Digital Enterprise Journal Study Identifies Key Forces Shaping IT Operations in 2018 - Evanios

Digital Enterprise Journal Study Identifies Key Forces Shaping IT Operations in 2018


Recently, Digital Enterprise Journal (DEJ) published the results of an in-depth study of the IT operations market. Titled “17 Areas Shaping the IT Operations Market in 2018,” the report focuses on DEJ’s survey of more than 2,500 organizations, identifying key areas with the strongest impact on IT operations.

The report is fascinating, both for its data-driven insights and pragmatic conclusions. Here are some of its most important results – and how Evanios is delivering this vision today.

Context Is King

According to the report, more monitoring data doesn’t translate into better IT performance. In fact, growing complexity is generating a steep increase in monitoring data, but 71% of organizations report that this data isn’t actionable. On the other hand, top-performing organizations (TPOs) leverage capabilities including correlating IT and business performance, and contextually enriching events to make sense out of their monitoring data. The report recommends that all IT organizations follow similar strategies.

Evanios sees this issue every day. Organizations tell us they are drowning in noise, and that what they need is actionable alerts. Filtering is a key first step, but unless you correlate data across siloed monitoring systems, there is no easy way to diagnose and remediate end-to-end issues. Equally important, events need business context – such as service and business impact. Otherwise, IT operations doesn’t know where to focus their efforts. That’s what Evanios does – and it’s why we’re an event management leader.

Intelligent Automation at Scale

The DEJ report makes something else perfectly clear – IT operations needs scalable solutions to respond to the new digital economy. 58% of TPOs say that scalability is a key selection criterion for their IT operations platforms, and 57% say the same about automation. Interestingly, DEJ also says that the demand for scalability isn’t primarily driven by the number of devices managed. Instead, new types of technology and infrastructure are driving a dramatic increase in monitoring data volumes, as are rapidly rising transaction volumes. For example, containers and microservices produce 18 times more monitoring data on average than traditional architectures, according to the DEJ report.

At Evanios, we believe that scalability is about more than simple processing power. It’s about having machines do the groundwork, maximizing the productivity of IT staff. By providing out-of-the-box integrations to a huge range of monitoring sources, we help IT organizations scale manage new types of technologies and services. By applying codeless logic and machine learning, we reduce a deluge of monitoring information to a trickle of actionable events. And, with automated root-cause analysis and remediation, we free up IT staff to work on the difficult issues while we take care of the rest.

Automation, AI, and Machine Learning

And, intelligent automation isn’t just marketing hype. According to the report, AI and ML-based solutions have crossed over into the mainstream. 45% of IT organizations have already deployed machine learning platforms or plan to do so in 2018. However, the report also cautions that not all solutions are created equal, and that vendor messaging is creating market confusion.

Evanios recognizes that IT organizations face a difficult choice when selecting a next-generation event management vendor. In our opinion, there is too much black-box magic out there, with vendors touting machine learning as a panacea – a universal cure. We take a different, more pragmatic view. Machine learning complements existing approaches, rather than supplanting it. For example, configured logic works well for event filtering and deduplication, so there is no need to replace it. On the other hand, machine learning is incredibly useful for recognizing event patterns, making it far easier to group and even predict events.

And, transparency is key to adoption – which is why black-box solutions will fail. Unless IT staff understand why an AI system is making recommendations, they won’t trust it. That’s why Evanios make sure that anyone with an IT background can understand what our platform is doing – there is no need to be a data scientist.

Proactive Approach Is Not Optional

According to the DEJ report, IT organizations are increasingly investing in solutions that can proactively forecast service issues. In fact, there has been a 53% increase in adoption of proactive tools in the last three years. However, DEJ also notes that these tools have historically delivered mixed results. As a result, organizations are increasingly turning to new predictive technologies to enable success.

As we have noted previously, first-generation predictive analytics solutions relied on profiling IT environment performance and reporting anomalies. They tell you that there is a potential issue, but they don’t help you to identify and fix it. As a result, IT teams still spend huge amounts of time diagnosing and remediating service issues – by which time, the service is already in trouble. On the other hand, Evanios’ next-generation predictive analytics give you actionable information, pinpointing future issues, diagnosing the root cause, and recommending remedial steps – so you fix potential service issues before your customers are affected.

The Need for New Incident Management Strategies

Finally, the report points to the need for new ways of handling incidents. IT organizations are recognizing that it is no longer humanly possible to manage incidents with legacy solutions. In fact, 79% of respondents reported that adding more IT staff to manage incidents is not an effective strategy. Instead, the report recommends an “entire lifecycle” approach, including centralized visibility, proactive detection, and ongoing learning from previous incidents.

This is fully aligned with Evanios’ approach to IT operations. We consolidate and correlate monitoring data, creating a single pane of glass. Our next-generation predictive analytics deliver an actionable, proactive approach to managing incidents. And, our machine learning algorithms use incidents and other historical ITSM data to enrich event data – including predicting business impact, automating assignment, and identifying root cause.

That’s why some of the world’s most forward-looking organizations come to Evanios to help them transform their IT operations. To see firsthand how we can help your company scale IT Operations automation, create end-to-end visibility and deliver actionable, intelligent incidents and events, contact us for a demo.

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