Solid State Storage: NextGen Enterprise Storage

The section begins by outlining the long-held aspiration in computer architecture for storage devices offering high IOPS at low cost (IOPS/$/GB), alongside instant access (low latency). Enterprise-ready SSDs, available in SATA and PCIe-based hybrid storage products, are presented as technologies fulfilling this vision. However, the true breakthrough is attributed to the recent advancements in controllers and firmware. These advancements enable seamless mitigation of earlier challenges concerning reliability, endurance, data retention, performance, manageability, and integration with existing storage interfaces. The introduction of automated storage tiering tools, which dynamically migrate 'hot' data to SSDs based on I/O access patterns, is highlighted as a critical factor in the widespread adoption of SSDs within enterprise environments. This approach has yielded remarkable results, showcasing improvements exceeding 475% in IOPS and 80% in response time during peak loads. The overall aim is to present a comprehensive overview of the technology, encompassing performance, cost, reliability, endurance, and relevant applications, backed by real market data.

This section clearly outlines the learning objectives, aiming to provide a comprehensive understanding of SSD technology, its characteristics, and its optimal applications within enterprise storage systems. The goal is to equip attendees with the knowledge needed to effectively plan, implement, and realize the benefits of using SSDs as tiered storage in specific scenarios. The focus is on applications like OLTP/databases, business intelligence, and cluster-based HPC workloads. The presentation emphasizes practical aspects by including real-life case studies involving SANs (Storage Area Networks), showcasing successful implementations and tangible results. Key areas addressed include improving transaction query response times and IOPS, workload characterization, identifying applications best suited for SSDs, and the significance of new intelligent controllers in modern SSD storage systems. The discussion also touches upon data forensics and tiered mapping techniques.

The economic benefits of adopting SSDs are emphasized, contrasting them with the limitations of HDDs. A key argument is that achieving specific performance improvements (e.g., query response times) is far more cost-effective with SSDs than by solely increasing buffer memory with HDDs. The presentation utilizes data comparing HDD and SSD capacity within a standard 2U rack, demonstrating the higher density and subsequent cost-effectiveness of SSD deployments. The text explicitly highlights the advantage of using SSDs (or hybrid SSD/HDD configurations) for database and OLTP applications, contrasting this with the drawbacks of over-relying on HDDs or employing short-stroking techniques. The price erosion of SSDs and the corresponding increase in IOPS/GB are emphasized, illustrating the rapidly improving economics of SSD technology.

This section directly confronts the challenges historically associated with SSDs and presents solutions currently implemented. Best practices and goals for minimizing functional failure rates are discussed, emphasizing the importance of error avoidance algorithms and verification testing. The architecture of intelligent SSD controllers is detailed, covering aspects such as interface controllers, flash controllers, DRAM cache buffers, and RAID configurations. Advanced features of these controllers, such as adaptive digital signal processing, enhanced error correction codes (ECCs), and wear-leveling algorithms, are explained in detail. The discussion highlights how these technologies contribute to extended SSD lifecycles and enhanced reliability. Over-provisioning of capacity and its role in enhancing performance and reliability are also covered.

This section dives into the core technology of SSDs, starting with NAND flash memory. It details the crucial role of intelligent controllers in managing this memory, highlighting features like error correction codes (ECC), wear-leveling algorithms, and over-provisioning of capacity. These techniques are presented as key to overcoming the historical limitations of NAND flash in terms of endurance and reliability. The architecture of an SSD is dissected, outlining the functions of interface controllers (managing communication with the host system), flash controllers (managing the NAND flash arrays), and the use of DRAM cache buffers to boost performance. Different SSD types, such as SATA and PCIe-based drives, are mentioned, along with the impact of their respective interfaces on overall system performance. The discussion also touches upon the concept of Storage Class Memory (SCM) and its position in the market, bridging the performance gap between DRAM and HDDs.

The section acknowledges previous limitations of SSD technology, particularly regarding endurance and reliability. It then presents strategies and best practices for addressing these challenges. Specific methods, such as utilizing error avoidance algorithms and rigorous verification testing, are highlighted as crucial for keeping the total functional failure rate below acceptable thresholds. The importance of robust ECC (Error Correction Code) techniques, internal RAID configurations, wear leveling to reduce hotspots, and the use of spare capacity to manage wear-out are emphasized. Techniques to address write amplification and improve garbage collection efficiency are also mentioned. These strategies are presented as key to ensuring the long-term reliability and endurance (5-year life cycle) needed for mission-critical applications in enterprise settings. A mention of SandForce as a source for this information is also included.

