Dell ECS 'Eleven 9s' Durability: The Claim Without the Calculation

Dell ECS and ObjectScale claim 99.999999999% durability using standard 12+4 Reed-Solomon erasure coding. The math should be straightforward. So why won't they publish the calculation?

Dell ECS (Elastic Cloud Storage) and its software-defined successor ObjectScale claim “99.999999999 (eleven 9s)” data durability [1][2]. This appears in technical FAQs, whitepapers, and product documentation as a key reliability metric. The architecture uses standard Reed-Solomon 12+4 erasure coding - well-understood technology with published mathematical foundations. The component failure rates come from disk manufacturer specifications. The rebuild times can be measured empirically. The durability calculation should be straightforward.

Yet Dell’s published technical documentation doesn’t show the calculation. The Technical FAQ states the eleven 9s claim but provides no methodology [1]. The High Availability Design whitepaper describes erasure coding architecture but omits durability formulas [3]. A third-party product analysis notes: “Performance information has not been published” [4]. The number appears without the math that produces it.

This matters because durability claims mean nothing without verification. When vendors publish MTTDL calculations, customers can check the assumptions, adjust for their specific environment, and make informed decisions. When vendors publish only the final number, customers must trust without verifying. Let’s examine what Dell claims, what can be calculated independently, and why transparency matters for storage reliability assertions.

What Dell Claims

Dell ECS documentation specifies: “ECS durability is 99.999999999 (eleven 9s), while ECS availability is 99.999 (five 9s)” [1]. This separates durability (probability data remains intact) from availability (probability data is accessible). The distinction is important - a system can be unavailable due to maintenance or failures while maintaining full data durability.

Eleven 9s durability translates to an annual data loss probability of 10^-11, or approximately 100 billion years Mean Time To Data Loss (MTTDL). This matches AWS S3 [5], Google Cloud Storage [6], and other major object storage platforms. The number sits in the industry-standard range for object storage with erasure coding.

Dell achieves this through Reed-Solomon 12+4 erasure coding as the default configuration [2][3]. Each object gets broken into 12 data fragments and 4 coding fragments, with the resulting 16 fragments dispersed across nodes in the local site. The system can reconstruct objects from any 12 of the 16 fragments, tolerating 4 simultaneous node failures.

This architecture is solid. Reed-Solomon codes have decades of production validation. The 12+4 configuration provides genuine 4-failure tolerance with 33% storage overhead. Nothing about Dell’s erasure coding approach raises mathematical concerns. The issue is transparency: show us the calculation that produces eleven 9s from 12+4 erasure coding, component failure rates, and rebuild times.

What Standard MTTDL Calculations Produce

Durability calculations follow established methodologies using Markov models or combinatorial probability [7][8]. The basic approach:

  1. Component Failure Rate: Disk manufacturers specify Annual Failure Rate (AFR), typically 0.5-2% for enterprise drives
  2. Erasure Coding Parameters: N data shards, M parity shards, tolerates M simultaneous failures
  3. Rebuild Time: Window during which additional failures could cause data loss
  4. Correlated Failure Probability: Likelihood of multiple failures during rebuild periods

For a 12+4 configuration with 1% disk AFR and 24-hour rebuild time, the eleven 9s claim is plausible. The system tolerates 4 failures, so data loss requires 5 simultaneous failures within a rebuild window. With proper disk distribution across failure domains, this probability can reach 10^-11 annually.

The calculation isn’t complex. Microsoft Azure publishes their methodology for LRC codes [9]. Google explains their eleven 9s calculation with specific assumptions [6]. Backblaze provides a detailed breakdown of how durability numbers emerge from component failures and erasure coding parameters [10]. These vendors show their work.

Dell’s technical documentation describes the 12+4 architecture and states the eleven 9s result but omits the connecting mathematics. The Technical FAQ lists erasure coding configurations and durability claims as separate facts without showing how one produces the other [1]. This gap isn’t a minor documentation omission - it’s the difference between a verifiable engineering assertion and a marketing claim.

The Transparency Problem

Storage reliability claims require transparency because:

Assumptions Matter: Durability calculations depend on component failure rates, rebuild times, and operational procedures. A system achieving eleven 9s with 0.5% AFR drives and 12-hour rebuilds won’t maintain that durability with 2% AFR drives and 48-hour rebuilds. Without published assumptions, customers can’t adjust calculations for their environment.

Verification Enables Trust: When Azure publishes their erasure coding math, storage engineers can verify the calculations independently. When Google explains their eleven 9s methodology, customers can check whether the assumptions match their deployment. Publishing the calculation demonstrates confidence in the claim.

Operational Planning Requires Details: Understanding what failure scenarios the durability calculation covers - and what it doesn’t - helps operations teams plan for reality. Does eleven 9s account for correlated failures? Software bugs? Human error? The calculation methodology reveals these boundaries.

Industry Standards Exist: The mathematics for MTTDL calculations is well-established [7][8]. Reputable vendors publish their methodology using standard formulas. Withholding the calculation while claiming durability numbers suggests either the math doesn’t support the claim or the vendor prefers opacity over scrutiny.

