Subscribe Here!

Moving to Cloud? Here's How a Hybrid Approach Can Help

by Michael Le – May 8, 2018

Today, the growth of unstructured data is scaling beyond what traditional legacy storage and backup softwares were designed for. While advances in cloud architecture from AWS, Microsoft Azure, and Google Cloud present solutions for managing enterprise data, many enterprises face obstacles to adopting cloud and stick with legacy storage and backup software as a result.

Challenges of Cloud Adoption

Enterprises face significant obstacles that prevent them from moving to cloud.

For one, the sheer size of their data makes the process of migrating to cloud difficult. Datasets generated from on premises machines and sensors can be too big to move to cloud and access without impacting performance, since accessing data stored in public cloud relies on network speed.

Many enterprises also have regulations set in place prior to the advent of cloud, which means that adopting new technologies such as cloud often conflicts with compliance.

Another barrier to cloud adoption is that traditional IT lacks the skills required to manage a cloud environment, according to Gartner.

These are all common obstacles that prevent enterprises from adopting cloud. Despite the challenges, a need to address the growth of data will lead many enterprises to include cloud in some form in their data management strategy. The Wall Street Journal found that “25% of total application workloads will be running in the cloud by the end of the year, up from 20% currently, and will increase to 44% by 2021.”

Benefits of a Hybrid Cloud Approach

Instead of a complete infrastructure overhaul, enterprises can take one step towards cloud by adopting a hybrid approach. Gartner research shows that for those enterprises seeking a hybrid approach, many will still be utilizing the same on-premises legacy storage to move forward.

Instead of tearing out existing IT infrastructure and all the expensive NAS appliances in place, a hybrid strategy integrates with on-premises legacy hardware. This enables a modern approach to data management, which uses cloud as a repository for cold, less frequently accessed data.

However, sending massive unstructured file data to cloud and being able to find and access it requires a unique approach in the hybrid strategy that won’t impact performance and create bottlenecks in the network, while always keeping data secure and protected.

Using Igneous in Your Hybrid Cloud Strategy

Enter Igneous Hybrid Storage Cloud. Utilizing both on-premises storage and public cloud storage, Igneous provides a solution that addresses many of the challenges faced by enterprises in adopting cloud today.

Here are just a few of the benefits of using Igneous in your hybrid cloud strategy:

  • Igneous provides API integrations that work with current legacy storage systems along with the new storage solutions enterprises plan to replace them with.
  • Igneous Hybrid Storage Cloud provides security that meets compliance by keeping and managing data behind the firewall in environments where compliance has already been met.
  • Igneous addresses the concerns of skills needed to have a staff capable of managing cloud by offering our product as-a-Service, where our Remote Management Platform handles all monitoring, diagnostics, failure management, and software updates.

Learn more about our cloud-tiering and other features on our Product page.

learn more

Related Content

Archive Calculator: How to Save Money with Archive to the Cloud | Igneous

December 6, 2019

Efficiently utilize cloud tiers to mitigate storage costs

read more

The Economic Benefits of the Igneous Channel Program

June 12, 2019

A Special Note from Igneous' new VP of Channel Sales

read more

PAIGE and Igneous Build Industry-Leading Compute Cluster for Healthcare AI

January 16, 2019

PAIGE’s mission to revolutionize the diagnosis and treatment of cancer through machine learning requires an extremely large dataset of high resolution slide images. To do so, they are building an industry-leading compute cluster for healthcare AI. The team needed to not only protect all of this unstructured data, but also programmatically move and process small subsets of the overall dataset on demand for high performance computations.

read more