5 Ways Container Data Storage Can Save Your Organization Money
Most of us have encountered certain issues after preparing a file on one computer and then attempting to open it on another only to discover something isn’t compatible. Even though the file looked perfect and performed well on the first computer, somehow it became glitchy, didn’t look good or failed to run on the second machine. Of course, many unfortunate people don’t realize this until mere moments before needing to use the file in a presentation, conference meeting or sitting with a client.
If that felt nightmarish, imagine having to deal with that sort of problem on a larger scale, like a huge data project for a sizable organization.
With so much at stake in today’s data-centric world, this is a critical issue. The root of the problem lies in how applications or operating systems might be incompatible for one reason or another. If they’re developed by the same company or designed to be compatible with one another, it can be something as simple as overlooking a software update. Nevertheless, no matter how insignificant the issue, the end result could very well lead to big problems, expensive delays or costly fixes.
Understanding Data Storage Containers and Why They’re Imperative
Simply put, a container is a software application that includes all the necessary binaries, libraries, dependencies and configuration files bundled into a single package. Since the container has everything required to operate, users can move it from one computing environment to another without suffering the problems mentioned above.
A perfect example of containers in use is when software developers employ them to safely move newly finished software from their computer to a sandboxed environment; from a physical machine to a virtual machine; from acceptance to production environments, as well as any other tier environment used by developers. Containers allow developers to successfully integrate data into various operating systems. They can also circumvent differences in system infrastructure, software versions, storage, and security protocols.
One should not confuse data containers with virtualization technology since virtualization involves replicating entire operating systems or other software environments. Nonetheless, data containers are adaptable and transportable by design, making them perfect solutions for cloud-based applications—a characteristic that has added to their increased popularity among information systems (IS) and information technology (IT) architects. Many experts believe that as computing and storage increasingly incorporate cloud technologies, containerization will become a more essential tool.
Ways Container Data Storage Solutions Save Organization Precious Time and Money
For those organizations seriously considering investing in container data storage, let’s go over its benefits.
1. Reduce the Amount of Storage Capacity Consumed
Allocating storage for operating system (OS) images will no longer be essential because immutable container images will automatically decrease the volume of storage used—both for primary and secondary storage. Developers can increase storage through standard application programming interfaces (APIs) themselves, which reduces the over-allocation of storage. Developers are afforded flexibility since they can pick and change the storage options depending on the workload; this can be done without having to bother an admin.
2. Sharing Redundant Data Lowers Storage Costs
Container technology shares redundant information between containers and lowers storage costs. However, even when utilizing container data storage solutions, organizations need to monitor their data collection and management methods to ensure they don’t get out of hand. Those organizations already using data container storage have learned the hard way that failing to establish solid data tiering and management policies, as well as encouraging data sprawl is a waste of money.
3. Streamline Storage Operations
Data container technologies that can automate application deployment, scaling, and management can improve staff performance and efficiently by automating allocation and deprovisioning—storage management is reduced thanks to eliminating server-specific application dependencies.
4. Ephemeral and Stateless Architecture Reduces the Need for Persistent Storage
Significantly reduce the need for persistent storage by adopting an ephemeral and stateless architecture; two things data container technology offers that directly correlate to a reduction in the volume of storage required to maintain enterprise activities. Containers enable organizations the ability to efficiently construct stateless applications, eliminating the need for them to rely on persistent storage or having volumes linked to each individual pod.
5. Reduce Wasteful Repetitions
Considering the information covered above, one begins to understand that solely thinking of storage in conventional terms results in unwanted waste and stagnation. In the context of enterprise data storage, one must look at the compute fabric that supports data containers in a different way.
Storage must no longer be held as an independent focus or a maintained as siloed technology. Traditional ways of managing data storage can no longer hope to support the growing needs of today’s organizations—organizations require an effective delivery model, sufficient management, and simple operations, all of which are powered through code and conveniently available via APIs. To learn more about this topic or RAID Inc. enterprise storage solutions, please feel free to contact one of our data storage experts today.
