You might have heard of the phrase "canary in the coal mine," which refers to an indicator of potential danger or failure ahead. In the tech industry, these potential failures could be catastrophic, as anomalies in applications negatively impact the performance, customer experience and business outcomes. As we have seen during this digital transformation boom during the pandemic, technologists are managing more applications and data than ever before, which has led three quarters of technologists to be concerned with increased IT complexity.
Even more significant, 89% admitted to feeling under immense pressure to keep up with the churn, according to the recent AppDynamics Agents of Transformation report. It's clear that the pandemic has pushed many technologists to their breaking point. To help tackle IT burnout, tech professionals need a "canary" to help them streamline and catch the anomalies before they cause any major performance issues.
The Canary is Full-Stack Observability
Businesses have fast-tracked their digital strategies, moving toward technology like cloud computing to meet storage and speed demands. As a result, technologists have not only had to continue to manage their initial applications running the business' digital properties, but now also the new applications from the cloud. For technologists to manage the deluge of data, relieve them from the pressure of having to manually monitor each domain of the IT stack, and catch and fix issues before they disrupt business, they need to consider implementing a full-stack observability strategy.
Full-stack observability enables technologists to have visibility into the full IT estate — current and new, on-prem, hybrid and/or cloud applications — and the ability to connect performance issues or updates directly to their effect on business outcomes. Full-stack observability allows for visibility, understanding, and optimization of what happens inside and beyond architecture.
The advantage of deep business context is that it speeds digital transformation by aligning teams around shared priorities and enables technologists to act with confidence on what matters most. Instead of trying to keep up with the complex and increasing amount of data running through the business' IT stack, technologists can observe everything and understand how what they do directly relates to the bigger picture.
Save Time, Money and Energy
In addition to saving the time that would have been spent on manually monitoring everything, the overview of the IT estate that full-stack observability provides also brings opportunities to save money and energy. When you're looking at your IT stack's infrastructure, network and security domains; you can identify which applications are performing well and the criticality of having access to business context, versus those that are potentially being underutilized or not producing valuable results. This allows you to redirect your finances accordingly, so you are getting your money's worth and optimizing all your applications.
Similarly, your IT team can relocate its energy to supporting the applications that are functioning properly and identify areas where there might be room for the business' digital strategy to innovate or expand.
IT burnout is real and on the heels of the past year's events, it is clear that digital transformation will only continue to evolve going forward. Now that most organizations have had to shift to a digital strategy, they must do more in order to stay competitive, as the bar for digital experiences has increased dramatically.
Give your team the support they deserve and help your business' digital strategy expand by starting the journey with full-stack observability and letting it serve as the "canary in the coal mine," giving teams visibility, correlation back to the app, as well as user and business experience which leads them on their path for success.
The Latest
The 2024 State of the Data Center Report from CoreSite shows that although C-suite confidence in the economy remains high, a VUCA (volatile, uncertain, complex, ambiguous) environment has many business leaders proceeding with caution when it comes to their IT and data ecosystems, with an emphasis on cost control and predictability, flexibility and risk management ...
In June, New Relic published the State of Observability for Energy and Utilities Report to share insights, analysis, and data on the impact of full-stack observability software in energy and utilities organizations' service capabilities. Here are eight key takeaways from the report ...
The rapid rise of generative AI (GenAI) has caught everyone's attention, leaving many to wonder if the technology's impact will live up to the immense hype. A recent survey by Alteryx provides valuable insights into the current state of GenAI adoption, revealing a shift from inflated expectations to tangible value realization across enterprises ... Here are five key takeaways that underscore GenAI's progression from hype to real-world impact ...
As software development grows more intricate, the challenge for observability engineers tasked with ensuring optimal system performance becomes more daunting. Current methodologies are struggling to keep pace, with the annual Observability Pulse surveys indicating a rise in Mean Time to Remediation (MTTR). According to this survey, only a small fraction of organizations, around 10%, achieve full observability today. Generative AI, however, promises to significantly move the needle ...
While nearly all data leaders surveyed are building generative AI applications, most don't believe their data estate is actually prepared to support them, according to the State of Reliable AI report from Monte Carlo Data ...
Enterprises are putting a lot of effort into improving the digital employee experience (DEX), which has become essential to both improving organizational performance and attracting and retaining talented workers. But to date, most efforts to deliver outstanding DEX have focused on people working with laptops, PCs, or thin clients. Employees on the frontlines, using mobile devices to handle logistics ... have been largely overlooked ...
The average customer-facing incident takes nearly three hours to resolve (175 minutes) while the estimated cost of downtime is $4,537 per minute, meaning each incident can cost nearly $794,000, according to new research from PagerDuty ...
In MEAN TIME TO INSIGHT Episode 8, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AutoCon with the conference founders Scott Robohn and Chris Grundemann ...
Numerous vendors and service providers have recently embraced the NaaS concept, yet there is still no industry consensus on its definition or the types of networks it involves. Furthermore, providers have varied in how they define the NaaS service delivery model. I conducted research for a new report, Network as a Service: Understanding the Cloud Consumption Model in Networking, to refine the concept of NaaS and reduce buyer confusion over what it is and how it can offer value ...
