Does automation actually reduce our burden or trammel us more?

There is this classic saying, unequivocally a faulty assumption, “if it ain’t broke, don’t fix it” — assuming that all systems are operating the way they should be.

When managed under traditional server administration, automation often faces the same set of age-old IT problems. No IT team enjoys the experience of an outage, especially when it kicks off a race for your team to implement its emergency procedures. That’s ironic, isn’t it? cos automation came to lighten us up & definitely not to enlighten us with what we don’t want it to offer us. Yeah, that’s right!! the unintended unprecedented errors!! Not to mention the cost of workforce implemented to fix them but also the goodwill of customers.

Automations should be defined in a way where human intervention must not be within scope yet often requires tiresome long hour parameterizations & definitions from workforce, also automations should be robust enough to stand against the testament of time. Some popular widely adopted options in the market include shell scripting, Configuration management tools like Ansible/Puppet/Chef, Workflow/RPA tools like Power Automate/UiPath which can mimic the human actions based on rules defined. While these offers automating routine tasks, job scheduling & software deployment, there are some potholes to leap, such as,

1. Complexity: Writing and maintaining shell scripts can be complex, especially for large & intricate automation tasks. Scripts may become harder to perceive, debug, and maintain over time.
2. Limited Customization: Workflow automation tools may have limitations in terms of customization or extensibility, restricting users’ ability to implement complex workflows or specific business logic.
3. Dependency: Workflow automation tools rely on external services and APIs, which can introduce dependencies and potential points of failure if those services experience downtime or disruptions.
4. Scalability: Scaling RPA initiatives to handle a large volume of tasks or across diverse environments may pose challenges, particularly in terms of managing robot deployments, scheduling, and resource utilization.
5. Human Oversight and Error Handling: Above automation options may require human oversight to handle exceptions, errors, or unexpected scenarios effectively, especially in tasks requiring judgment or decision-making (the most sensitive drawback, which renders the purpose of automation as obsolete)

I can hear you questioning, what’s the solution? what can handle which automation can’t? well, your prayers have been answered. Let me introduce you the underrated & under-utilized solution — Self healing.

Self-healing is an autonomous & personalized AI to handle your IT infrastructure the way you want. It can significantly enhance IT infrastructure management by introducing intelligent capabilities to detect, diagnose, and remediate issues truly automatically. Let’s delve into some key capabilities of Self-healing,

1. Autonomous Issue Detection: AI algorithms can continuously monitor the IT infrastructure for anomalies, performance degradation, or potential failures. By analyzing humongous amount data in real-time, AI can swiftly identify issues before they escalate into major problems.
2. Effective RCA: AI can deep dive & analyze complex dependencies within the IT environment to determine the root cause of issues. By understanding the underlying anomalies, self-healing can implement effective remediation strategies.
3. Automated Remediation: Once an issue is detected and diagnosed, AI powered self-healing can automatically initiate remediation actions without human intervention. This could involve restarting services, reallocating resources, adjusting configurations, triggering failover mechanisms & even workarounds to ensure uninterrupted service availability.
4. Adaptive Optimization: AI- powered Self-healing can analyze historical data and patterns to predict potential failures & dynamically adjust configurations, resource allocations, or workload distributions based on changing demand patterns or environmental conditions. By continuously optimizing the IT infrastructure, self-healing can improve efficiency, performance, and cost-effectiveness.
5. Self-Learning & Improvement: AI-powered self-healing systems can learn from past incidents and outcomes to improve their performance over time. By leveraging machine learning algorithms, it can adapt to evolving threats, vulnerabilities, and operational challenges, enhancing their effectiveness and reliability.

Self-healing powered by AI can empower IT infrastructure management to an enormous scale by enabling proactive, intelligent, and autonomous management of complex systems. It enhances system resilience, agility, and efficiency while reducing the burden of IT professionals and improving overall operational reliability.

Keep calm!! Let AI take you by storm!!