Today, digital experiences define how we live and engage with colleagues and businesses from connecting with companies through mobile apps, to using collaboration tools and productivity solutions at work. The pursuit of flawless digital channels has facilitated improved employee and customer experiences, but these have also created new levels of complexity for IT teams.
Consequently, they often have an incomplete view over network and application performance, despite their best efforts. A key reason for this is that the tools that should help IT are also generating significant amounts of data for them to process. In the absence of tools that expediate the derivation of valuable insight from this data, IT teams can find it challenging to address issues or to innovate. As a result, the seamless digital experiences that employees and consumers have come to expect are harder to achieve.
Observability is the answer
It is clear that organisations and their IT teams need more context and insight from the data they generate to make a tangible difference, such as predicting and preventing digital experience issues before they happen. Observability presents the answer.
Observability correlates information from disparate sources and gives actionable insights on why things are happening. As such, it empowers IT to collaborate and investigate “unknown unknowns” on the fly. This bridges silos across domain-specific teams, increases agility, improves service availability, facilitates productivity, and ultimately guarantees business continuity, all while reducing costs.
Observability brings the benefits of monitoring, visibility, and automation together. However, most observability tools available on the market today have limitations, so ultimately, it’s unified observability which organisations need. Here are the main pillars of unified observability and why they matter.
The power of full-fidelity telemetry
Capturing full-fidelity data across the complete IT ecosystem – including client devices, networks and servers, cloud-native environments, applications, and the users themselves – gives IT a holistic view. This enables IT to establish what has happened and what is happening. Combined with actual user experience analysis, opposed to just using sample data, IT teams can achieve deep insight as they can augment quantitative measures of user experience with qualitative measures of employee sentiment.
Applying intelligent analytics
Organisations can also be empowered to better detect anomalies and resolve key challenges quickly and precisely through intelligent analytics. Specifically, applying Artificial Intelligent (AI), Machine Learning (ML), and proprietary data science techniques across disparate data streams, including third-party data.
Unlike other available observability tools, this means businesses know the impact and seriousness of any issues as soon as they arise. This means they can prioritise better and focus time and effort where it’s most needed.
A single source of truth
The actionable insights derived from AI and ML facilitate successful cross-domain collaboration by delivering a single source of truth. This supports efficient decision-making that will accelerate mean time to resolution.
It also minimises the time spent in war rooms, unnecessary portioning of blame, and excessive escalations. With open APIs, actionable insights can be imported from or exported to wider third-party systems, including security tools and ITSM, so service quality and overall digital experiences can be continuously improved.
Automated remediation
With unified observability, businesses also benefit from an expandable library of pre-configured and customisable actions that can assist manual and automated remediation of common issues. The system recommends corrective actions for the issue under investigated, so IT can then decide whether and when to implement these in line with their core objectives and goals.
Exceptional digital experiences are in reach
High quality digital services are paramount to an organisations’ success. However, increasing demands on IT teams, created by evolving customer preferences and workforce models, results in complexity that can act as a barrier to this. With unified observability this doesn’t need to be the case. By unifying data, insight and actions across IT, data siloes and alert fatigue are removed, facilitating improved decision-making for continuously enhanced digital experiences.
