Traditional enterprise storage architecture had very limited autonomy. The autonomy on these systems was limited to providing spare drives, to automatically replace failed drives. Controller failures required manual intervention and high cost maintenance contracts to maintain storage SLO. Data migrations done to improve performance or provide resiliency were typically disruptive operations which meant a hit for application performance or data unavailability scenarios in extreme conditions.
Datera was designed with one single mantra in mind “The only Constant is Change”.
How did we design Datera to be so dynamic and adaptive? The Datera distributed control plane resolves your objectives into a set of policies that are given to a high-performance data plane as key value stores for execution of the policy. The data plane then maps key value pairs onto the current physical hardware to deliver performance, reliability and accessibility.
Software on the individual nodes, built from commodity infrastructure, utilize resources-specific capabilities depending on the type of storage, CPU, memory and networking that optimize for:
- Transformation – protection, compression, encryption, deduplication…
- Placement – NVMe, SSD, HDD, Cloud…
- Functionality – snapshot, replication, copy data management…
Datera continuously monitors how the cluster is performing relative to the specified application intent, i.e. compares admin_state and operation_state. Application requirements in the form of policies are specified by the application admin, and the control plane works to apply them constantly to a completely programmable data plane based on the availability of physical resources. A policy change to improve performance of a subset of data would involve that data migrating to a node supporting media-types to better fit the policy autonomously with absolute transparency.
The autonomous characteristics of Datera Storage systems include but are not restricted to the following underlying behavior:
- Recovery: A Datera system will autonomously recover and adjust data in a way to meet the policy intent during failure and restoration of a variety of physical and software components.
- Policy Changes: Policies can be changed on the fly and the system will autonomously adjust data placement in an entirely transparent and non-disruptive manner to configure the data plane to meet the policy intent.
- Autonomous Redistribution: Datera allows creation of application intent to be created via AppInstance, even if the capabilities are not currently available on the cluster. When resources such as new storage media, memory are added, as part of closed loop autonomous optimization, the data will be redistributed in a non-disruptive manner to meet intent. Datera allows admins to decide the end-goal and the system strives to meet the goal when resources are made available.
- Scaling: Datera automatically incorporates scale-out a storage node to the cluster, and this would involve adding network configuration and upgrading of the software version on the node to meet the cluster versioning while adding the node. Conversely Datera also allows a cluster to scale-in by decommissioning of storage nodes and data from the nodes will be migrated out and cleansed on the retired node.
- Data Placement: Datera provides an outcome based data placement mapping driven by application intent.
- Re-balance: As part of continuous optimization, as additional capacity is added to the cluster in terms of nodes or additional media-types, Datera will move data workloads over to the added capacity in-order to balance the capacity and targets across the cluster.
- Rolling-Upgrades: When a new software version is available, the cluster will autonomously deploy new software, in a non-disruptive, per node, rolling basis, including managing any networking changes to ensure continuous availability.
Datera’s forward thinking and holistic design approach is to envision these capabilities to be operating in concert to create autonomous operations. It strives to make data movement transparent to all host environments across generations of “x86” server & storage media-types, driven autonomously by “current+future” application intent state. Datera is Built For Change, and is helping the largest Global 1000 enterprises future proof and modernize their storage infrastructure.
If you would like to learn more about Datera’s flexibility and future-proofing capabilities, please read our Built For Change White Paper.
Vikram Desai heads up Datera’s Technical Program Management team, and has been with the company for nearly three years. He has been instrumental in supporting our largest OEM’s and other Partners. Prior to Datera he worked across IaaS and Cloud Storage products at Cisco & Akamai.