Four observability trends IT leaders to have on their radar

By Bernd Greifenader, Founder and CTO, Dynatrace
Organisations are being forced to prioritise cost reduction, but it's important that efficiency doesn’t come at the expense of innovation and growth

The year 2022 brought more than its fair share of challenges. Just as the world began to emerge from the immediate impacts of an unprecedented global healthcare crisis, it faced yet another emergency. Soaring energy costs and rising inflation have created strong macroeconomic headwinds that force organisations to prioritise efficiency and cost reduction. 

However, organisational efficiency can’t come at the expense of innovation and growth. Otherwise, organisations will quickly fall behind their rivals in an increasingly competitive market. The need to strike this balance correctly will be the dominant factor underlying digital transformation initiatives in the year ahead. In light of this, here are my predictions for the most significant observability trends we’ll see shaping IT leaders’ agendas in 2023.

Prediction no. 1: “Trustworthy AI” will emerge as a required attribute for organisations that need to automate increasingly complex digital ecosystems.

As organisations strive to do more with less and forge ahead through rising macroeconomic headwinds, automation will be critical in 2023. Greater automation will enable organisations to free skilled resources to focus on tasks that deliver the greatest value. As a result, teams can accelerate the pace of digital projects and innovation instead of cutting back. 

However, the growing awareness of the potential for bias in artificial intelligence will be a barrier to widespread automation in business operations, IT, development, and security. Organisations can’t drive automated runbooks with AI that confuses the symptoms of a problem with its root cause, that prioritises lower-risk issues over ones that have true business impact, or implements the wrong solutions. 

Without trustworthy AI, human operators will continue to feel compelled to manually validate any answers their AI-powered solutions provide. This will negate efficiency gains and hinder efforts to automate business, development, security, and operations processes. Trustworthiness will therefore emerge as a prerequisite for any AI solution through its ability to provide precise and explainable answers instead of statistical guesses.

Prediction no. 2: Observability, security, and business analytics will converge as organisations strive to tame the data explosion.

The continued explosion of data coming from multicloud and cloud-native environments, coupled with the increased complexity of technology stacks, will lead organisations to seek new, more efficient ways to drive intelligent automation in 2023. It’s not just the huge increase in payloads transmitted but the exponential volumes of additional data, which can be harnessed to gain better observability, enhanced security, and deeper business insights. 

However, the prevalence of siloed monitoring tools that offer insights into a single area of the technology stack or support an isolated use case has impeded progress in accessing this value, making it difficult to retain the context of data. It also results in departmental silos, as each team remains focused on its piece of the puzzle rather than combining data to reveal the bigger picture. 

To address this, observability, security, and business analytics will converge as organisations consolidate their tools. Teams will seek to move from myriad isolated and hard-to-manage do-it-yourself tools to multi-use, AI-powered analytics platforms that offer business, development, security, and operations teams the insights and automation they need. This convergence will help to tame clouds and the data explosion and drive intelligent automation across multiple areas, from cloud modernization to regulatory compliance and cyber forensics. 

Prediction no. 3: DevSecOps matures into SecDevBizOps as cyber-insurance demands that every innovator is responsible for minimizing risk.

Mitigating cyber risk will become front-of-mind for everyone involved in innovation, as growing maturity in the insurance industry makes it imperative to treat security as a shared responsibility. Organisations taking out cyber-insurance policies will be required to demonstrate that every innovator in the business can conduct due diligence and manage the risk associated with their actions. 

There will be a growing focus on solutions that enable teams to mature their DevOps and BizDevOps-centric strategies into a more holistic SecDevBizOps approach, combining security, development, and IT practices with business analytics. This will lead to increased investment in observability platforms that support cross-departmental processes and ensure everyone has the answers they need to be accountable for delivering secure innovation.

Prediction no. 4: Data context-driven automation will emerge as a priority for organisations looking to mature basic AIOps into more precise AISecOps.

Organisations will increasingly realize that to be effective, the platforms they use to automate software delivery pipelines and support AIOps need to be data context-driven. That means they need the ability to unify data and its context in a single source of truth, where it can be transformed into precise answers and intelligent automation. This will be key to ensuring that the AI powering automation can distinguish between cause and effect to make smarter and more timely decisions. 

Organisations have struggled to maintain this context as the growing complexity of dynamic cloud architectures and increasingly distributed digital journeys have generated an explosion of data and disparate analytics tools. In the coming year, however, organisations will shift their focus from consolidating tools to drive efficient AIOps to embracing platforms that support more advanced AISecOps (AI for security and operations). This will enable teams to break down the silos between observability, business, and security data and bring it together with topology and dependency mapping. As a result, teams will be able to retain the relationship between data streams and unlock the full context needed to drive more powerful and precise automation and deliver seamless digital experiences.


Featured Articles

Gen AI Boom Drives Nvidia Value to Overtake Microsoft

Nvidia surpasses Microsoft to become the most valuable company, with its AI and chip developments tripling stock and prompting a US$3.3tn market cap

IBM & Wimbledon: AI Is Changing the Game for Sports

IBM and The All England Lawn Tennis Club have unveiled AI features for Wimbledon that will provide real-time analysis and expanded, personalised content

Zoom: Powering EMEA with a Partner-Led Focus

We examine how Zoom is moving towards greater digital transformation via its EMEA partnership channels, inspiring the next generation of collaboration

Schneider Electric: UK&I President Grows Her Europe Presence

Digital Transformation

DTW24 Ignite: AI to Power the Next Generation of Technology

Digital Transformation

SolarWinds: IT Professionals Worry about AI Integration Risk

AI & Machine Learning