Dell’s approach - stating eleven 9s durability without calculation methodology - falls below industry transparency standards. AWS, Google, Azure, and others publish enough detail that independent verification becomes possible. Dell provides the final number without the supporting mathematics.

What Dell Does Publish

Dell’s technical documentation covers erasure coding architecture comprehensively [2][3]. The High Availability Design whitepaper explains:

This architectural information is useful. It describes how the system responds to failures, how data gets distributed, and what redundancy options exist. Storage engineers can understand the failure tolerance mechanisms without requiring black-box trust.

What’s missing is the connection between architecture and durability numbers. The whitepaper describes a system that can lose 4 nodes without data loss but doesn’t show the calculation that translates “tolerates 4 failures” into “99.999999999% durability.” That calculation exists - it’s standard MTTDL mathematics. Dell chose not to publish it.

One third-party analysis notes: “Performance information has not been published” [4]. This extends beyond durability to general transparency about benchmarks, recovery times, and operational characteristics. The pattern suggests a preference for controlled disclosure rather than open verification.

Independent Verification Attempts

Can customers calculate eleven 9s independently? Partially. With public information, we can estimate:

Known parameters:

Unknown parameters:

Using standard assumptions (1% AFR, 24-hour rebuild, exponential failure distribution), the eleven 9s claim appears achievable with 12+4 erasure coding. But “appears achievable” differs from “verified calculation.” Without Dell’s actual assumptions and methodology, independent verification can only confirm plausibility, not validate precision.

This matters when customers need to answer: does this durability number apply to my specific deployment? If I use different drives, different rack configurations, or different operational procedures, how does durability change? Without the calculation methodology, these questions can’t be answered quantitatively.

Comparison to Transparent Vendors

Google Cloud Storage publishes a detailed blog post explaining their eleven 9s durability [6]. They describe:

This transparency enables informed decision-making. Customers understand what eleven 9s means for their use case and can adjust expectations based on their specific deployment characteristics.

Microsoft Azure publishes academic papers about their erasure coding [9]. The LRC (Local Reconstruction Codes) paper includes:

Azure’s openness about LRC limitations - acknowledging certain 4-failure combinations cause data loss - demonstrates intellectual honesty. They publish impressive durability numbers while explaining boundaries and trade-offs.

AWS S3 claims eleven 9s durability but keeps implementation details proprietary [5]. However, they provide enough operational transparency that engineers can reason about reliability. Service uptime history, regional failure behavior, and recovery characteristics give customers empirical data beyond marketing claims.

Dell’s approach sits below these transparency standards. The eleven 9s claim exists without published methodology, making independent verification impossible and informed deployment decisions harder.

The “Trust Us” Problem

When vendors publish durability claims without calculations, they’re essentially saying “trust us.” This might be acceptable for consumer products where verification isn’t feasible. For enterprise storage systems managing petabytes of critical data, “trust us” doesn’t suffice.

Storage procurement teams need to answer:

Without published methodology, these questions require engaging Dell’s sales engineering team and hoping for internal documentation access. Organizations shouldn’t need special access to verify basic reliability claims. The mathematics is standard. The assumptions should be public. The calculation should be verifiable.

“Trust us” becomes particularly problematic when comparing vendors. If Vendor A publishes detailed durability calculations and Vendor B states only final numbers, how do customers compare meaningfully? Are the assumptions equivalent? Do both calculations cover the same failure scenarios? Without transparency, comparison reduces to comparing marketing claims rather than engineering reality.

What Good Documentation Looks Like

Useful durability documentation should include:

Erasure coding parameters: Specific configuration (12+4, 10+2, etc.) with overhead percentage and failure tolerance.

Component assumptions: Drive failure rates used in calculations, typically from manufacturer specifications or empirical measurements.

Rebuild time estimates: How long recovery takes for different data volumes, affecting the window where additional failures could cause loss.

Formula applied: Reference to MTTDL calculation methodology, whether Markov models, combinatorial probability, or other approaches.

Limitations acknowledged: What failure modes the calculation covers (hardware failures) and what it doesn’t (software bugs, operator error, disasters).

Operational guidance: How customers can adjust calculations for their environment and what operational practices maintain claimed durability.

Ceph’s documentation approaches this standard. Their erasure code documentation explains parameters, references academic papers on the mathematics, and provides tools for operators to calculate durability for specific configurations [11]. The approach treats durability as an engineering property subject to verification rather than a marketing metric to be claimed.

Dell could publish similar information for ECS/ObjectScale. The erasure coding architecture is already documented [2][3]. Adding the MTTDL calculation methodology, component assumptions, and operational guidance would enable independent verification without revealing competitive secrets or proprietary algorithms. The math is standard Reed-Solomon. The formulas are published in academic literature. Only the specific assumptions and application require documentation.

Why This Matters Operationally

Durability claims affect how organizations plan for data protection. A system with verifiable eleven 9s durability using 12+4 erasure coding might not need additional replication or backup for certain workloads. A system claiming eleven 9s without showing the calculation introduces uncertainty that affects risk management decisions.

