Data Centers

Reevaluate skills expectations for engineers working in cloud-based data centers

Managers and engineers need to stay abreast of the skills needed to work in a cloud-based data center. These are the basics to explore.

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The enterprise data center is evolving. The catalyst for this evolution has been cloud and converged infrastructure. The cloud service model along with the supporting technologies of network virtualization and storage virtualization are breaking down the walls in the traditional IT infrastructure.

From an organizational view this means more than having the storage, server, and network engineers reporting to the same manager; in this transformation process, the IT organization looks very different in the end. The skills mix needed to run a data center built to deliver a cloud is different than the traditional data center.

The transformation of the data center creates a problem for engineers and data center managers. The data center manager needs to understand what skills to look for in their existing personnel, while engineers need to understand what skills to pursue. We'll take a look at several areas that managers and engineers looking to retool for the cloud should explore.

DevOps and automation

The cloud infrastructure adds value by enabling end user applications to better leverage the underlying infrastructure. The advantage of fronting an infrastructure with a cloud management platform such as vCloud, CloudStack, or OpenStack is to enable application level control of the infrastructure. However, this doesn't indicate that end user applications will start making API calls to the infrastructure directly.

Unlike monolithic applications such as Facebook and Google Search that manage the infrastructure directly, enterprise cloud applications will leverage a DevOps layer. DevOps is the practice of using software code to automate the control of the underlying infrastructure. The job of DevOps teams is to leverage features of the cloud infrastructure without knowing the details of the infrastructure.

Examples are: leveraging the DevOps layer to dynamically spin-up additional application servers, provisioning networks, and adding load balancers as demand from the application arises. Puppet, Chef, and vRealize are platforms that can be leveraged to create workflows that automate the infrastructure. The orchestration of the underlying infrastructure is enacted without the developer of the end user application being aware of the underlying infrastructure. The enterprise data center needs infrastructure engineers turned developers to enable this capability.

Service management

More than ever, service management is a critical part of the infrastructure. Most enterprise infrastructure teams are accustomed to service management being a separate team. The need for a higher-level service management team will continue to exist; however, infrastructure teams will find themselves managing vendors and services on a micro-infrastructure level.

Infrastructure services may be provided by on- or off-premises infrastructure as the data center becomes an abstracted concept. EMC gave an example of leveraging AWS-based storage to achieve close to one million IOPS for an AWS-hosted application; the test shows the potential of mixing workloads in a hybrid cloud. Infrastructure teams will need to be adept at negotiating service contracts as well and overseeing the management of multiple vendors in order to provide a complete data center solution.

Virtualization

While not a new skill, virtualization has become the de facto method of data center abstraction. Even if your organization is looking to leverage hardware-based technologies such as ACI, there will still be a strong requirement to understand virtualization at each discipline of the data center. The large influence of server virtualization within the data center dictates that network and storage engineers have a deep understanding of the technology. Storage and network vendors are introducing solutions that run as virtual appliances on top of virtual infrastructures.

In the networking discipline, Network Function Virtualization (NFV) has quickly become a large part of any network deployment. NFV solutions include firewalls, virtual switches, and load balancers. These solutions are highly integrated into the fabric of the enterprise data center network.

Storage is also seeing a large uptick of virtualized appliances. EMC recently announced a virtualized version of the popular replication solution RecoverPoint. It would be very difficult to avoid virtualization in the modern data center.

Conclusion

Managers and engineers need to evolve their workforce mix and skills continually to meet the demands of the cloud-based data center.

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About Keith Townsend

Keith Townsend is a technology management consultant with more than 15 years of related experience designing, implementing, and managing data center technologies. His areas of expertise include virtualization, networking, and storage solutions for Fo...

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