How to Build and Drive a Data Culture
More and more aspects of our everyday life are taking place online – from how we work, to how we shop, and how we connect with others. To keep pace, organisations have stepped up their digital transformation efforts, supported by the shift to dynamic multicloud environments and cloud-native architectures. However, traditional monitoring solutions and manual approaches cannot keep up with these vast, highly complex environments. As a result, many organisations are turning to new, observability-based approaches to understand what is happening in their digital ecosystems. This, however, brings new challenges that must be overcome.
Here are six things to know about observability to ensure organisations can gain true value, combat the complexities of their modern multicloud environments, and drive digital success in 2021 and beyond.
1. Most organisations have very limited observability.
The scale, complexity, and constant change that characterises hybrid, multicloud environments presents a real challenge to IT teams. Our research found that, on average, digital teams have full observability into just 11 percent of their application and infrastructure environments – not nearly enough to understand what is happening, and why, across the digital ecosystem. Additionally, 90 percent said that there are barriers preventing them from monitoring a greater proportion of their applications – including limited time and resources. Without improving observability across the entire cloud environment – by drawing in metrics, logs, and traces from every application – IT teams are limited in the success they can have driving digital initiatives.
2. Manual approaches can’t keep up.
With organisations relying on more dynamic, distributed multicloud architectures, IT teams are being stretched further than ever. Nearly a third of organisations say their IT environment changes at least once per second, and 61 percent say it changes every minute or less. This rate of change creates a volume, velocity, and variety of data that has gone beyond IT teams’ ability to handle with traditional approaches – there’s no time to manually script, configure, and instrument observability and set up monitoring capabilities. The need for automation is therefore critical. By harnessing continuous automation in place of manual processes, teams can drastically improve observability; automatically discovering, instrumenting, and baselining every component in their cloud ecosystem as it changes, in real-time.
3. Cloud native adoption is obfuscating observability.
To remain agile and keep up with the rapid pace of digital transformation, organisations are increasingly turning to cloud native architectures. Our research found 86 percent of organisations are using cloud-native technologies and platforms such as Kubernetes, microservices and containers. However, the complexity of managing these ecosystems has made it even harder for IT teams to maintain observability across their environments. Over two-thirds of CIOs say the rise of Kubernetes has resulted in too many moving parts for IT to manage, and that a radically different approach to IT and cloud operations management is needed.
4. Data silos result in tunnel vision.
In an effort to boost their observability, many organisations have simply thrown more tools at the problem. Our research found that the average organisation uses an average of 10 monitoring solutions across the technology stack. However, more isn’t always better, and multiple sources of observability data can result in fragmented insights. This in turn makes it harder to understand the full context of the impact that digital service performance has on user-experience, and unravel the nearly infinite web of interdependencies between applications, clouds, and infrastructure. Instead, organisations should seek a single platform with a unified data model, to unlock a single source of truth. This will be integral to ensuring that all digital teams are on the same page, speaking the same language, and collaborating effectively across silos to achieve business goals.
5. Observability alone is not enough.
Simply having observability doesn’t help organisations achieve tangible benefits or reach their business goals. To get true value, the data being processed must be actionable in real-time. As such, observability is most effective when paired with AI and automation. This creates automatic and intelligent observability that enables teams to instantly eliminate false positives, prioritise problems based on business impact, and understand the root cause of any problems or anomalies so they can resolve them quickly. The alternative is to manually trawl through dashboards and data to find insights, which is incredibly time-consuming and makes it almost impossible to act in real-time. Our research found that 93 percent of CIOs think AI-assistance will be critical to IT’s ability to cope with increasing workloads and deliver maximum value to the business. AI is clearly no longer just a ‘nice to have’ but a business imperative.
6. Observability isn’t just for the back end.
Far from just having observability of their multicloud environments, IT teams also need to be able to see how the code they push into production impacts the end-user experience, and how that in turn affects outcomes for the business. This is a major goal for many CIOs, with 52 percent citing the ability to be more proactive and continuously optimise user experience as a benefit they hoped to achieve from increased use of automation in cloud and IT operations. By harnessing automatic and intelligent observability, digital teams can unlock code-level insights and precise answers to their questions about user experience and behaviour, so they can continuously optimise their services.
Observability is key for modern organisations looking to accelerate their digital transformation. By understanding these six key things about observability, digital teams will be better placed to master dynamic, multicloud ecosystems, and drive better outcomes for the business and its customers.