John Holtz, Director of Federal Sales, Panasas, uncovers the top three HPC systems storage challenges for government agencies and how to overcome them
Government organizations are at the cutting edge of high-performance computing (HPC). From complex modeling and simulation to machine learning and deep learning, government agencies and national labs rely on mountains of HPC systems and data – stored across various locations, formats, and systems – to drive advanced research and secure national interests.
When decision-making speed is paramount, government agencies cannot afford to overlook
their data storage and management infrastructures. All solutions implemented must support their ultimate objectives while ensuring they can also win the battle against soaring security threats and adhere to stringent data privacy regulations.
This article explores three significant challenges government agencies face regarding their storage infrastructure and the factors IT decision-makers must consider when evaluating their IT environments.
1) Accelerating workloads while keeping costs down
Government researchers depend on their HPC systems to support bandwidth-intensive applications such as computational fluid dynamics (CFD) simulations of aircraft designs, AI-enabled molecular modeling, climate change analysis, and defense mission simulations. These applications demand scalable, low-latency, and high-throughput performance from their underlying storage, capabilities that typical enterprise solutions like scale-out NAS simply cannot sustain.
Optimal performance, however, often comes at a price, which can strain already stretched IT budgets. To boost productivity and reduce costs, consider deploying a parallel file system that excels in three key areas: reliability, manageability, and workload flexibility.
A parallel file system is designed to enable rapid access to enormous datasets through simultaneous and coordinated input/output operations (IOPS) between clients and storage nodes. This makes it an ideal solution for large-scale data-intensive workloads since it leverages distributed storage and data striping techniques to achieve high throughput. When selecting a parallel file system, ask yourself the following:
- Reliability:
- Does the solution guarantee the reliability needed to ensure optimal data integrity and availability? Consider features such as per-file object erasure coding, the ability to use different RAID schemes for additional files within the same volume, and continuous data integrity checks.
- Manageability:
- Can time-consuming tasks such as overseeing, tuning, and maintaining storage infrastructure be automated? Look for a solution that a single IT admin can manage during a small part of their day. This will free up the budget and allow IT teams to focus on other strategic projects that support the business objective.
- Workload flexibility
- Does the solution support varying workload types and sizes? Many parallel file systems are narrowly tuned to reach peak performance for only one specific workload type.
As the business grows and emerging applications place different demands on the storage system, it is critical to ensure that your HPC systems and infrastructure can easily adapt to diverse applications and multiple concurrent workloads.
2) Protecting sensitive data
Government organizations face growing pressure and urgency to secure their large datasets to meet data privacy and regulatory requirements for each region.
According to the 2021 Thales Data Threat Report, nearly half of U.S. federal government respondents noted they had experienced a security breach at some point.
Of these, 47% said they had experienced a breach in the last 12 months. There’s no question that data loss, storage failures, and security breaches (fueled by unintentional internal errors and intentional external vectors) continue to threaten mission-critical deadlines and – most importantly – national interests. Outdated legacy storage and multi-vendor infrastructure sprawl reduce data interoperability and increase an organization’s vulnerability to these threats.
To keep government data safe and available, follow these three essential steps:
- Take a defense-in-depth approach to data security. ACLs, SELinux support, and hardware-based encryption at rest prevent unauthorized access while the realm is both online and offline with no performance degradation.
- Select a solution with automatic error recovery, continuous data scrubbing, and parallel rebuild. Per-file object erasure coding will ensure maximum protection, while built-in prevention and automated rapid failure recovery logic help avoid corruption issues and maximizes system uptime.
- Consolidate legacy systems onto a modern storage platform with a superior reliability architecture.
3) Driving smarter decisions from data
Knowing where and how to use your data best is just as important as protecting it. Monitoring skyrocketing data stores across multiple locations is challenging for government IT staff, and manual methods quickly become unsustainable. Government agencies should prioritize intelligent data insight and mobility capabilities when evaluating their IT infrastructures. These will improve data management and decision-making practices throughout the entire organization.
Look for comprehensive data insight and mobility solutions that deliver:
- Parallel multi-threaded operations for pooled data movement.
- Fast, secure, and reliable data movement between on-premises systems and the cloud, including extensions for backup and archive to S3 object stores.
- Powerful scan capabilities to enable agency-wide data discovery.
These features will allow government agencies to search and analyze their data files to mobilize them when and where needed.
Empowering mission-critical workloads
Government agencies may have vastly different purposes – from defense simulations to particle physics – but all face similar data storage challenges: exploding data volumes and data types, stretched budgets, and heightened security concerns.
At the same time, they must provide rapid and reliable access to large files and datasets to power mission-critical workloads. The choice of storage infrastructure can dramatically affect their productivity and bottom line.
