How to Speed Up Your Migration to the Cloud with DevOps

DevOps is a key driver in cloud migration

The exponential growth of data in the world arouses the problem of its sufficient organization, sourcing, storage, usage, value and implementation. When mentioning Big Data one should keep in mind that it includes all existing data, from personal to global. A great deal of information content is created by individual users, but the overall responsibility for its storage and management lies with specialized enterprises.

How to choose the right cloud deployment model?

Business enterprises, from small companies to large-scale corporations, must clearly realize their necessity of cloud migration. Data specialists have to evaluate the available computing resources, analyze reliable and open tools, predict possible outcomes and failures and conclude how the enterprise can really benefit from moving to the cloud. There are 3 types of cloud deployment models:

  • Public (cloud data is reposited by a third-party service provider);
  • Hybrid (combines the benefits of on-prem and public storage).

Cloud service providers: Which one to opt for?

There is a broad variety of cloud servers providing the capabilities that can meet the most demanding customer needs. Among the major vendors that offer cloud migration solutions are Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, IBM Cloud, Digital Ocean, Rackspace, etc. Each of them has a unique paradigm of delivering business and data approach, the core essence of which is to provide agile, flexible, reliable, automated, long-term, yet quick services. The DevOps-fueled service type is expected to experience the most rapid growth in 2018–2022 as this model combines the high-level data orchestration and consistent teamwork.

What type of cloud services is right for your business?

In a word, three main cloud service models can be shown as follows:

  • Platform as a Service (PaaS) — build on it.
  • Infrastructure as a Service (IaaS) — migrate to it.

Tapping into the DevOps practices

Moving to the cloud still requires careful steps and deep understanding of the process. Data can be migrated in sets, and then approbation is recommended. If everything goes well, the process continues until the complete migration or otherwise can be declined if it turns out not to be efficient enough. Oftentimes, a specialized guidance of platform architects, operational and developer resources is needed for getting fruitful results.

Getting more control over data in cloud with DevOps

The DevOps model effectively results in better control functions based on shared responsibility and potential. Data specialists (developers, operators, analytics, experts, engineers, scientists) can handle cloud data-related projects on the ground of AI, Machine and Deep Learning, Agile methodology, etc. Data-driven companies easily monitor data flows and market demand. Once having migrated to a cloud server, enterprises enable themselves to leverage software integration, development efficiency and quality assurance.

  • Reliability — clouds enable data transfer, backups and redundancy so you’ll never lose your data;
  • Privacy — data in clouds is available private or public (only on your consent) and will be damaged at any time according to the agreement;
  • Velocity — data operating depends on network connection speed so enterprises should be ready to make necessary technology improvements;
  • Cost — cloud providers usually claim reasonable payment for data storage volume and period;
  • Location — look for cloud servers that are geographically closer to your enterprise.

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