Consider an organization deploying 10PB of data on Dell ECS. The eleven 9s durability suggests annual data loss probability of 10^-11, or one byte lost per 100 billion bytes per year. Should they implement additional backup? Mirror to a second site? Accept the durability as sufficient?

With published calculation methodology, the organization could verify:

Without methodology, the organization must either accept the eleven 9s claim on faith or implement conservative additional protection that might be unnecessary. Neither outcome serves operational efficiency.

What Dell Gets Right

Dell ECS/ObjectScale’s erasure coding architecture is sound. The 12+4 Reed-Solomon configuration provides genuine 4-failure tolerance. The system’s ability to reconstruct from any 12 of 16 fragments is well-established mathematics. Nothing about the technical approach raises concerns.

The documentation of erasure coding architecture, failure handling, and recovery procedures helps operations teams understand system behavior [2][3]. Knowing how the system responds to node failures, how data reconstruction works, and what redundancy options exist enables effective operational planning.

Dell’s support for both local and multi-site protection gives deployment flexibility. Organizations can choose appropriate redundancy levels based on their specific durability requirements and risk tolerance.

These technical strengths exist independently of documentation transparency. The erasure coding works whether or not Dell publishes MTTDL calculations. But transparency would enhance trust, enable verification, and help customers make informed decisions about whether Dell’s architecture matches their requirements.

What Needs to Change

Dell should publish durability calculation methodology for ECS/ObjectScale including:

This information doesn’t reveal competitive secrets. The erasure coding scheme is already documented. The MTTDL formulas are published in academic papers. Only the specific application to Dell’s architecture requires disclosure.

Publishing methodology would align Dell with industry leaders like Google, Azure, and others who enable independent verification of durability claims. It would demonstrate confidence in the engineering and respect for customers who need to make informed procurement decisions.

The Core Issue

Dell ECS and ObjectScale use legitimate Reed-Solomon erasure coding. The eleven 9s durability claim falls within the plausible range for 12+4 configurations with reasonable component failure assumptions. Nothing suggests the number is fabricated or impossible.

But “plausible” differs from “verified.” Storage procurement teams shouldn’t need to accept durability claims on faith when the mathematics exists to verify them. Dell has the calculation - they had to perform it to arrive at eleven 9s. Publishing that calculation enables customer verification and informed decision-making.

Storage vendors compete on specifications, and durability numbers factor into RFPs and purchasing decisions. But meaningful comparison requires transparency. When some vendors publish detailed methodologies while others state only final numbers, customers can’t evaluate reliability claims on equal footing.

The storage industry should embrace transparency around durability calculations. The mathematics is standard. The assumptions are measurable. The formulas are published. Only vendor choice prevents verification.

Dell ECS and ObjectScale deserve evaluation on their technical merits: solid erasure coding architecture, flexible deployment options, and enterprise-grade features. These capabilities should be verifiable through published documentation, not accepted on faith because the vendor prefers opacity.

Because when a vendor claims eleven 9s durability using standard erasure coding but won’t publish the calculation, customers should ask: why not?

References

[1] Dell Technologies, “Dell ECS Technical FAQ,” https://infohub.delltechnologies.com/en-us/l/dell-ecs-technical-faq/general-faq-3/

[2] Dell Technologies, “Dell ObjectScale Technical FAQ,” https://infohub.delltechnologies.com/en-us/l/dell-objectscale-technical-faq/general-faq-3/

[3] Dell Technologies, “Dell EMC ECS: High Availability Design,” White Paper H16344.6, https://www.delltechnologies.com/asset/en-ie/products/storage/industry-market/h16344-ecs-high-availability-design.pdf

[4] Futurum Group, “Dell ECS / ObjectScale - Product Analysis,” https://futurumgroup.com/wp-content/uploads/documents/EGL2_Dell_EMC_ECS-8.pdf

[5] AWS, “Amazon S3 Durability,” https://aws.amazon.com/s3/faqs/

[6] Google Cloud, “Understanding Cloud Storage 11 9s durability target,” https://cloud.google.com/blog/products/storage-data-transfer/understanding-cloud-storage-11-9s-durability-target

[7] Greenan, K., & Plank, J. S. (2010). “Mean time to meaningless: MTTDL, Markov models, and storage system reliability.” HotStorage. https://www.usenix.org/legacy/event/hotstorage10/tech/full_papers/Greenan.pdf

[8] Balaji, S.B., et al. (2018). “Erasure Coding for Distributed Storage: An Overview,” arXiv:1806.04437.

[9] Huang, C., et al. (2012). “Erasure Coding in Windows Azure Storage,” USENIX ATC. https://www.usenix.org/system/files/conference/atc12/atc12-final181_0.pdf

[10] Backblaze, “Cloud Storage Durability: What Do All Those 9s Mean?” https://www.backblaze.com/blog/cloud-storage-durability/

[11] Ceph, “Erasure Code Documentation,” https://docs.ceph.com/en/latest/rados/operations/erasure-code/

StorageMath analyzes all vendors with equal scrutiny. Dell’s erasure coding architecture is solid. Their documentation transparency needs improvement. Customers deserve verifiable reliability claims, not numbers without methodology.