Companies and business owners have long been encumbered by reliance on expensive and limited storage architectures for storing their log files. And, while many log management vendors have developed advanced features powered by machine learning, the simple fact remains that storing logs is much more expensive than it should be.
The result is that many businesses have been forced into the uncomfortable position of determining which of their logs they want to keep or are otherwise forced to transfer their logs to cold data storage solutions. Neither scenario is ideal, because companies need to be constantly analyzing their logs for resource usage, production monitoring, customer behavior, and web traffic patterns.
Fortunately, there is now a log management solution that both reduces the expense and raises the scale of log file storage. That solution is object storage.
What is Object Storage?
When compared to more traditional storage architectures like block or file storage, object storage is very new.
Object storage is less of a tool and more of a strategy in regards to how data is stored. Relying primarily on the idea of storing data in the form of individual units (or ‘objects,’ hence the name), object storage aims to eliminate the tiered file structures that have long plagued traditional file storage systems.
This is accomplished by combining all company data into a single repository with a unique identifier and then distributing that repository across multiple devices, versus diversifying the data into different folders. Additionally, object storage removes the built-in limits that exist in traditional file storage systems, which makes it much easier to store large volumes of unstructured logs and rich data such as audio and video files.
The result is a storage architecture that is highly scalable as well as more efficient for effectively managing distributed media content and data. It’s for these reasons, perhaps, that cloud services from major corporations like Amazon and Microsoft have turned to object storage as their primary storage method.
The Architectural Principles of Object Storage
There are three chief architectural principles to object storage. These are:
1. Ease of Programming
All data stored in an object storage system should be accessed via an API, which means that developers can easily perform programmable actions to query and find objects regardless of where they are located in the storage repository. This makes things much easier for developers, many of whom are relatively inexperienced as studies show that a majority of working developers today have less than five years of working experience.
All object storage solutions should have monitors to determine memory consumption, CPU utilization, and the ability to gauge data usage amongst the different parts of a company.
Major operations in the case of object storage are fully automated, including the processes of indexing, compressing, and encrypting data. Object storage also allows developers and administrators to move data from the cloud to an on-premise storage solution.
Also read: Developing an Edge Computing Storage Strategy
The Benefits of Object Storage Over Traditional Storage Architectures
None of the above, of course, is to say that traditional storage architectures like block storage or file storage no longer have a role to play.
Aggregating data into multiple ‘blocks’ and distributing that data into multiple servers, as is the case with block storage, or managing data as a hierarchy in the case of file storage, are still viable solutions for organizations who want to assign different tiers or access levels to their logs. Block and file storage additionally allow you to lock shared files to prevent data corruption and are largely compatible with standard operating systems and storage applications.
But this is to say that object storage can overcome many of the obstacles that have created limitations in block and file storage solutions. For one thing, object storage simply offers a more cost effective archive for data. Cost is always a major factor in regards to data storage, and object storage is cheaper because it gives the user the ability to begin small and then scale upwards.
That’s also not to mention that object storage solutions are typically much easier to manage than traditional storage architectures. This is thanks to configurable security in the form of erasure coding, customizable metadata, and sequential throughput performance that makes it easier for streaming large media files.
Furthermore, most object storage solutions today are compatible with Amazon’s Simple Storage Service, or S3 API. This is significant because the S3 interface has become the gold standard for object data storage solutions, and subsequently application developers no longer have to deal with proprietary interfaces.
Object storage is no longer merely an archive for storing large volumes of unstructured data. Now, object storage makes more sense as a primary data storage strategy for companies because of the inherent flexibility it affords in regards to data that can be stored, analyzed, and distributed.
Companies that have to store several years or decades worth of critical data, cold data that won’t be accessed for several months at a time, or visual media content stand to benefit the most from switching to object storage from traditional storage solutions.
Read next: Three Key Memory Technologies Driving Data Management