This article was originally published in Dataversity.
Today, businesses are implementing new applications and adopting new technologies to become more agile, efficient, and responsive. As part of those efforts, they are employing more cloud-based solutions, software-centric and microservices architectures, virtualization and containers.
In addition, hybrid IT is now table stakes in most enterprise organizations. The dynamic and increasingly complex nature of hybrid IT creates new challenges and makes it difficult to operate efficiently. For example, Gartner predicts that by 2020, more than 50 percent of global organizations will be running containerized applications in production, up from less than 20 percent today. The upside of containers is that they offer portability and greater scalability. However, containers move around a lot, they appear and disappear in the blink of any eye. That in itself multiplies the number of moving pieces exponentially.
IT currently has many disparate tools that collect data. Big data is no longer enough – IT operations needs to gain deep insights into their distributed multi-vendor, multi-domain and multi-technology IT infrastructure in order to meet their challenging business objectives and data correlation is critical.
We need new tools that collect and correlate information about the application itself and about the underlying infrastructure. That should include data about application server performance, events, logs, transactions, and more. The compute, network, and storage resources involved in application delivery also need to be figured into the equation. Only with this full complement – and correlation – of data can organizations understand what is happening with their applications. That is important to ensure applications perform as expected to yield the desired business results.
AIOps Sees Everything…and then some
Artificial Intelligence for IT Operations (AIOps) changes IT Operations by correlating, visualizing and predicting business affecting issues across hybrid IT stacks. It allows IT operations unprecedented visibility into the relationships between every entity in your IT ecosystem.
Let’s take a look at what machine learning for AIOps can do for you.
Application and Infrastructure Inventory – With the complexity of running multifaceted, multi-tier enterprise applications, do you really know what you have in terms of infrastructure and application assets? AIOps with machine learning technology map all the relationship between all of the entities in your IT ecosystem. Before you continue to invest in your stack, you have to know exactly what is in your stack and how it works together. You need to see an accurate and complete inventory of application dependencies so that you know the potential impact of changes and plan transitions and migrations that will not affect the application performance monitoring of business critical applications.
Optimum End User Performance – With AIOps, monitor performance from an end-user’s perspective from transaction through each aspect of the datacenter ensures high performing applications for each individual transaction—with no blind spots—including front end, application performance, infrastructure, containers, and cloud. High-performing customer-facing applications help increase revenues, customer satisfaction, and business agility.
Quickly Identify Root Cause – AIOps maps the flow from applications to infrastructure, including application flows, and virtual and physical compute, network, and storage locations. With these maps, you reduce the complexity and can rapidly drill down, see anomalies, and rectify the situation quickly.
Predict Problems Before they Happen – Increase uptime and performance with AIOps predictive analytics. AIOps correlate data and uncover patterns, which allow your organization to discern what problems are likely to appear downstream from trouble spots. Predictive analytics enable companies like yours to address potential problems before they impact applications and business operations.
Get More Out of Your Cloud Investment – AIOps provides intelligence on application performance so businesses can better allocate resources. The data correlation capabilities reveal what specific resources each application requires. This mitigates the risk of overinvesting and helps you purchase only those cloud resources your applications require.
Traditional, domain-centric monitoring and IT operations management tools are now inadequate because they can’t correlate the onslaught of data various IT domains create. What’s more, they’re unable to provide the insights IT operations teams need to proactively manage their environments – and that just doesn’t work.
IT organizations need a new class of technology to modernize the IT operations process. This technology needs to be able to correlate millions of data points across all IT domains. It should have the smarts to apply machine learning to detect patterns and it should present that information so organizations can easily see what’s happening and gain insights. This technology is AIOps.
About the Author
Enzo Signore, Chief Marketing Officer, Fixstream is passionate about building and growing businesses. He brings a wealth of industry and marketing experience, having led the go to market strategy of early stage companies and established leaders like Cisco and Avaya. Most recently Enzo was the CMO at 8×8, a public SaaS communications company and 5-times Gartner Magic Quadrant leader. Prior, Enzo was responsible for marketing at Avaya, a $4B communications company and for marketing and sales at JDS Uniphase, the leader in optical and test & measurement solutions. Earlier Enzo lead the DSL and Cable business at Cisco, and helped two early stage companies (Retix and ISOCOR) grown from Series A to successful IPO’s. Enzo loves to travel, play sports and is an avid Torino soccer fan.