex system and deriving actionable insights from the vast array of diverse monitoring data emanating at microsized-intervals.
A data driven approach is needed to address this problem. At CGI, we’ve identified Artificial Intelligence Operations (AIOps) as a key industry trend that has the potential to significantly contribute to overcoming current ITOps challenges. Here’s why.
The core challenges facing ITOps teams today
The main challenges, as always, relate to people, processes and technology:
- Operational excellence: there is added pressure for operational efficiency, due to the need to reduce total cost of ownership (TCO) under tighter regulations. We require highly productive, multi-skilled ITOps engineers. They must be able to collaborate and apply innovative techniques. Site Reliability Engineering (SRE) is one of the fastest growing roles in IT.
- Overcoming rigid processes: We now need a more proactive approach to IT Service Management (ITSM). Processes need to be less siloed and more nimble to allow engineers to respond more quickly and precisely. A transition to an agile DevOps methodology supported by automation of repetitive tasks will help.
- Real-time observability: ITOps have to derive meaningful insight from an enormous volume of data coming in at high velocity. This can be tackled by having a centralised data model residing in low-cost distributed storage, with sophisticated algorithms harnessing insights and presenting it in a simplified manner.
How we’re using AIOps at CGI to tackle these
At CGI, we are constantly researching industry trends and working with key technology vendors in order to stay one step ahead. Our CGI members are always trained and prepared to support our clients.
As mentioned, we recognised the role that AIOps can play in overcoming our ITOps challenges. By leveraging key vendor partnerships, we have developed a platform that sets us up in the journey towards AIOps.
Our platform is not just capable of ingesting the big data of the IT operations environment. By using ML technologies, such as anomaly detection algorithms applied to real-time streaming data, we can also surface these insights quickly and take automated remediation actions.
Our service delivery model has also been fine-tuned to work optimally with our platform. We are a team of technologists who are challenging ourselves to leveraging the benefits of emerging technologies such as advanced analytics, cybersecurity and automation.
It must be said that these developments owe thanks to the crucial cultural support of our company. Our journey towards AIOps would not have been possible without CGI’s foundations, frameworks and culture of innovation.
The ultimate benefit? Enabling our clients to achieve better outcomes
We believe CGI’S AIOps capability will greatly enhance our operational excellence, leading to even better outcomes for our clients.
By improving the key metrics of IT operations, such as availability, saturation, performance and responsiveness, our solutions will enable the organisations we work with to go beyond achieving Service Level Indicators/Objectives/Agreements. They’ll be able to focus more intently on what matters the most: providing a better service for their customers.
Interested in learning more about the AI technologies we’re employing at CGI to maximise our operational efficiency? Shoot me a message!
Check out our careers page to find out how you could be working alongside me on AIOps at CGI.
