Anytime a technology improvement has been readily available for consumption, a paradigm shift has followed. This holds true for all technology milestones: everything from easily accessible personal computers and spreadsheets to cloud computing models and application development practices.
Yesterday, we had dedicated application development/quality assurance teams for coding, and dedicated operational teams for deploying monolithic applications via manual IT frameworks.
Today, we have microservice based containerized applications being updated and deployed via continuous integration and continuous deployment (CI/CD) workflows, orchestrated by Dev/Ops teams.
The objective for these teams is the same as it has always been: provide better time to value for their users/customers.
Some of the mechanics on how to provide better time to value are simple: automate manual infrastructure tasks, standardize management and access protocols and enhance the usability of application data.
From an object storage perspective providing better time to value means: cutting storage provisioning times, standardizing on a single REST based API for communication (ie AWS S3) and extending data objects with custom metadata.
Reducing provisioning times has always been a challenge in traditional SAN/NAS environment. Day 1 operations may have been scripted but typically storage changes were handled by specialized operators. Day 2 operations and forward almost always needed manual intervention. Try as traditional storage vendors might, adopting a RESTful API to administer storage platforms has been a long process, often ending in only a subset of RESTful API calls being available. Features like Cloudian’s Admin API set, which allows programmatic control of the platform, rarely reached maturity.
From an application development perspective, AWS S3 has become the de facto standard storage communication API for cloud native applications. Multiple applications and environments can easily access the same or multiple buckets via S3 API and object storage provides an entire suite of fine grain access permission controls that simply don’t exist in SAN/NAS. For the application, there is no difference between accessing objects in AWS’ S3 service or a Cloudian implementation on premises, the calls, functions and return codes are the same.
When it comes to enhancing data, as an object storage platform, Cloudian excels in this category. By leveraging custom metadata and annotations it is now possible to separate data and data context from the systems that generated the data…
It’s easier to illustrate with an example….
A traditional commerce application would have at least 3 components, a client front end interface, a database for storing transactional history (date, time and amount) and dedicated storage for the transacted data (itemized order receipt, invoice, shipment notify). Without the transaction database, each individual piece of data is meaningless, ie the receipt lacks context. If Cloudian was leveraged as a data store in this example, each object (receipt) could have the transactional information captured as metadata. The requirement for the transaction database is removed, objects can be moved from system to system and still provide full context of what occurred.
To bring the pieces together, DevOps teams are leveraging S3 storage in the following ways:
Operational functionality has been automated by leveraging RESTful Admin API sets. Meaning deployment, Day N changes are reflected as a piece of code, that requires no manual human changes to the environment.
Numerous modern and legacy applications already leverage AWS S3 to store persistent data, breaking the hold for SAN/NAS as the only storage options. Workflows can immediately integrate Cloudian for storage without the need to recode or refactor applications.
Developers can leverage a metadata rich platform to build applications that reduce the dependency on separate data stores to provide context for data. Data can now be moved easily between systems; an order receipt can be fed into an AI platform to help predict a customer’s future purchasing patterns.
Persistent data storage can be provided by Cloudian in containerized environments, such as VMware Tanzu and RedHat OpenShift.
This means cloud native applications running in hybrid environments continue access Cloudian for storage, regardless of where the application is running.
By leveraging S3 for storage, DevOps teams can leverage Cloudian for everything from simple Backup & Disaster Recovery requirements to providing storage for Dev/Prod environments.
As with all technology milestones, greater adoption generates further use cases, check out https://cloudian.com/products/hyperstore/ for more examples!
