This need for AIOps was simmering conveniently and gradually reaching its threshold when the pandemic suddenly hit the world, pushing organizations into remote work. The sudden, global-scale change raised challenges for IT operations teams to monitor and detect incidents in a distributed environment and maintain cybersecurity and compliance.
While the pandemic pushed some organizations into the reality of remote work, others were already on their way to digital transformation. Digital transformation aims to make business processes more automated, agile, efficient and streamlined so information and applications are available throughout an organization for rapid decision-making and innovation.
Digital transformation puts the same pressure on IT operations as remote work did- to ensure IT operations proactively identify and resolve issues before they affect internal development teams or customers.
Finally, a digital era of hybrid IT infrastructure renders traditional operations methods obsolete. Traditionally, IT teams scaled alongside the IT infrastructure, from standalone systems to vertical scaling through distributed computing. However, virtualization led to a whole other beast of microservices and ephemeral systems with containerized scaling.
And we arrive today when organizations simply produce too much data for humans to monitor using legacy tools.
How DevOps Helps Organizations
Here are the core benefits of DevOps for an organization:
- Customer centricity – It’s easy for developers to focus too much on the software project and too little on the customer’s needs. Even the best-developed software can fall short of customer expectations in case of miscommunication. All a customer needs is a functional product to solve their challenge, and that’s where DevOps helps focus.
- Faster time-to-market – With agile development methodology, development teams have been able to build software products fast in the last decade. However, IT operations teams fell behind, so products weren’t shipped at the same speed as they were built. DevOps bridges the gap between development and operations to accelerate time-to-market.
- Simple development process – DevOps encourages focusing on one development area at a time instead of shipping a big product release. With the former approach, it’s easier to troubleshoot bugs and issues than when heavy code has been installed.
- Sleek automation – Teams who traditionally rolled out big software releases never had to think about automation. However, when the same development processes are executed frequently and repeatedly, automation makes sense.
- Streamlined responsibilities – DevOps rarely only affects the development and operations teams. It also impacts other teams at various points in the pipeline who contribute to shipping the software, allowing organizations to streamline responsibilities and maintain a competitive advantage.
So, if DevOps helped organizations in a myriad of ways, why the need for AIOps?
How DevOps Falls Short Today
Due to all the reasons that landed us here, discussed in the first section, DevOps falls short. However, AIOps doesn’t replace DevOps, and it only augments it. DevOps falls short because of the volume of data that the modern organization produces in an unstructured format from various siloed systems.
DevOps fails to maintain a secure and compliant organization with the many variables in the modern IT environment and the pace of change. In modern enterprise, without the application of artificial intelligence, operations would once again fall behind the development and reduce the pace of innovation and progress.
DevOps doesn’t account for the need for observability in the modern organization and ignores changed requirements for open telemetry in operational environments. In short, DevOps still innocently assumes operations will be able to keep up with the speed of innovation and development.
AIOps can automatically map dependencies and relationships within an IT environment, centralize access to operations data, proactively identify incidents, automate incident response and escalate only when necessary, reducing daily conundrums to meaningful signals that must be addressed by ops teams.
Why DevOps Needs AIOps
The market size of AIOps platforms is projected to reach $19.92 billion by 2028, up from $2.83 billion in 2021 at a CAGR of 32.2%. As per a report by Dell Technologies, titled “The State of Autonomous Operations: Why IT Automation is Driving Digital Transformation Success”, many organizations lag in adopting AIOps. The report also found that nine in ten organizations struggle with their IT staff spending undue time on repetitive tasks that could otherwise be automated.
DevOps needs AIOps to handle the evolved needs of operations teams today when complex IT environments proliferate across industries, demanding streamlined monitoring, observability, and incident response.
Top AIOps use cases include:
- Noise reduction – One of the goals of AIOps is to relieve DevOps teams of the burden of tirelessly sifting through noisy events data and jumping on every alert for fear it might be the big one. Observability through AIOps can direct DevOps teams to the most critical alerts and incidents that need their valuable expertise.
- Quick detection – AIOps eliminate the need for manually tracking alerts in each corner of the IT environment to trace the impact of an incident or find out the root cause. It facilitates quick incident detection by contrasting metrics against historical data and, more sophisticatedly, setting dynamic baselines by identifying deviations in behavior.
- Root cause analysis – Change is constant and continuous with DevOps, so it’s urgent and critical to know where to look when an incident occurs. AIOps save crucial time in root cause analysis and can even provide action steps for known incidents.
- Incident response – AIOps leverages ML algorithms to consistently learn from past incidents so repetitive incidents can be automatically acted on.
- Events correlation – Correlating key incidents is what allows for noise reduction. AIOPs enable event correlation by identifying time-series metrics and symptoms for quicker resolution.
AIOps augments DevOps so that development and operations teams can work in tandem to create business outcomes that maintain your organization’s progress, security, compliance, and readiness.
The AIOps of the future are even more advanced with Robotic Data Automation Fabric. Read more about the Future of AIOps here.