While the opportunities and potential of AIOps (artificial intelligence for IT operations) are massive, as the car commercial disclaimers say, "your mileage may vary." Many organizations are unsure where to begin with AIOps, but should seriously consider adopting an AIOps strategy and solution. To get started, it's important to identify the key capabilities of AIOps that are needed to realize maximum value from your investments.
Why AIOps is a Game Changer
To survive and thrive in today's app economy, your organization needs to deliver innovative, rewarding, and reliable digital services. Your IT teams are tasked with ensuring the performance and availability of these services, and the stakes are high. At the same time, your teams also have to contend with intense demands around accelerating innovation and managing costs.
Meeting these competing, urgent demands only grows more difficult as IT environments keep getting increasingly ephemeral, complex, and dynamic. The proliferating use of containers and microservices, multiple clouds, continuous integration and continuous delivery, and DevOps, are all serving to yield massive increases in the amount of operational data that has to be managed. If it hasn't already happened in your organization, the volume, variety, and velocity of data generated will most likely soon fundamentally surpass human ability to manage.
To contend with this growth, meet service level agreements (SLAs), and support evolving business requirements, IT operations teams are increasingly pursuing AIOps initiatives. According to Gartner's Market Guide for AIOps Platforms, "AIOps platforms combine big data and machine learning functionality to support all primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety and velocity of data generated by IT." What capabilities are really needed to establish a successful AIOps strategy? To start, you must understand the central functions of AIOps platforms, which include ingesting data from multiple sources, enabling data analytics, employing machine learning, and more.
Key Requirements for Maximizing the Value of AIOps
To quickly and pragmatically realize maximum value from AIOps, it's important to build on the foundational capabilities above. You should look for an AIOps solution that not only leverages big data and machine learning, but also employs the specific code, functionality, and algorithms that make it easy to apply these capabilities to your specific IT operations use cases. In addition, your teams need advanced capabilities like automated event remediation and service resolution, optimized cost and capacity management, and proactive vulnerability mitigation. Ultimately, these capabilities will enable your team to realize more value from your AIOps investments, and do so much more rapidly.
1. Automation: By harnessing AIOps and advanced automation, your organization can fully leverage insights being generated by data aggregation. Following are two key areas where this automation can be applied:
■ Automated operations. Your teams can establish automated remediation workflows to speed mean time to resolution. You can automate commonly recurring tasks, such as restarting services, cleaning up temporary resources, and provisioning additional capacity.
■ Automated service resolution. Your teams can institute automated, closed-loop processes with service desks, from ticket generation to close. With integrated capabilities for service modeling, they can implement more intelligent routing and prioritization of incidents based on business impact.
This automation can fuel a range of significant benefits. Your teams can reduce the cost and risk associated with many manual, labor-intensive tasks, and minimize the repetitive tasks that can burden your skilled IT resources. Even more importantly, these capabilities can yield faster diagnosis and remediation, and therefore boost service levels, customer satisfaction, and SLA compliance.
2. Cost and Capacity Optimization: By augmenting AIOps with integrated cost and capacity optimization capabilities, your teams can move beyond performance management, and begin to better optimize your resources and investments aligned to business demands and requirements. The combination of artificial intelligence, machine learning, and capacity and cost management can deliver powerful capabilities for more intelligently managing both on premises and cloud-based resources including:
■ Predictive budget management alerts that leverage advanced algorithms to help identify expected cost overruns, beforehand.
■ Recommendations for optimizing resource sizing, which can then trigger automated actions such as terminating idle resources or right-sizing existing ones.
■ Automated, policy-based analysis and remediation of cloud resource misconfigurations.
With these capabilities, you can effectively model the impact of resource changes and do more intelligent cloud migration planning.
3. Security Operations: For today's organizations, it's vital to quickly find and fix the vulnerabilities and misconfigurations that jeopardize security. It's even better to keep these gaps from occurring at all. By harnessing complete AIOps platforms that incorporate security operations capabilities, your organization can significantly reduce risk. To realize maximum security improvements, you need solutions that help your teams realize these outcomes:
■ Find and fix vulnerabilities and misconfigurations that compromise security and compliance.
■ Employ machine learning algorithms to intelligently and quickly route information on vulnerabilities, violations, and issues.
■ Predict security misconfigurations through anomaly detection of asset configurations.
With the right AIOps platform, your teams can start harnessing advanced capabilities in such areas as automation, cost and capacity optimization, and security operations. With the right solution, you'll be able to meet your most critical objectives — including optimizing service levels, making smarter investments, and speeding innovation. As you evaluate AIOps solutions, remember the foundational requirements for establishing a sound AIOps platform and strategy.