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Three trends in operational analytics

Software is becoming more and more business critical. Whether you’re delivering excellent e-commerce experiences or online banking, applying operational analytics is needed to monitor software and achieve zero-downtime. While operational analytics is still advancing, one thing remains certain. Whether operational analytics is being applied now or later, this technology will be adopted more in the next three years. Applying operational analytics to proactively address issues and prevent future outages is the way digital enterprises of the future are moving towards zero-downtime today.

The complexity and agility of today’s emerging infrastructure demand a new wave of monitoring tools. DevOps, continuous delivery, digital transformation and the rise of new technologies like Docker, Mesos and Kubernetes have pushed IT operations to the next level.

Operational analytics is needed to pave the way towards zero-downtime. Organizations achieved this by connecting their business with IT, implementing automated monitoring and automated analytics.

1. Connecting business with IT

To achieve zero-down-time, organizations transform their enterprise IT into a technology-driven company. Organizations like Facebook have had the luxury of building up their environment on new technologies from the start. Enterprise infrastructures, however, have had to add new technologies on top of existing ones, plugging them into their infrastructure. They consist of layers of technologies built on top of each other, each one necessary to facilitate market changes, new requirements, and customer needs. While more modern organizations have introduced and used many new technologies, enterprise IT still needs to deal with legacy software, legacy applications and more... legacy.

Where to begin? No existing business is turned into Facebook in a blink of an eye. Change happens step by step. And that's not the only challenge.

The biggest challenge of digital transformation is gaining insight across business and IT. Despite the silos inside any large enterprise and the existing tensions between IT and the business, the digital priorities of an organization are end-to-end. Without insight and a common goal, technology doesn’t serve the business well. Every aspect of customer-facing software, from the user interface down to the underlying systems and hardware, must perform at warp speed without disruption. Every part must satisfy the customer.

2. Automated monitoring

Enterprises must monitor their technology on both its performance and its impact on the business and customer satisfaction. Most enterprises use multiple tools to monitor parts of the entire landscape, with no single view on all teams and their tools. There is too much data, too many complicated graphs, too many alerts and dashboards from different tools with too few insights. To gain control of data, the environment and the business services, organizations have started to implement operational analytics. These systems and tools can extract, analyze and report data automatically and instantly. By searching through massive amounts of information from different sources, operational analytics generates proactive insights and prevents potential issues, allowing companies to move towards zero-downtime through a more modern monitoring view.

3. Automated Analytics

With a few thousand dependencies, the smallest change in an IT-landscape can create a domino effect that severely impacts stability. Finding the cause of the problem, when it occurs, takes up valuable IT-team time. By applying operational analytics technologies, IT-operations teams can completely automate root-cause analysis so that when problems occur, the component(s) which most likely caused the failure are revealed, reducing the time to find and fix them.

Automated analytics are used for anomaly detection. As in many cases there is a lag between the first anomaly and a business process impacting event, anomaly detection allows organizations to take remedial action and avoid incidents by spotting unusual behavior as soon as they happen.

IT teams also implement operational analytics to detect patterns and automate the entire problem-solving process. Patterns are not necessarily anomalies, but they can be associated with negative outcomes. Detecting patterns of past failures can prevent future problems. When a pattern is recognized the system will automatically trigger remediation processes to prevent issues before they affect critical services.

Real-Time Visualization of IT and Business

Operational Analytics-based tools will provide enterprise IT organizations the next piece of the puzzle by pulling together all the information from different tools in one place to create a real-time visualization of the entire IT and Business landscape.

This article is part of the Urgent Future IT Forecast 2017.

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