Effectively managing high-performance workloads demands an equally high-performance infrastructure. Unfortunately, the typical data management point solutions frequently employed to connect disparate silos cannot scale to the levels required by high-performance computing (HPC).
Instead of effectively bridging these gaps, these solutions become obstacles that unnecessarily complicate user workflows. These bottlenecks strain IT resources and budgets across various domains, including HPC parallel file systems, enterprise NAS, and global namespaces. These technologies operated independently in the past, siloing the data and making it challenging to merge, retrieve, and transfer.
Typically, an IT architecture that supported fast processing and diverse data sets from disparate storage silos required a trade-off; you could only have one or the other. Today, unstructured data orchestration brings together different data sets and data technologies from multiple vendor storage silos and geographic locations without compromising performance or secure global data utilization.
Seamless Integration
Unstructured data orchestration is the critical technology solution necessary for seamlessly integrating datasets and data technologies from various vendor storage silos and geographic locations. This integration enables uninterrupted and secure global data utilization while maintaining top performance.
The recent demand for data analytic applications and AI capabilities has significantly increased data utilization across multiple locations and organizations. Data orchestration automates the process of aggregating siloed data from numerous data storage systems and locations into a single namespace and high-performance file system. This process allows for effective data placement at the edge, in the data center, or on a cloud service best suited for the workload.
The traditional 1:1 link between data and its source applications or compute environment of its origin has evolved. Data must now be utilized, analyzed, and repurposed to support various AI models and disparate workloads in a collaborative remote setting.
Data orchestration technology facilitates data accessibility to various foundational models, remote applications, decentralized compute clusters, and remote workers. This automation improves the efficiency of data-driven development initiatives, insights gained from data analysis, and business decision-making processes for businesses.
Fine-Tuned Data Services
It is crucial to enable IT teams to fully utilize the performance capabilities of any server, storage system, and network worldwide. This approach allows organizations to store, safeguard, and operate data seamlessly, automatically relocating it according to policy or demand, enabling easy access to compute resources, utilizing cost-effective infrastructure, and making files accessible locally for distributed teams. Such an approach creates a unified, swift, and effective global data environment for every workflow step – from initial creation to processing, collaboration, and archiving across edge devices, data centers, and private and public clouds.
It is now possible to control enterprise data services globally at a file-granular level across all storage types and locations for governance, security, data protection, and compliance. In addition to accessing data stored in remote locations, applications, and AI models can also use automated orchestration tools to provide high-performance local access for processing when necessary. Organizations can also expand their talent pools by having access to team members anywhere in the world.
The Benefits of Data Orchestration
Data orchestration makes data available to decentralized computer clusters, applications, and remote workers to automate and streamline data-driven development initiatives, data insights, and business decision-making. It offers many benefits, including:
- Data access to applications and users is not interrupted when moving data across hybrid, decentralized, or multi-vendor storage environments.
- Non-disruptive data movement never requires updating applications or user data connections.
- Data placement is automated using objective-based policies that place data where it’s needed, when it’s needed.
By managing data effectively, it becomes more widely accessible and usable to individuals, systems, and organizations, enabling the utilization of more processing and brain power and ultimately accelerating the value derived from the data. Additionally, each instance of utilizing data accelerates its impact and generates additional valuable data.
Data analysis leads to insights that inform future data collection and analysis, creating an ongoing cycle of new data generation. By orchestrating the flow of data and ensuring proper capture and preservation of new data, organizations can magnify this feedback loop and derive further significant insights from their existing data. This process leads to potential new revenue streams and improves operational efficiencies for organizations.
Now is the time for enterprises to stop struggling with siloed, distributed, and inefficient data environments. With automated data orchestration, enterprises can achieve far more.
Molly Presley is Senior Vice President of Marketing at Hammerspace. She brings over 15 years of product and growth marketing leadership experience to the Hammerspace team.