The section examines different workload characteristics and their impact on SSD performance. It discusses various aspects of workloads, including random versus sequential access patterns, read/write ratios, queue depths, and threading. The importance of pre-conditioning SSDs with appropriate test workloads is also highlighted. The concept of 'burst' performance (initial, high-speed performance) versus steady-state performance (after extended use) is explained. The section describes how advancements in controller technology have brought the performance of Multi-Level Cell (MLC) SSDs closer to that of Single-Level Cell (SLC) SSDs. Finally, the discussion underscores the influence of various factors including operating systems (OS), applications, drivers, caching strategies, and SSD-specific commands (TRIM, Purge) on overall SSD performance.

This section focuses on the application of SSDs within database systems. It highlights the key components of databases, such as commit files, logs, redo/undo operations, and temporary databases (tempDB). The suitability of SSDs for structured (SQL) versus unstructured data is discussed; structured data access is generally considered a good fit, except for very large, expanding tablespaces. Conversely, unstructured data access is less ideal, except for small, static, tagged files. Typical read/write ratios in databases (80/20 or 50/50) are noted. The challenges of creating representative test environments with sufficient I/O characteristics are mentioned. Different database workloads are analyzed: batch workloads (write-intensive), data warehousing workloads (predominantly read-based with low buffer pool hit ratios), and OLTP workloads (strongly random I/O intensive). The critical importance of backup and recovery times, necessitating high sequential I/O for backups and high random I/O for recovery, is emphasized. The section also mentions using historical performance data to identify performance bottlenecks and hot data regions within databases.

Building upon the previous section, this part details best practices for optimizing database, data warehousing, and business intelligence (BI) applications using SSDs. It stresses the need to define clear goals for service level agreements (SLAs) concerning performance, cost, and availability, as well as business continuity/disaster recovery (BC/DR) plans and compliance requirements. Specific strategies for enhancing performance are suggested: removing stale data, classifying data using partitioning software based on access frequency, improving query performance by minimizing I/O operations, and reducing the number of disks needed through data compression. The importance of aligning data classification with tiered storage devices is underscored. The section further advises on establishing goals for SLAs (performance/cost/availability), BC/DR (RPO/RTO - Recovery Point Objective/Recovery Time Objective), and compliance, aiming to improve the performance of databases, data warehousing, and OLTP applications. Using advanced compression software to reduce disk requirements is also highlighted.

This section introduces automated storage tiering as a key technique for optimizing performance. It explains that every workload has a unique I/O access signature and historical performance data can reveal performance bottlenecks and hot data regions. The core principle is the non-disruptive migration of 'hot' data (the approximately 5-10% of data most frequently accessed) from HDDs to SSDs. This automated reallocation leads to significant performance improvements, with examples showing response time reductions of around 70% and IOPS increases of 200% for I/O-intensive workloads. The technique of I/O forensics, using LBA (Logical Block Address) monitoring and tiered placement, is detailed as the mechanism driving this automated data migration. The focus is on achieving significant performance gains, especially in time-sensitive OLTP environments. The use of PCIe SSDs over SATA SSDs and the benefits of Nehalem class CPUs for PCIe SSD configurations are also mentioned.

This section provides a concise summary of best practices for implementing storage tiering with SSDs and HDDs. Key points include using PCIe SSDs over SATA SSDs where possible, employing Nehalem class CPUs, placing frequently accessed files (indexes, tables, tablespaces) on SSDs, and reserving sufficient space on SSDs to prevent write deterioration. Sequentially written files are recommended for placement on HDDs to leverage their strengths. The importance of using auto-tiering software, employing heat mapping and workload analysis, and performing smart data migration are highlighted. Faster networks (10GbE over 1GbE) are suggested to prevent network bottlenecks. The section concludes by summarizing the potential price/performance benefits, which can reach 150-800%, and advocating for archiving less-active tables and records to HDDs to extend SSD lifespan and improve overall efficiency. Finally, the document underscores the significant paradigm shift in storage technology brought about by SSDs.

The concluding section emphasizes the significant paradigm shift occurring within the storage industry due to the widespread adoption of solid-state storage (SSS). It reiterates the substantial opportunities for optimizing computing infrastructures through the strategic integration of SSDs. However, it stresses the importance of conducting thorough due diligence before making any decisions, including careful vendor and product selection, rigorous industry testing, and a comprehensive understanding of the technology's implications. The section effectively summarizes the presentation's core message, highlighting the transformative potential of SSDs and the need for informed decision-making in leveraging this technology. The overall tone is one of encouragement for SSD adoption but with the crucial caveat of careful planning and research.

The final part of the document acknowledges the contributions of several individuals who played a vital role in shaping the presentation's content and direction. It specifically mentions Joseph White and expresses gratitude for their industry vision and leadership, particularly in identifying critical I/O bottlenecks within various storage systems. The acknowledgement extends to Jim Gray (posthumously) and Anil Vasudeva, underscoring their expertise and insights into the field of storage technology and their contributions to the understanding of performance limitations and potential solutions. This section serves to highlight the collaborative nature of the work and to recognize the individuals responsible for contributing to the advancement of knowledge within the storage industry.