Unified data observability: Helping IT deliver winning digital experiences

A click today is everything. Whether in the office, at home or anywhere else, and at any time of the day or night, that action comes with intent and expectation – of a flawless digital experience. These experiences are the heartbeat of the fiercely competitive digital-first world we live and work in.

Question: What is the No. 1 challenge plaguing IT teams? 

Answer: With data quantity and usage exploding, ensuring digital service quality in increasingly complex environments.

The increasing complexity of IT in a hybrid world

The fundamental job of IT is to keep the services, systems and applications that run a business functional, accessible, performant and secure for employees, partners and customers. And while the job hasn’t changed, IT environments have. Today’s environments are exponentially more complex, dynamic, distributed and hybrid, and the enormous amount of data and alerts generated by tools designed to help IT make work more difficult. 

Most IT teams manage a mix of traditional on-premises infrastructure with private cloud and public cloud, where performance is not always under IT’s direct control. Meanwhile, cloud-native applications that are modular, ephemeral, transient and serverless comingle with applications that are self-hosted, managed, or delivered as a service. Effectively managing this hybrid infrastructure and application architecture requires unique skills and expertise. 

In addition, transformational shifts to remote work require IT to support employees across more devices in more locations. In a competitive market to attract and retain talent, including Gen Z workers, businesses need apps, devices and technology to delight employees, which also drives greater productivity. To do that, they need better insight and more context from the data they receive to do their job well in today’s constantly evolving environment. 

Observability as means to avoid data deluge

Observability is a term many tech leaders say will usher in the next phase of monitoring and visibility, but – as with any hype-inducing technology – there is an ongoing discussion around its definition and utility for modern enterprises. Let’s set the record straight today.

Observability is the ability to measure the internal states of a system by examining its outputs. To be effective in today’s modern world, organizations need a better approach to ensuring digital service quality and effective collaboration in dynamic, distributed, hybrid environments. Otherwise, businesses may drown in data. Consider research from Statista that shows the volume of data generated, consumed, copied and stored is projected to reach 180 zettabytes in 2025, up 3 times from 64 zettabytes in 2020.

Observability gives IT the flexibility to dig into “unknown unknowns” on the fly. It enables access to actionable insights by correlating information and providing appropriate context around why things are happening. However, it’s important to note that observability is not a replacement for monitoring and visibility.

Data monitoring, visibility and observability: What’s the difference?

Simply put: monitoring, visibility and observability are different and complementary concepts that build on each other. Monitoring happens at a domain level and is symptom-oriented. It tells you that something is wrong and it is predicated on knowing in advance what signals to monitor.

Visibility is achieved by comprehensive monitoring and the aggregation and analysis of data across domains. Visibiilty provides relationships in data that monitoring might not detect.

Observability, as noted earlier, extends the benefits of visibility through AI, ML and automation, providing actionable insights that help IT understand unknown unknowns, make decisions, prioritize actions and solve problems, faster.

Unified data observability: Busting silos make digital seamless

Unified observability requires businesses to break down their data silos, and to unify data, insights and actions so they can deliver seamless, secure digital experiences. This is a big focus for our customers. There are four tenets to building a unified observability environment: 

• Full-fidelity telemetry — To achieve unified observability, organizations must capture full-fidelity data from monitoring and visibility tools across the entire IT ecosystem, including client devices, networks, servers, applications, cloud-native environments and users. This complete picture enables IT to understand what is happening and what has happened while not missing key events or context due to sampling. And, when it comes to user data, it’s critical that organizations augment quantitative measures of user experience with qualitative measures of employee sentiment for a deeper level of insight into actual user experience.
• Intelligent analytics — Applying AI, ML and data science techniques across disparate data streams, including third-party data, can help IT teams detect anomalies and changes better. By doing so, the organization can surface the most critical issues faster and with precision. This capability enables better prioritization to focus IT teams’ time and effort on the areas that matter most to their organization.
• Actionable insights — With a powerful combination of AI- and ML-enabled automation, organizations gain context-rich, filtered and prioritized fix-first insights. These insights enable effective cross-domain collaboration because unified observability offers a single source of truth, allowing for more efficient decision-making to accelerate mean-time-to-resolution (MTTR). This approach also reduces time spent in war rooms, finger-pointing and excessive escalations. 
• Automated remediation — What could your organization do with an expandable library of preconfigured and customizable actions to support manual remediation and automated self-healing of common issues? Automated remediation actions are recommended by the system based on the problem being investigated, but IT maintains decision-making control on whether and when to execute the suggested corrective action. This approach ensures that measures can be implemented in alignment with an organization’s primary goals and objectives. 

Serving up an excellent digital experience is no easy feat. The tectonic shifts in hybrid work, distributed cloud networks, and modern app architectures further complicate the job of IT, making it harder to keep digital services accessible, high performing, and secure.  And the pandemic further complicated matters by accelerating digital transformation initiatives from years to months. For organizations to succeed in this digital-first world, they need to be able to see through this massive complexity and unify data, insights, and actions across IT and the business. 

Mike Marks is vice president of Riverbed Technology.