Cloud computing can provide a number of benefits to an organization, including access to more powerful IT infrastructure, increased efficiency, flexibility, and easier management. But implementing a cloud architecture isn’t always a simple task. Besides the time, money, and effort involved in migrating on-premises systems and data to the cloud, enterprises often have to deal with a diverse array of technologies, regulatory requirements, operating models, and working environments.
Successful adoption of cloud requires a combination of elements: an understanding of the technology, a clear set of objectives, and a comprehensive strategy, among others. In this article, we’ll be looking at some best practices for implementing a cloud computing architecture.
Get Stakeholder Support for A Commitment To Cloud Architecture
Your organization may be moving its IT infrastructure to a private, public, or hybrid cloud for any number of reasons. Despite the advantages that such a shift may offer, there will inevitably be changes to the way things operate that may not go down so well with everyone. Once you make a commitment to implementing a cloud architecture, it’s therefore important to get your stakeholders on board as early as possible in the process.
Bringing all these people together for a full and frank discussion of the project and all of its implications is a necessary first step. The issues raised in this forum will also provide guidelines for what needs to be covered in your change management and communications strategies, moving forward.
Set Up A Cloud Computing Business Office (CBO)
Setting up a cloud business office (CBO) as an independent unit dedicated to all things cloud in the enterprise provides a single hub for implementing and monitoring your change management program. The CBO can serve in establishing the business case for your move to the cloud. With centralized tools and analytics, it also provides an administrative hub with oversight into all aspects of your cloud deployment.
Make an Inventory Of Your Existing IT Assets
By making an inventory of your existing applications and systems, you’ll be in a better position to determine which tools and processes can be migrated to the cloud immediately, the ones that can wait, and those that may be better off left on-premises.
Particularly with a hybrid cloud architecture, where some resources remain on site while others move to a public cloud, there’s also the issue of application compatibility with platforms like AWS, Microsoft Azure, and Google Cloud. In addition, it’s important to establish the volumes of data that will likely be moving between on-premises applications and the cloud, tolerable degrees of network latency, and any critical inter-application dependencies.
Make A Thorough Assessment of Your Cloud Computing Options
Not all cloud providers were created equal. Before choosing a cloud partner, it’s important to exercise due diligence on them, and to make a detailed analysis of their cloud’s dependencies and constraints, migration patterns, potential applications, and any infrastructure as a service (IaaS) options that they offer.
Develop A Data Migration Strategy
Each organization’s migration to the cloud will be unique, and influenced by its specific circumstances, existing infrastructure, business objectives, and cloud resource requirements.
For large data sets for example, migration may use a “forklift” approach, where on-premises data clusters are moved to equivalent storage built from the ground up, using basic compute instances in the cloud. Alternatively, the organization might choose a data migration as a service option from the cloud provider, or a gradual transition from on-premises data storage to a hybrid cloud architecture.
Whichever option is most appropriate, your migration plan should be both detailed and flexible enough to allow each data asset to be mapped to its most suitable cloud counterpart.
Choose Technology Compatible with Your Policies for Data Management, Compliance, And Security
Although the cloud security technology used from client to client shows little variance between providers, you’ll need to study the reference architectures of the various solutions on offer, to establish how their security and governance control objects map to the repeatable patterns of your cloud deployment. It’s also important to understand how the standards and regulations used by the control objectives of each solution will map to your cloud program.
Cloud master data management(MDM) solutions should be portable, and have a cloud architecture that supports micro-services. This will enable you to continuously update and enhance your management solution, and have the option of moving from one infrastructure provider to another. The solution should also scale to allow for adjustments in data volume, data sources, and the number of end users.
Traditional hardware-based models for dealing with compliance issues will have to be adjusted for a consumption and software-based cloud architecture. Change management and controls must therefore shift to continuous compliance software, which perpetually monitors and regulates the cloud environment, and provides “software signatures” that check for specific governance and compliance issues.
Build A Minimum Viable Cloud (MVC)
As a working model for your full-blown cloud architecture, a minimum viable cloud (MVC) should be set up initially. Microsoft Azure, AWS, and Google all provide tools for automation programming as the primary means of building such a platform. Its performance and management will serve as a template for your larger cloud migration.
Use Automation to Simplify And Speed Things Up
Cloud architecture allows the enterprise to adopt an “infrastructure as code” approach to handling its IT resources and environment. Scripting and automation are central to this. Just as each of your applications can be implemented and deployed through code, it’s possible to use repeatable automation templates to carry out operational procedures and governance across the cloud.
Similarly, a cloud MDM system may deploy artificial intelligence (AI) and machine learning (ML) features to automate data stewardship processes, and to perform analytics that provide actionable insights for the business.
Prepare to Migrate At Scale
Once your minimum viable cloud has revealed the best ways to implement and manage your cloud architecture, you should adopt a gradual and phased approach, as you migrate more and more of your applications and data to the cloud.
Having established the order in which applications and infrastructure should migrate, you’ll need to set up your cloud computing environment to receive these assets, secure them, and prepare them for full operation.
With an experienced business strategy and IT team, a reputable and reliable provider, the right tools, and a phased and strategic approach to infrastructure, data, and governance, implementing a cloud computing architecture in line with these best practices should bring multiple benefits to your enterprise.