5 Steps towards building Autonomous IT Ops
“Organizations can reduce the number of application outages by at least 50% and simultaneously deliver services 50% faster by automating 70% of their network change activities.”–Gartner
Automation, AI, Machine Learning, IoT are common-place within enterprises today. Businesses are already experiencing and implementing these solutions. They are, however, being implemented at an application level, with each application siloed from the next.
An ‘Autonomous Enterprise’ is one where automation and Artificial Intelligence solutions are integrated into the enterprise systems and are connected to every business process, applications, devices, and users. An autonomous enterprise has the ability to self-drive, self-monitor, self-analyze, and self-optimize, often around business-critical processes and applications with little to no human intervention.
But why automate processes within an enterprise? Apart from its obvious benefits and simply ‘because we can,’ automation also resolves modern-day problems faced by enterprises:
Organizational Challenges That Call for Automated Infrastructure & Operations
- Increased endpoints within an enterprise
Maintaining uptime, optimal performance, and security within an enterprise becomes a challenge as the number of users, devices, and applications increase. Manual configuration and monitoring leave vulnerabilities to downtime.
- Need for integration between IT and business
Technology and business processes within an enterprise need to work in tandem (and not on a supplementary level, as is often seen today), especially since there are technological solutions available today that can catalyze the achievement of business goals.
- Agility for quick adaptation to changes
Enterprises need to be able to adapt to changing business, economic, user, and technological landscapes quickly. The recent COVID-19 pandemic and the ensuing global lockdown is a clear example as to why businesses need to be prepared to execute quick operational changes.
- Need for enhanced enterprise security
Security is always the number one priority for an enterprise. With the diverse range of devices, software, and applications entering the enterprise network, and also with the network perimeter expanding to accommodate remote workers, potential vulnerabilities increase. Human-managed tracking, monitoring, and troubleshooting are not sufficient anymore.
- Better user and device management
The increased number of endpoints (owing to a large number of users and multiple devices/applications per user) makes administrative tasks and management a challenge. Admins lack accurate information needed to apply enterprise-wide secure and standard policies.
Building an Autonomous Enterprise
Building an autonomous enterprise depends on the type of business, existing infrastructure, and the ability to expand. There are, however, some areas of automation that form the foundation for any enterprise:
- AI-Driven Analytics
AI-enabled analytics is the most important aspect of building an autonomous enterprise. An analytics system that tracks, monitors, analyzes, and draws insights from all endpoints (devices and users) within the enterprise is essential. An ‘AI-enabled’ analytics solution is capable of deriving insights from accumulated data, and these insights form the basis for all further automated action.
- Analytics-driven automation
Automatically reacting to insights derived from the analytics system is the next step to achieving a fully autonomous infrastructure. ML (machine learning) and behavioral monitoring can be used by the system to define a standard activity, and any anomaly can then be detected and automatically corrected. For example, analyzingcloud usage within an enterprise will provide insights on high traffic days/times, and the network can automatically and proactively adapt (by limiting the number of devices/user, throttling, etc.).
- AI to supplement HI
Supplementing (or in some cases replacing) human intelligence with AI is key to building an autonomous enterprise. Identify areas where business processes that are being manually run can be better handled with automation and implement an automated solution, and then tie different solutions together.
For example, instances causing downtime of applications and services can be predicted and auto-apply fixes. This automatically improves an enterprise’s ability to close instances quickly for high availability of applications.
- Software-driven infrastructure
Infrastructure can be defined as usable resources (tangible like workstations and intangible like personal device connectivity). Driving infrastructure allocation and adjustment automatically via software is the next step in building an autonomous enterprise. For example, in a manual scenario, a user who wants to connect their personal phone to the enterprise network would need to contact an administrator, but in an autonomous enterprise, the user simply attempts to connect to the network, and the software-driven solution checks access level and takes a decision.
- Open architecture
Enterprises inadvertently have an open architecture in place – a business-controlled network, and vendor/cloud architecture integration. For a fully autonomous enterprise, the network should have the capability to interact with all endpoints within the business ecosystem (this includes vendor and external architecture that comes within the scope of the enterprise) in order to fulfil business demands.
Final Words – The Benefits of a Fully Autonomous Enterprise
Now that the need for an autonomous enterprise and the process of implementing it is defined, let’s look at the result of automating enterprise processes:
- Proactive operations instead of reactive
AI-enabled analytics and automation systems have the capability to monitor, infer, and react faster than manually-run operations. Enterprises get the benefit of proactive troubleshooting and resolution as opposed to reactive in the case of manual operations.
- High-level visibility
When needed, enterprises can get a complete high-level (and at a macro-level) overview into all the usersand applications within the enterprise network. The business can also access insights derived from the autonomous network to improve manual tasks. For example, improving customer personalization from behavior analytics drawn via AI and ML.
- Improved experience
Proactive issue resolution, automated resource allocation, and personalized interaction enhance the experience of employees and customers of the enterprise.
- Higher level of security
Finally, an autonomous enterprise has a higher level of network, infrastructure, and data security as opposed to manually-driven operations. Proactive issue detection, load distribution and root-cause analysis contribute to building a highly secure enterprise.
If you’re looking to implement AI for IT operations in order to build an autonomous enterprise, our Matilda Cloud’s platform is the right fit for you. Matilda Autonomous IT Ops platform embeds AI into every aspect of operations. Whether it is wrangling data across silos for real-time insights, proactive monitoring, or delivering deep performance intelligence automated by machine learning, we have it covered.
Schedule a demo to experience the power of an automated enterprise first hand.