Data Center Automation is the Future - Here's Why

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Tuesday, December 8, 2020

Automation solutions are likely to be an essential part of future data centers. What do you need to know?

Article 4 Minutes

To stay competitive in today's environment, paying close attention to how you manage your resources is vital. But while many businesses may focus on ensuring their operations are efficient and their supply chains are working as smoothly as possible, there's one vital resource that's critical to every company's success - data.

Data has long been described as the 'new oil', and this means organizations need the correct infrastructure in place to handle it. But with the volume and variety of data growing all the time, and increased requirements for real-time information, legacy data centers can often struggle to cope with these demands.

Today's data centers therefore need to be bigger and faster than ever. As such, modernizing these parts of the network is essential if businesses want to compete. And a key part of this is increasing the use of automation.

The emergence of the automated data center

Data center automation has become a hot topic in recent years, but thanks to emerging technology such as artificial intelligence (AI) and machine learning, it’s become more practical and more cost-effective than ever.

Indeed, according to one study, the global market for data center automation technology is set to reach as much as $17 billion by 2027, up from $4.9 billion in 2020. While this has been coming for some time, these trends may have only been increased by the impact of COVID-19 lockdown restrictions around the world in 2020.

With key data center workers among those affected, the need for management solutions that can be conducted remotely or autonomously has grown, and this is a trend that’ll stick around for many years to come.

How data automation works

What does effective data center automation look like? Essentially, this involves automating key management, monitoring and maintenance tasks that would previously have required human interaction.

This is typically achieved via software solutions that can offer centralized control over the data center. Tools such as AI can then conduct a wide range of operations to ensure the smooth and efficient running of the facility.

Key features offered by data center automation tools include:

  • Creating and running scheduling and monitoring tasks
  • Managing routine processes such as patching, updating and reporting
  • Providing insight into the performance and configuration of server nodes
  • Ensuring agreed standards, policies and processes are being followed

The importance of improving your data center automation

Data center automation can bring many benefits to a business. Done effectively, it streamlines operations, ensures these facilities are operating as efficiently and cost-effectively as possible and enables data center professionals to respond more quickly to changing demands.

One area where it can also help is in reducing downtime. In many legacy data center operations, administrators would have to schedule in periods of downtime for evenings or weekends in order to perform upgrades or updates. But with automated data centers, this can be avoided. What's more, the ability to automatically monitor and respond to any issues can cut the risk of unplanned downtime through predictive maintenance.

Among the other advantages that data center operators can expect as a result of embracing automation technologies are:

  • Improved flexibility and scalability
  • Faster application provisioning
  • Reduced complexity
  • Improved utilization of resources
  • Better control and manageability

The keys to an effective automated data center

While the benefits of implementing automation within the data center are clear, how should businesses go about that, and what solutions will they need in order to make such efforts a success?

Technologies like AI will be an essential part of managing such facilities, but these solutions can only operate effectively if they have the right information available to them. Any machine learning system is only as good as the data that's fed into it, so any gaps can leave automation ineffective. It's also important to remember that these systems improve over time as they gather more data about the environment and use it to refine their algorithms and decision-making

This means that real-time visibility into every aspect of the data center is essential to automation. If the software can’t see what’s going on in a certain server node, it’ll be unable to respond effectively. Problems can occur anywhere within the infrastructure and cause ripple effects elsewhere, so it's essential for data center architects to build deep, real-time visibility into the entire stack, including compute, virtualization and storage resources.

This also ties into the need for effective real-time analytics. These tools should be able to instantly pinpoint the source of any anomalies, diagnose the root cause of the issue and formulate a response plan that sticks to established procedures.

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