Here’s How CIOs are Modernizing IT Ops to Solve 3 Key Problems

AIOps is seen by many as a saving grace that enables CIOs and ITOps to achieve operational efficiency.

As CIOs around the globe know all too well, change is happening – rapidly. Once viewed as just supporting the enterprise initiatives, CIOs now find themselves squarely in the limelight – driving the initiatives. Pitted against increasing market demands and the necessity to be agile enough to meet them, CIOs are embarking on a digital transformation that if successful, will completely revolutionize their entire business model.

Murali Nemani
CMO
ScienceLogic

To meet the expectation of enabling business opportunities, CIOs have to forcefully respond to a myriad of challenges, three of those including:

1. Delivering resilient customer experiences: It almost sounds too simplistic; development and operations teams (DevOps) work together to test and produce an application that rolls straight into production working flawlessly over time. Unfortunately, that’s not the reality. Over the lifespan of the application – which isn’t that long – ensuring digital resiliency becomes a significant challenge due to the dynamic nature of the modern IT environment. And as the underpinning infrastructure of the app change with dynamic workloads, it becomes increasingly difficult for the app to maintain its performance, which leads to either complete degradation, or continual maintenance from DevOps.

2. Mitigating business service impact: In today’s IT ecosystem, everything is interconnected. Whether it’s at the application or infrastructure layer, there’s complex and instant synchronicity involved – across disparate technologies – to deliver immediate results. And when something breaks, those layers of complexity can make it difficult to identify the source of the issue rather than where it appears. To compete in the digital era, Ops has to anticipate and identify the service issue before it becomes apparent to the end user.

3. Extracting operational efficiencies: According to a 2018 study of cloud computing trends by RightScale, 96 percent of approximately 1000 respondents are using the cloud, with the average organization employing almost 5. Citing operational efficiency and agility, it’s no wonder the cloud is popular among organizations, but there’s also a potential downside – cloud sprawl and runaway cloud costs. To do more with less, Ops needs to be able to create and run a common operating model across multi-cloud deployments and move at machine speed through automated actions.

In response to these three forces, CIOs are searching for something; anything that will help move them along their digital transformation and towards organizational agility. With the ephemerality of today’s technology (multi-clouds, micro-services, containers, and serverless technologies), manual processes are too slow and inefficient to keep up.

CIOs need to heed the old axiom of fighting fire with fire. To do that in today’s increasingly complex IT ecosystem, that means soliciting the help of machine assistance to make better decisions by collecting the right data, learning from it, and driving automation to move as quickly as possible.

Enter AIOps.

Artificial intelligence for IT operations, or AIOps, is an incredibly hot and trendy topic within our community. Defined as the combination of big data and machine learning, AIOps is seen by many as a saving grace that enables CIOs and ITOps to achieve operational efficiency. Although we think the exact definition of AIOps is a bit more nuanced and depends on the quality of data used, it’s important to recognize AIOps for what it is – a game changer.

As I wrote in my previous blog, “4 Reasons to Believe the Hype in AIOps,” I realize that some people are skeptical of employing the AIOps framework because the concept might seem too futuristic and good to be true, but rest assured that AIOps isn’t some far-off solution.

On the contrary, AIOps is here, and it’s already helping enterprises around the globe.

Need more evidence? Look no further than recent research conducted by Enterprise Management Associates (EMA). In their study, they sought to create a roadmap of what technologies are in use today and examine the dynamics that separate the most effective AIOps deployments from the ones that are struggling to catch traction.

In my presentation at Gartner Gold Coast, I’ll dive a bit deeper into the findings, but here are four fascinating nuggets that stood out:

Strategy matters – As my colleague, Brian Amaro, previously pointed out in a blog, AIOps is an incredibly powerful tool, but you better have a strategy. Both Brian and EMA note that it’s critically important for the CIO to provide a direction that creates and implements policies and procedures to enable the organizational agility necessary to drive automation – the end goal of AIOps. It’s important for CIOs to drive this charge because as EMA put it, “AIOps [is] understood as a unifying technology that can help to bring IT silos closer together with shared data and common insights.”

Take a look at your technology – There’s some hesitancy to buy into AIOps because some CIOs think they’ll have another tool to look after and manage – this is NOT the case. If done correctly, the right AIOps platform will help you consolidate your tools, not add to them. In fact, the study found that the average enterprise has 23 different toolsets to integrate. And it’s particularly sobering when you realize that number doubled in the last two years and is expected to double again!

Context is critical – In the report, EMA captured it well when they said, “One of the features that sets AIOps and advanced IT analytics overall apart from classic big data analytics is an awareness of the interdependencies across the application/infrastructure.” In ScienceLogic language, we refer to this ability as “context” and note its importance because it turns big data into an actionable data lake and allows you to understand and track the relationships within the infrastructure and applications. If you remember the second challenge that I mentioned CIOs need to resolve – mitigating service impact – the application of context is a direct route to achieving that goal.

Struggles and pain points – As a practice, AIOps isn’t just plug-and-play. In their report, EMA notes data quality issues, products not yet fully baked, and data relevance as the top three roadblocks to successfully implementing the framework. Once those critical issues are resolved, the benefits of AIOps is delivered in spades. Without giving too much away, 42 percent of respondents indicated that the value of AIOps dramatically exceeded costs.

If you’re attending the 2018 Gartner Symposium/ITxpo in Australia and want to learn how AIOps can help you accelerate automation and deliver resilient digital experiences, stop by the ITxpo show floor at 1pm on Wednesday, October 31.