Now is the time to move log management over to object storage
Enterprises and business owners have long had a reliance on expensive and limited storage architectures to store their log files. And while many log management vendors have developed advanced features based on machine learning, the simple fact remains that logs are much more expensive than it should be.
The result is that many organizations are in the inconvenient position of being forced to determine which of their logs to keep or otherwise forced to migrate their logs to cold data storage solutions. Both scenarios are not ideal as organizations need to constantly analyze their logs for resource usage, production monitoring, customer behavior, and web traffic patterns.
Fortunately, there is now a log management solution that both reduces costs and increases the amount of log file storage. That solution is object storage.
What is object storage?
Compared to more traditional storage architectures such as block or file storage, object storage is very new.
Object storage is not so much a tool as it is a data storage strategy. Based 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 achieved by combining all company data in a single repository with a unique identifier and then distributing this repository across multiple devices instead of diversifying the data into different folders. In addition, object storage removes the built-in limitations in traditional file storage systems, making it much easier to store large amounts of unstructured logs and large amounts of data such as audio and video files.
The result is a storage architecture that is highly scalable and more efficient to effectively manage distributed media content and data. For these reasons, large enterprise cloud services like Amazon and Microsoft may have turned to object storage as the primary storage method.
The architectural principles of object storage
There are three main architectural principles for object storage. These are:
1. Simple programming
All data stored in an object storage system should be accessed through an API, which means that developers can easily take programmable actions to query and find objects no matter where they are in the storage repository. This makes things a lot easier for developers, many of whom are relatively inexperienced, as studies show that the majority of working developers today have less than five years of work experience.
All object storage solutions should have monitors to determine memory usage, CPU usage and the ability to measure data usage in different areas of an organization.
Essential object storage operations are fully automated, including the processes of indexing, compressing, and encrypting data. Object storage also enables developers and administrators to move data from the cloud to a local storage solution.
Also read: Develop an edge computing storage strategy
The advantages of object storage over conventional storage architectures
Of course, all of this does not mean that traditional storage architectures such as block storage or file storage no longer play a role.
Aggregating data into multiple “blocks” and distributing that data across 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 with different levels or accesses want to assign levels in their logs. Block and file storage also allows you to lock shared files to prevent data corruption and is broadly compatible with standard operating systems and storage applications.
However, this means that object storage can overcome many of the obstacles that have limited block and file storage solutions. On the one hand, Object Storage simply offers a more cost-effective archive for data. Cost is always an important factor when it comes to data storage, and object storage is cheaper because it allows the user to start small and then scale up.
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 that makes streaming large media files easier.
In addition, most object storage solutions today are compatible with Amazon’s Simple Storage Service or the S3 API. This is important because the S3 interface has become the gold standard for object data storage solutions and as a result, application developers no longer have to deal with proprietary interfaces.
Object storage is no longer just an archive for storing large amounts of unstructured data. Today, object storage makes more sense as the primary data storage strategy for businesses because of the inherent flexibility in the types of data that can be stored, analyzed, and distributed.
Organizations that need to store critical data for years or decades, cold data that cannot be accessed for several months, or visual media content will benefit most from moving to object storage from traditional storage solutions.
Next read: Three important storage technologies for data management