Are Cloud Autonomics, Automated Management and Optimization Around the Corner?

Dusty Simoni

By Dusty Simoni, Senior Product Manager, 2nd Watch

The holy grail of IT operations is to achieve a state where all mundane, repeatable remediations occur without intervention, with a human only being called into service for any action that simply cannot be automated. This allows not only for many restful nights, but it helps IT operations teams to become more agile while maintaining a proactive and highly optimized enterprise cloud. Getting to that state seems like it can only be found in the greatest online fantasy game, but the growing popularity of “AIOps” gives great hope that this may be closer to a reality than once thought.

Skeptics will tell you that automation, orchestration and optimization have been alive and well in the data center for more than a decade now. Companies like Microsoft with System Center, IBM with Tivoli and ServiceNow are just a few examples of platforms that harness the ability to collect, analyze and make decisions on how to act against sensor data derived from physical/virtual infrastructure and appliances. But when you couple these capabilities with advancements brought through artificial intelligence for IT operations, or AIOps, you’re able to take advantage of the previously missing components by incorporating big data analytics along with artificial intelligence (AI) and machine learning (ML).

As you can imagine, these advancements have brought an explosion of new tooling and services from cloud ISVs intended to make the once utopian “autonomic cloud” a reality. Palo Alto Network’s Prisma Public Cloud product is a great example of a technology that functions with autonomic-type capabilities. The security and compliance features of Prisma Public Cloud are impressive, but it also has a component known as User and Entity Behavior Analytics (UEBA).

UEBA analyzes user activity data from logs, network traffic and endpoints and correlates this data with security threat intelligence to identify activities — or behaviors — likely to indicate a malicious presence in your environment. After analyzing the current state of the vulnerability and risk landscape, it reports current risk and vulnerability state and derives a set of guided remediations that can be either performed manually against the infrastructure in question or automated for remediation to ensure a proactive response, hands off, to ensure vulnerabilities and security compliance can always be maintained.

Another ISV focused on AIOps is Moogsoft, which is bringing a next-generation platform for IT incident management to life for the cloud. Moogsoft has purpose-built machine learning algorithms that are designed to better correlate alerts and reduce much of the noise associated with all the data points. When you marry this with the company’s AI capabilities for IT operations, it is helping DevOps teams operate smarter, faster and more effectively in terms of automating traditional IT operations tasks.

As we move forward, expect to see more and more AI- and ML-based functionality move into the core cloud management platforms as well. Amazon recently released AWS Control Tower to ease your company’s journey toward AIOps. While coming with features for new account creation and increased multi-account…