5 observability gaps that could blindside your organisation
To operate effectively and keep up with the ever-growing demand for digital services, IT teams need to clearly see and understand what is happening in their organisation’s IT environment. However, traditional monitoring solutions and manual approaches are struggling to keep up with the dynamic nature of today’s hybrid, cloud-native environments, which makes gaining and maintaining insight far more difficult than ever before.
As a result, more organisations are shifting towards new approaches that support the three key pillars of observability: metrics, logs, and traces. However, these approaches are only effective if the data being gathered can be fully understood in its wider context. As such, gaps in observability can impact digital teams’ ability to understand, monitor, and manage their services effectively.
Here are five of the biggest areas where observability gaps occur that can blindside organisations.
1. Containers, microservices, and Kubernetes
Using cloud-native architectures based on microservices, containers, and Kubernetes can massively benefit organisations, offering increased agility, efficiency, and scalability, to drive faster innovation. However, they also result in an extremely dynamic environment that is constantly changing. has found that 61 per cent of CIOs say their IT environment changes every minute or less, and that per centage will only increase as more organisations adopt cloud-native architectures. It’s near impossible for teams to keep up with this pace of change using manual approaches to configure and instrument apps, or to script and source the data they need to maintain observability – leaving them with blind spots. In fact, 63 per cent – nearly two-thirds – of CIOs say the complexity of their cloud environment has surpassed human ability to manage. As such, automation is becoming critical to manage cloud-native environments.
2. Real user experience
A key focus for modern organisations is the ability to create excellent user experiences by continuously improving their digital services. However, if organisations don’t monitor the way real users experience their applications and software, they create an observability blind spot, which makes it difficult to effectively optimise user experiences. Without measuring the experience from the perspective of the user, it’s impossible to know if applications are working as they should, or if changes are needed to optimise the user journey. Organisations also need to be able to put this information in context, so they can see the full picture of how digital service performance impacts user experience. That can only be achieved with a single platform and a unified data model, not the multiple tools that many organisations rely on to maintain observability and manage user experience.
3. IT operates in a silo
In our recent research, 56 per cent of CIOs said IT is becoming more of a business imperative, while 64 per cent said they’re under more pressure from an increased demand for digital services. Despite this, most organisations look at observability data in isolation of business metrics, such as revenue and conversions. This siloed approach to IT operations creates a blind spot, as the relationship between key IT and business metrics can easily be missed, meaning crucial context falls through the cracks. For instance, business teams may notice a sudden drop or a spike in e-commerce conversions after the IT team deploys a new software update to a back-end application. If IT and business metrics aren’t considered in context of one another, organisations can miss these correlations, meaning users often find out about problems before the business does, through a poor digital experience.
4. Too many tools
In their efforts to maintain observability into their multi-cloud environments, many organisations use an average of 10 different monitoring tools to keep track of individual platforms and services. However, IT teams are struggling to keep up with the huge volume, velocity and variety of data this creates, and to make sense of the often-conflicting alert noise that results from it. 72 per cent of CIOs have said they can’t keep plugging monitoring tools together to maintain observability. 84 per cent say the only effective way forward is to reduce the number of tools and the amount of manual effort IT teams invest in monitoring and managing the cloud. They’re calling for a single platform that can provide end-to-end observability. However, that won’t solve all their problems, as IT teams still need to interpret vast quantities of data quickly enough to understand what it’s telling them. That’s why AI is becoming so critical in this area, enabling IT teams to instantly turn observability data into actionable insights that can be used to optimise services and resolve issues before users are impacted.
5.Manual, DIY approaches
Many organisations take a DIY approach to observability, manually building instrumentation into application code as they go along. Not only is this a time-consuming process that takes up team resources that could be better spent elsewhere, but it also usually creates blind spots. While newer systems often have observability built in, many older ones don’t, as IT teams would need to go back to their existing applications and instrument them retrospectively. This leaves a fragmented view of the environment, with research showing digital teams only have full observability into 11% of their application and infrastructure environments. This means teams won’t have the full context of what is happening and how IT service performance impacts users and the business. It’s therefore essential to automate the process of instrumentation to ensure that observability is end-to-end and continuous. This will enable IT teams to focus their efforts on more valuable tasks that drive better outcomes for the business.
Observability is essential to success for modern organisations, providing the insight they need to ensure services deliver the frictionless experiences that users and the business demand. As such, these five observability blind spots pose a significant threat to the business if they remain unchecked. AI and automation hold the key to closing observability gaps and enabling IT teams to reduce risk and drive better business outcomes.
Abdi Essa is regional vice president, UK&I, for Dynatrace