As organisations have pushed through digital transformation programs to navigate the pandemic, most have relied heavily on the cloud to enable them to move at the required speed and scale. The last 18 months have proved the benefits of cloud architectures beyond all doubt, providing operational speed, agility and resilience.
But whilst the dramatic shift to the cloud has enabled businesses to respond quickly to changing business conditions, it has caused significant problems in the IT department. Our latest Agents of Transformation study, Agents of Transformation 2021: The Rise of Full-Stack Observability, revealed that 86% of technologists in the United Arab Emirates (UAE) are experiencing greater levels of complexity as a result of the acceleration of cloud computing initiatives during the pandemic. And 84% cited technology sprawl and the need to manage a patchwork of legacy and cloud technologies as an additional source of complexity.
The research highlights major challenges in how IT departments are able to monitor and manage technology performance in these new hybrid cloud environments. Technologists are finding that traditional monitoring approaches simply aren’t fit for purpose in dynamic, distributed, software-defined environments, where organisations are continually scaling up and down their use of IT, based on business needs.
Adoption of cloud computing is expected to accelerate even further over the next three years. The consequences of this extremely rapid growth, and the pressure it will put on IT teams, are potentially severe. Businesses are unable to guarantee seamless digital experiences to ever-more demanding users and they risk jeopardising the massive investments they have made in digital transformation. Our research found that 79% of UAE technologists believe its very important to have the ability to monitor all technical areas across the IT stack and directly link technical performance to business outcomes.
So, with that in mind, here are three factors technologists should consider as they look to gain greater visibility and insight into all IT environments.
It’s only ‘full-stack’ observability if it includes your entire IT estate
The observability market is becoming increasingly crowded and complicated, and it can be hard to understand exactly what a solution will deliver. Our research found that 67% of technologists across the Emirates are now finding it difficult to distinguish between monitoring and observability tools.
For any organisation that is embarking on a large-scale shift towards cloud computing, it’s essential to implement a platform that delivers genuine visibility across all cloud and traditional infrastructures, from customer-facing applications through to core infrastructure such as network and storage, security and the open Web.
Most tools on the market still struggle when it comes to visibility into applications and their supporting infrastructure for large-scale public cloud environments
So it’s vital for technologists to ensure they have access to a tool that provides alerting, root cause and analysis of correlated MELT (metrics, events, logging, and tracing) data to enable comprehensive, early and easy troubleshooting.
Observability must be linked to business metrics
Technologists don’t just need visibility into cloud infrastructure and the applications they execute to track health and performance, they also need a way to navigate through the massive volumes of data that increased digital transformation is generating.
The only way to cut through this data noise is to connect real-time IT performance insights with business outcomes, such as customer experience, sales transactions and revenue.
This allows technologists to identify and fix critical issues early before they impact end users, and to prioritise actions and investment based on what really matters to the business.
So ensure that your full-stack observability solution allows you to view IT health and performance data (including in the cloud) through a business lens so you can always prioritise your decisions based on business impact.
Think about cloud observability requirements in three years
As the speed of innovation gathers pace and organisations continue to turn to cloud computing to run their critical workloads, the volume of data that businesses are generating will increase exponentially over the next three years.
It won’t be long before IT departments find themselves unable to commit the resources required to manage and optimise health and performance across the whole IT estate. What’s more, most current observability solutions just aren’t designed to handle the spiraling amounts of data and soaring IT complexity that will engulf IT departments.
So when considering observability solutions, it’s important to recognise that what works today could soon become inadequate soon.
Technologists should be thinking about how they can pre-empt issues down the line and reduce their reliance on manual interventions to assess IT data and address performance issues.
This is where automation and AI is set to play a big part in minimising the impact of data overload, tracking health and performance across the IT estate, and particularly in infrastructure for large-scale public cloud environments. managed kubernetes environments in public clouds.
By using AI to identify and fix issues in real-time, before they impact end users, organisations can deliver faultless digital experiences at all times.
In addition to this, technologists should also consider the benefits of a SaaS-based observability platform which can easily scale and flex to business demand. Moving from an on-prem to a SaaS platform can reduce management overheads, increase security and deliver cutting-edge AIOps functionality which automates insights. And, because it is cloud-based, a SaaS solution offers self-updating capabilities which will ensure technologists always have the latest functionality.
By taking a long-term view around IT performance, technologists can set themselves up to deliver the game-changing innovation that their businesses need now and in the future.
