Why You Should Incorporate AIOps Into Your Container Strategy
If you’ve been paying attention to container adoption in recent years, you’ve witnessed its steady growth.
According to a report from Diamanti, 44 percent of the surveyed IT leaders plan to switch from virtual machines (VMs) to containers, and a separate survey shared that, by 2020, 83 percent of enterprise workloads will be cloud-based. We’re forecasting a cloudy, code-based enterprise future and a containerized world. We can also expect it to be rife with noisy, data-filled virtual processes for IT operators to monitor and maintain.
The Monumental Task of Containing the Data Lake
IT operation is currently facing—and will continue to face—a tidal wave of data. With networked and automation-driven devices becoming commonplace smart and connected cars, IT professionals have their work cut out for them.
To help ease the challenges of a modern-day IT infrastructure, the utilization of virtual machines have become a common strategy. But there’s always room to innovate, and now we are tapping the potential of containers. Equally capable of supporting traditional top-down control networks, containers also can assist less-centralized, or edge-based, systems that we’ll see more commonly in future IT architectures.
You might have already incorporated container strategy into your line of work, as 59 percent of IT leaders from the Diamanti survey claimed they already have or plan to deploy containers in a production environment. But if you haven’t, you can make the switch with Docker and Kubernetes. Docker is an industry go-to tool for creating containers while Kubernetes manages and controls the container deployment. Together, both tools ensure fast, safe deployment of code, and IT operators can run them in the cloud, on-premises or locally (in-device) as necessary.
With Docker and Kubernetes keeping containers in step with each other throughout their life cycle, employees can focus on more important tasks than keeping the lights on. Better yet, switching to containers can actually save money. Even easing into the adoption usually pays for itself, dollar for dollar.
Evolve Your Incident Management Processes with AIOps
If you’re currently facing a digital transformation toward a cloud-based infrastructure, now is also an ideal time to implement a container-centric architecture. A primary focus should be ensuring the organization’s incident monitoring systems are capable of handling huge data streams. If not, maintaining the steady uptime and efficiency that an enterprise system requires will be impossible. If that’s not enough, tools may lack the power of penetrating and analyzing data within and between containers.
Enter artificial intelligence for IT operations, or AIOps. Utilizing automation is crucial, as it grants the ability to see what’s inside these containers to track and analyze the information generated.
Thankfully, AIOps is already available to be utilized alongside Kubernetes and can correlate container-swarm orchestration data with system alerts and logs. This enables the IT team to recognize root causes of issues with pinpoint accuracy from a single application. What’s more exciting is that this is all possible even in the most complex scenarios, such as when various components are containerized in separate public clouds.
The Heavy Cost of Falling Behind
Traditional incident management systems may have served us well in the past, but they’re simply not able to handle increasingly high data volumes in a world moving toward container-based architecture. Not only will it be difficult to manage alerts today, but anticipating future problems is out of the question.
Practicality is key. Monitoring everything and resolving issues quickly can only be accomplished when personnel aren’t wasting thousands of hours manually seeking the hidden sources of errors.
Pairing AIOps platform and container adoption streamlines and organizes data flow while granting flexibility in unique decisions such as deploying your current services, maintaining the flow or developing an entirely new one. The alternative could be drowning in both data lake and VM fees as you watch others rise to the top.
