Why does observability matter to your role?
A modern enterprise – one built to respond quickly to both problems and opportunities within hybrid multi-cloud environments – relies on a modern IT infrastructure. The more advanced the system, however, the more complex it becomes and the more difficult to manage. And IT doesn’t exist in a vacuum. Stakeholders throughout the organization impact, influence and benefit from the systems for which IT is responsible. And the impact of a mere one-second delay means a 7% decrease in customer conversion¹ and a 16% decrease in customer satisfaction².
That’s why IT organizations are investing so heavily in observability, IT automation and AIOps solutions. 47% of organizations are doing so, according to a recent survey, with 44% citing an increased adoption of observability and monitoring tools.³
So, what does this investment in observability look like across an organization?
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Developers and DevOps
Developer and DevOps teams face a future of more new applications, more services, and more updates, all of which drive demand for ever-faster release cycles. Yet they can’t have any loss of quality or disruption of services. Because of this reality, developers and DevOps teams are under constant pressure. Observability enables them to eliminate the complexities of multi-cloud environments and see the entire IT environment with context and an understanding of interdependencies. That allows teams to automate tasks and stretch resources, detect problems proactively, and resolve issues faster.
For more insights, read The Future of Dev+Ops (Link resides outside ibm.com) and Observability for developers (Link resides outside ibm.com)
SREs
Site reliability engineers (SREs) seek to bridge the traditional gap between development and operation teams. Their goal is to improve an organization’s ability to ship and operate software better, faster, safer and happier. Driven by metrics, SREs say that reducing MTTR is their top focus, but their time is often spent on building and maintaining automation code. That’s why observability and automation are key to enabling agile, scalable SRE processes. SREs can use observability platforms as a sort of digital assistant — offloading the tedious tasks of instrumenting code and collecting data, while analyzing logs, metrics and traces.
CIOs
Although CIOs are responsible for the big-picture operations, they are often focused on budgets and projects. Questions like “are we delaying a roll out?” or “how much time do my developers spend or fixing bugs?” demand their focus. That’s why an observable platform matters. It’s a single, automated view of the entire environment that prevents problems before they start. It also frees up precious resources and allows teams to focus on enhancements and innovations.
CISOs
In 2021, the average number of cyberattacks and data breaches increased by 15.1% from the previous year, but organizations that had a fully deployed AI and automation program were able to identify and contain a breach 28 days faster than those that didn’t, saving USD 3.05 million in costs.⁴ While CIOs may focus on preventing system problems that cause downtime, Chief Security Officers can use the same observability tools to detect issues that might cause breaches and plug those holes before they allow any data to leak out.
For more insights into how security issues impact an organization, read the Cost of a data breach 2022.
CDOs
A Chief Data Officer helps steer a business to its strategic vision through a data strategy, embracing data as a competitive advantage. As data volume grows, managing the health and quality of data sets becomes more challenging, too; according to Gartner, every year poor data quality costs organizations an average USD 12.9 million.⁵ Data observability helps data teams and engineers better understand the health of data in their system and automatically identify, troubleshoot and resolve issues – including anomalies, breaking data changes, or pipeline failures — in near real-time.
For more insights on how to leverage data within an organization, read the Data Differentiator, or find out more about IBM’s acquisition of Databand.ai.