How to orchestrate workloads between public and private clouds
Imagine how an orchestra combines a multitude of instruments to create a symphony. In the same way, a hybrid cloud orchestrates, skillfully combining public and private cloud, to create a seamless cloud infrastructure. As multiple applications on a public–private hybrid infrastructure could add to complexities, with the help of orchestration, a centralized structure can be created to allow management of multiple applications using a single interface. Differences in bandwidths, workloads, and access controls can all be managed by this orchestration software.
Integration of different technologies in a hybrid infrastructure determines how effective the orchestration is. For seamless integration, the compatibility between different systems and applications must be ensured, so that orchestration of workloads between public and private clouds is seamless, providing the needed high-performance compute. In the absence of orchestration, enterprises using a hybrid cloud would be forced to manage the public and private clouds in silos, which can put pressure on their resources and demand additional overheads. In addition, orchestration provides the benefit of streamlining resources for coordination, making it easier to manage multiple workloads.
Orchestration on the Private Cloud
A private cloud may not be cheap, but it brings its advantages. It gives greater control over assets and provides enhanced cloud security, resiliency, and flexibility to the system. With private cloud orchestration, automation of the infrastructure could be managed, by establishing workflows that work without human intervention. While private cloud automation would initiate processes automatically, orchestration results in a unified structure of workflows. In this arrangement, resources can be provisioned as needed to optimize the workloads on a private cloud. Thus, an organization can realize savings in engineering time, and IT costs.
What does orchestration involve?
Orchestration enables a coordinated deployment of automation services on the cloud. Cloud orchestration happens at three levels: resource, workload, and service. At the resource level, IT resources are allocated, and at workload level, they are shared. At the service level, services are deployed so that shared resources are optimally utilized. While individual automation only takes care of a single task, orchestration automates end-to-end processes. It is similar to creating a process flow that automates the sequence of automation. The workflows created in the process enable technologies to manage themselves. There are many orchestration tools available in the market that can be used by organizations based on their individual requirements. Some popular tools are Chef, Puppet, Heat, Juju and Docker. Chef is used at OS level while Puppet is more popular at middleware level. Heat is an orchestration method developed from OpenStack, and it can orchestrate everything in OpenStack. Juju is used at the service level while Docker serves both as a tool for orchestration and technology for virtualization.
Workload placement considerations
In a hybrid cloud, both public and private applications generate different workloads. To manage these workloads, and handle their seamless switch between public and private cloud infrastructure, an appropriate cloud strategy is needed. Distributing the workload between different IT assets is a business decision in which regulatory compliance requirements, trade-offs, business risks, cost, and growth priorities are taken into consideration. For instance, certain countries like China may have certain federal restrictions on the use of the internet for which a private WAN can be deployed. The cost could be a concern for an organization looking to provide last-mile connectivity if private cloud is deployed, but with public infrastructure used for addressing service needs of remote locations, cost savings can be realized. A private or hybrid cloud may require establishing an in-house team for IT support while public cloud can work without any, and with limited, cloud expertise in-house.
Technical parameters such as data volume, performance, security, and integration are considered when orchestrating workloads between different cloud deployments. Based on the level of importance each of these attributes carries, workloads can be shifted between the public and private cloud. Public clouds could be deployed for workloads that require a higher level of security but a lower level of integration and performance, such as CRM and information systems. When a continuous demand for a higher level of integration arises, an organization may have to add a private cloud to the IT infrastructure. Workloads like file printing, networking, and systems management may work with either nature of the cloud. However, if data volumes grow, the public cloud would not suffice, and the organization should orchestrate to a private cloud. Applications like enterprise resource planning, data marts, and Big Data analytics make use of high volumes of data that need a private cloud to manage.
A true hybrid cloud allows for easy migration of workloads between public and private clouds. It is always wise to develop a hybrid cloud strategy depending upon workloads, as portability of workloads becomes possible and traditional applications can be bridged with modern applications across the cloud infrastructure. When cloud deployments are planned based on the changing needs of the workloads using orchestration, the enterprise can make their IT infrastructure more optimized, flexible, and adaptive.
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