From applied observability to hyperautomation: the new data-driven technologies set to drive business change in 2023
By Thomas Kunnumpurath, VP, Systems Engineering, Solace
 |
| Concept art generated by dream by WOMBO. |
Applied observability
Observability has grown up, breaking out from its infant stages as a tech-focused term to something that organisations realise will provide the key to keeping track of key data events in an increasingly decoupled business world spanning systems architecture to the business operations it supports.
Moving forward, we now have the next level, "applied observability", recognised by Gartner as a key 2023 strategic tech trend at its most recent Orlando Symposium. Applied observability enables organisations to exploit their data artifacts for competitive advantage. That means being able to ensure that the right data is delivered at the right time for rapid action, based on confirmed stakeholder actions rather than intentions.
“Observable” data include key digitised artifacts, such as logs, traces, API calls, dwell time, downloads and file transfers, that appear when any stakeholder takes any kind of action. Applied observability feeds these observable artifacts back in a highly orchestrated and integrated approach to accelerate organisational decision-making and allows the business owner to track how long an action took to fully process at every point in the workflow.
By having this visibility into end-to-end workflows, businesses can gain better visibility into how long their systems took to process a workflow and get real-time insights into bottlenecks or areas for improvement to ensure their systems function optimally.
But unearthing these insights requires an event-driven approach to software architecture. Distributed tracing, for example, is a method of tracking application requests as they flow from front end devices to backend services and databases. By definition, and in contrast to traditional tracing, distributed tracing can be visualised to show a searchable, graphical picture of when, where, and how a single event flowed through an enterprise, regardless of the number of hops the workflow took to fully process.
Consider the potential traceability and end-to-end observability benefits across a payment ecosystem underpinned by event-driven architecture. Embedding distributed tracing into an event mesh emits trace events in OpenTelemetry format so banks can collect, visualise and analyse them in any compatible tool. This empowers them to not only confirm that a given message was published, but easily understand exactly when and by whom, where it went, down to individual hops, who received it and when…or why not.
When planned strategically and executed successfully, Applied observability is arguably the most powerful source of data-driven decision-making. And, since OpenTelemetry is a well-defined open standard, it can be implemented across both synchronous and asynchronous workflows.
Hyperautomation and intelligent automation
Gartner and IDC identify both hyper and intelligent automation in their yearly technology trends for 2023. Hyperautomation moves automation up a level, adding more intelligence to automation and using a broader set of tools so that previously unautomatable tasks can be automated. Hyperautomation initiatives come in many different shapes and sizes and are being seen across a wide range of industries, from banking and insurance to manufacturing and healthcare.
Gartner points to US healthcare company CVS Health as a prime example of having taken advantage of hyperautomation to simplify its unwieldy benefits administration processes to improve efficiency, accuracy and customer service. A new system was developed to streamline tasks from application receipts and payments to issue resolution. These were cross-functional, largely manual and time-consuming tasks beforehand, which involved analysing data in a wide range of formats and aligning with complex coding rules. However, using a combination of artificial intelligence (AI), robotic process automation (RPA), machine learning, data analytics and natural language processes (NLP), the company was able to automate much of this work.
As consumers of goods and services continue to demand faster and better customer service, companies need to overlap development cycles and find ways to cost-reduce portions of what they deliver to stay ahead of the curve. Removing the friction that slows down implementation teams is key to success with end-customers.
But hyperautomation requires an organisation to be underpinned by an event-driven architecture (EDA) and – more specifically, an event mesh – to maximise success. An event mesh is an interconnected network of event brokers that allows data to be pushed in real time to parts of the organisation where the data is needed. It does this dynamically, meaning that new event types can be added any time, and interest in events can be registered allowing seamless interchange of data for the applications that are interested in using it.
Take the aviation industry as an example. An event mesh streams information such as flight routes, delays, cancellations, and mileage accruals between applications, connected devices and people anywhere in the world, instantly. With an event mesh, information about events can be continuously streamed to multiple systems, filtered so each system only receives the data it needs. This ultimately enhances the customer experience as passengers, pilots, and crews are notified in real time when something relevant occurs across on each and every flight.
Or take the working example of Heathrow Airport. After downsizing its IT department during the pandemic, it needed to reduce its dependency on IT to deliver solutions. The answer was to pivot the department to the role of orchestrator, building a low-code/no-code community of practice that enabled employees across the wider business to build-in their own automation for health and safety apps to support safe return to work or live audits.
As of last August, Heathrow’s hyperautomation efforts had garnered huge savings in potential outsourcing costs, reduced paperwork by 120,000 pages and decreased manual data entry hours by more than 1,170.
The two trends discussed above offer the potential to reshape the way we do business, interact with customers and partners, and make data-driven decisions. The common thread across these trends is the need for better movement of data, in real time, in motion, and all pointing to the need for an underlying event-driven architecture. To ensure success, organisations must adopt an event mesh underpinned by a proven strategy to designing, managing and governing events as they flow through their enterprise.
Comments
Post a Comment