Reduce Downtime and Boost Efficiency with AI and Automation
IT service outages, while inconvenient, also carry widespread ramifications that affect productivity, revenue streams, business reputation, and customer satisfaction. These outages can also drive burnout and increased human error for the IT operations (ITOps) teams tasked with managing the stress that comes with urgent issues and escalations.
To manage these issues, ITOps teams need effective observability capable of facilitating rapid incident identification and reducing downtime. However, not all approaches to observability are as effective as they claim to be. Today’s current observability practices often lack global visibility of hybrid IT environments, fail to offer intelligent insights, and do not actually reduce the need for manual intervention by IT teams.
In order to actually establish effective observability, these teams must first understand what the concept entails.
What is Observability?
A data-based concept, observability suggests that a system’s internal state, including issues and problems, can be determined from the data and outputs it generates. Observability often goes hand-in-hand with infrastructure monitoring, which indicates whether a system is working, to provide contextual data into why it’s not working.
When issues can take hours or days to resolve given today’s complex hybrid IT environments, the right observability tools are crucial to helping engineers quickly identify and solve problems across the tech stack – reducing downtime and increasing efficiency.
However, to enjoy the benefits of global IT observability, you may need to address a few challenges before implementing it.
Challenges to Achieving Observability
While observability is growing in popularity, implementing effective observability across modern hybrid IT estates remains a challenge—but one that can be overcome.
- Manual Processes
Even as tools and workflows modernize, many organizations still rely on human-driven methods for observability. Although tools can help with data collection, search, and visualization, the resulting data still requires human intervention and time-consuming collaboration to pinpoint the root cause of issues. This manual approach can be time-consuming and error-prone, resulting in longer mean-time-to-repair (MTTR), poor experience, reduced operational efficiency, and high costs.
A solution to this problem is observability powered by AI and automation. When your organization uses AI and ML for observability, it can benefit from an intelligent and automated system that provides complete visibility of the hybrid IT environment, identifies and flags issues (even before they happen), and precisely identifies root cause with up to 95% accuracy and 10x faster than using manual methods. This ultimately empowers engineers to handle tasks more efficiently.
- Multiplication of Data and Service Metrics
The volume of data generated by IT systems has grown significantly in recent years, making it increasingly difficult to observe and analyze. While observability tools can assist ITOps teams in collecting and organizing these vast amounts of data, we must also consider the limitations of the human brain. Operators still need to manually sort through an overwhelming volume of traces and logs to identify issues before service is impacted.
Rather than manually sifting through thousands of key service metrics, analyzing traces, and following a paper trail to identify potential triggers for a problem, an AI and automation-based approach to observability can provide accurate, real-time insights into operational status, potential issues, and their impact on services in minutes, not hours.
It can even suggest or initiate automated actions for quick incident resolution, freeing engineers to resolve issues that previously required top-tier expertise.
It’s a proven approach to observability and IT management that reduces troubleshooting time from 24 hours to 5 minutes to drive a staggering 60% improvement in MTTR.
- Digitization and Software Delivery
Given the speed of digitization and the constantly evolving IT landscape, software engineers also face observability challenges. Continuous integration and continuous delivery (CI/CD) practices mean that software systems are always changing. Even if these teams have an understanding of what could go wrong today and the potential downstream business impacts, that knowledge becomes outdated as the software environment changes weekly, if not daily.
By utilizing AI and automation-powered observability, ITOps teams can gain unprecedented cross-domain visibility and human-friendly insights into the diverse and evolving layers of technologies that make up modern IT infrastructure. This includes understanding the dependencies between these technologies and the digital business services they support. Next-gen observability can also identify new or novel problems that have never been encountered before – all without human intervention.
Furthermore, ITOps teams can automatically track configuration items (CIs) as they are added to the IT estate and track relationship changes in real time. This accelerates the onboarding of new technologies, keeps ITOps and DevOps aligned throughout the CI/CD lifecycle, and give businesses a competitive edge.
Take The Next Leap Forward with ScienceLogic
ScienceLogic can help your organization combine the power, intelligence, and automation of AI and ML into your observability strategy.
With AI and automation, you can go beyond simply observing your IT estate and achieve more advanced functionality that works alongside ITOps teams to reduce IT complexity and shift from manual to a machine-powered, automated business. One that is self-aware and self-healing, one that intelligently guides and advises humans on how to maintain the most optimized and efficient IT estate possible, a state known as Autonomic IT.
Autonomic IT delivers unparalleled flexibility. By automating formerly manual tasks and amplifying efficiency, you can reduce downtime and operational expenses, integrate new technologies with ease, and free up resources and capital to build new value-added services and recurring revenue streams.
To learn more about how your organization can embark on this journey and embark on a new approach to adopting and managing IT investments, download our eBook: Accelerate Your Journey to Autonomic IT.