Let’s recap your journey to automating incidents:
1. Your data is clean and precise
2. You’re using the right tools, processes, procedures, and your exec. team/staff are on board
You’re ready to reach a destination where many aspire to visit, but few have actually arrived—the moment of transformation from ITOps to AIOps.
The journey to automating incidents can be tedious, but the arrival is worth it. Automation means finally possessing the ability to solve three of the most persistent IT operational challenges facing today’s enterprise: growth, health, and efficiency.
As is the case with any journey, you need a map that offers clear visibility and guidance to see what’s ahead. That’s where topology, the subject of this last blog, comes into play.
Automation enabled by topology-based context
Since IT is the underpinning for an enterprise’s ability to compete in today’s digital society, many organizations are at a point where they are evaluating existing infrastructure investments against business plans. As a result, according to the Digital Enterprise Journal, “37% [are] looking to replace their IT Operations solutions to be able to support new technologies in 2018.”
Caught between desire and decision is a tough place to be, but whether you stand pat, evolve incrementally, or rip-and-replace, the way forward requires a foundation where you’re able to consume every bit of data emitted, map it in a meaningful manner, and present it in a context (in real-time) that allows you to evaluate and measure the cycle of network health.
Context imparts clarity to your view of network health and the efficiency of your operations, even as it keeps pace with growth. It ensures that every element of your network, data center, and infrastructure are mapped relationally to a function and desired result. A topology map that connects applications to their underlying infrastructure is of critical importance to providing holistic service visibility.
These are the insights you need to move your business forward because when you have complete discovery, topology and context you can identify:
• What’s broken (or showing signs of breaking);
• Changes in the IT environment;
• The relationship between new and existing technologies;
• How infrastructure relationships affect the business;
• What actions are needed to address the situation – such as adding capacity, migrating services or taking corrective/preventive measures.
(An example of topology mapping pulled from the ScienceLogic SL1 platform)
Without topology and context, you are generating noise and noise keeps you from trusting your data. When you can’t trust your data, you can’t automate.
On the other hand, a dynamic, comprehensive topology that allows you to manage network growth and health within an IT framework in real time builds necessary trust in the data that your network is producing. When you trust your data, you’re able to achieve more efficient operations. Possessing confidence in the data – along with implementing the proper processes and procedures – is the key element to automation’s role in achieving maximum efficiency since it means more than merely effecting a process for performing repetitive functions.
Parting advice
Not every benefit of automation is technical. One significant advantage that IT automation affords is that it provides relief to workers who are over-tasked and enables more efficient allocation of labor. Instead of spending most of their time chasing down menial tasks, your team is now freed and capable of focusing on higher value activities and service innovation. That freedom can translate to areas affecting revenue and customer retention (we’ll tackle that subject in the future).
That’s it! We hope this blog series helped you identify the steps needed to automate incidents properly. Click here to learn more about the ScienceLogic approach and how we’ve helped companies save invaluable time and resources.
Related Blogs:
Part 1: Are you seriously ready for AI and ML in incident automation? (Obtaining clean and precise data)
Part 2: Are you seriously ready for AI and ML in incident automation? (Processes and procedures)
