The Secret Behind PowerStore’s Best-in-Class Simplicity and Performance

Summary

In this session, Drew Shuli and Jody Hogland discuss the significance of architecture in storage solutions, focusing on the advantages of Dell Technologies’ PowerStore with its autonomous active-active architecture. They emphasize the ease of use, scalability, and efficiency of PowerStore, highlighting features like dynamic node affinity and global data reduction. The conversation contrasts PowerStore’s design with other market options, noting the manual complexity of quasi-active architectures and the limitations of active-passive models. Overall, they stress how PowerStore’s architecture drives simplicity, cost-effectiveness, and long-term performance.

Takeaways

• 😀 Active-active architecture in PowerStore drives simplicity and ease of use for customers, addressing the challenge of having to do more with fewer resources.
• 😀 The autonomous active-active design eliminates the need for manual volume pinning, ensuring optimized multi-pathing and eliminating complex tasks like LUN trespassing.
• 😀 PowerStore's Dynamic Node Affinity (DNA) automatically adjusts paths on the backend to ensure optimal performance, scalability, and low latency without user intervention.
• 😀 Dynamic Node Affinity (DNA) operates entirely via software, ensuring better performance and guarantees such as increased IOPS and throughput with zero intervention required.
• 😀 Software enhancements made in Dell Technologies World boosted data reduction by up to 20% and performance by up to 30%, improving the overall effectiveness of the platform.
• 😀 PowerStore's dynamic resiliency engine (DRE) enables scalability in single drive increments, providing flexible, cost-efficient growth options without disrupting operations.
• 😀 Customers can scale storage in PowerStore by adding individual drives, mixing and matching different drive types as needed, with no problem when growing the system.
• 😀 Quasi-active-active architectures offer active-active connections but require manual decisions on node and volume allocation, making the process less efficient compared to fully autonomous designs.
• 😀 In quasi-active-active setups, performance issues over time require manual decisions to migrate volumes, which introduces complexity and increases operational overhead.
• 😀 Active-passive architectures, while simple and advertised as active-active, suffer from inefficiencies due to rigid scalability, requiring users to select specific drive packs for expansion, which may increase costs and limit flexibility.

Q & A

What is the main advantage of PowerStore's autonomous active-active architecture?

PowerStore’s autonomous active-active architecture simplifies storage management by ensuring that performance is always optimized with minimal manual intervention. This design allows for continuous, active connections, reducing the need for administrators to manually adjust configurations or handle failovers.

How does PowerStore's Dynamic Node Affinity (DNA) contribute to performance optimization?

Dynamic Node Affinity (DNA) automatically manages the path distribution between storage nodes based on workload changes. Over time, as applications grow at different rates, DNA ensures optimal performance by adjusting paths to guarantee lower latency, more IOPS, and higher throughput, all without requiring administrator intervention.

What are the key differences between active-active, quasi-active, and active-passive architectures?

Active-active architecture, used by PowerStore, provides continuous active connections for both data paths and drives, ensuring optimal performance. Quasi-active architecture requires manual decisions for volume placement and path allocation, introducing complexity and inefficiency. Active-passive architecture, while advertised as active-active, is actually active on the front end but passive on the back end, offering limited scalability and efficiency.

What is the benefit of PowerStore's global data reduction feature?

Global data reduction is a feature that allows PowerStore to reduce the storage footprint across the entire array or appliance level. This improves storage efficiency and helps reduce costs by ensuring that data is optimized across all workloads and not just isolated to specific volumes.

How does the Dynamic Resiliency Engine (DRE) improve PowerStore's scalability?

The Dynamic Resiliency Engine (DRE) enables PowerStore to scale incrementally, adding one drive at a time to meet growing capacity demands. This flexible approach allows customers to grow their storage as needed without requiring large upfront investments, supporting a 'pay-as-you-grow' model.

What role does software play in PowerStore’s performance enhancements?

Software-driven architecture in PowerStore enables continuous performance optimization and efficiency improvements. For instance, software updates have led to up to 30% better performance and up to 20% better overall data reduction, ensuring that customers get the best possible performance over time with minimal manual intervention.

Why is it important that PowerStore allows for single-drive incremental growth?

Allowing for single-drive incremental growth ensures that customers can scale their storage environment gradually, adding drives as needed without being locked into rigid capacity plans. This approach reduces waste and allows for more cost-effective scaling, especially in environments with unpredictable growth patterns.

How does PowerStore handle the issue of workload growth and increasing performance demands?

PowerStore’s autonomous architecture automatically manages workload growth and performance demands through features like Dynamic Node Affinity (DNA). This allows the system to adjust paths and resources in real-time to ensure optimal performance, even as workloads change over time, without requiring manual intervention.

What are some potential challenges with quasi-active architecture compared to PowerStore’s active-active design?

Quasi-active architecture requires manual decisions for volume placement and path allocation, which increases complexity and can lead to inefficiencies as workloads grow. In contrast, PowerStore’s active-active design is fully autonomous, ensuring optimal performance without requiring manual configuration or handling of failovers.

What is the impact of model restrictions in active-passive designs, and how does PowerStore address this?

In active-passive designs, scalability is often restricted by the specific model being used, which may not support the same capacity as other models. PowerStore, on the other hand, offers a flexible architecture where all models, from entry-level to high-performance systems, support the same drives and capacities, allowing for seamless growth with minimal restrictions.