What is a single point of failure in a cloud storage system?

What is a Single Point of Failure (SPOF)? By definition, a single point of failure refers to a potential risk caused by design, implementation, or configuration flaws in a circuit or system. In other words, a SPOF is a type of failure that could cause the entire system to stop functioning.

What is a Single Point of Failure in Data Storage Systems?

A single point of failure in data storage systems can be understood as a failure of an element, component, or part of the system that leads to the entire system becoming inoperative. There are typically several scenarios:

• Suppose a storage device has only one power supply; this is a single point of failure. If the power supply fails, the entire device will shut down, and data will become inaccessible.
• Similarly, if there is only one storage head unit/storage controller, its failure will compromise the entire data storage system.
• If the data storage system lacks RAID or erasure coding, a single point of failure may also occur.
• If a drive fails, data on that specific drive will become inaccessible, which will also cause an interruption.

Why Do Single Points of Failure Exist in Cloud Storage Systems?

It seems that single points of failure in data storage systems typically occur in their hardware devices. However, for cloud storage/distributed storage, do single points of failure still exist? How severe are the impacts?

Centralized cloud storage providers are often exposed to single data center failure risks. This is because cloud storage services, like cloud hosting services, are concentrated in individual or specific data centers, and when using cloud storage services, one must choose to use one of these data centers. If the data center where the data resides experiences a power or network failure, it will affect normal service.

So how can we address the frequent single point of failure issues of centralized cloud service providers? The solution to single points of failure is "redundancy." Key servers should be clustered for redundancy, network connections should be redundant with multiple channels, storage should be mirrored or use RAID redundancy, and the entire data center should achieve redundancy through disaster recovery and active-active configurations.

It is undeniable that leading centralized cloud service providers dominate the cloud storage market, and thus there are also technical "firewalls" and commercial barriers between them, making it difficult for users to replicate data across "clouds." Each data center operates independently and does not allow data to be snapshotted or copied between different clouds. Therefore, under the commercial model of centralized cloud storage, if the "cloud" a user relies on fails, another "cloud" cannot promptly take over and handle the situation. The risks posed by single points of failure are still managed and controlled centrally, leaving users to rely solely on the cloud they choose to avoid failure, without any other more reliable solutions.

How Decentralized Cloud Storage Solves Single Points of Failure

Decentralized cloud storage, due to its inherently distributed architecture, largely avoids the single point of failure issues of centralized systems. In current distributed storage systems, such as Filecoin, Arweave, and Storj, users with idle storage resources can become part of the storage network by renting out storage space for incentives. Each project has its unique features, but in addressing single point of failure issues, they have not demonstrated much more innovative technology beyond the natural advantages of distribution. For example, in a peer-to-peer storage order service, preventing single points of failure requires the network to actively transact with multiple storage providers to achieve multiple copies.

CESS, as a secure, efficient, open-source, and scalable decentralized cloud storage network, naturally avoids single point of failure issues due to its distributed structure, and both its network and storage are decentralized. Compared to other decentralized storage projects, CESS stands out by introducing a new storage proof mechanism --- Multi-Replica Recoverable Storage Proof Mechanism (PoDR²). We will analyze the advantages of this storage proof in addressing single points of failure and disaster recovery capabilities from two aspects:

- Multi-Replica

PoDR² is a zero-trust data backup and recovery proof algorithm. Stored data is encrypted, sliced, and randomly sent to several miner nodes. Under the PoDR² mechanism, three replicas are generated by default. Of course, the system also supports users customizing the number of replicas produced. Using a homomorphic signature mechanism, it ensures that storage miners accurately store the number of data replicas specified by the CESS system or the user. Traditional centralized cloud storage also supports multiple backups, but the number of backups is ultimately still centralized and controlled, which does not significantly enhance security through multiple replicas.

- Recoverable

As mentioned earlier, "redundancy" is a method to solve single points of failure, which fundamentally involves replication and recovery. Through CESS's PoDR² mechanism, after processing data into multiple replicas, redundancy coding is utilized to ensure that even if any two blocks of data are damaged, they can be recovered through redundancy coding. Subsequently, the CESS system will generate auxiliary verification parameters for later data storage proof for each data segment, used for subsequent replication proof, temporal-spatial proof, and PoDR² storage proof. In this mechanism, the CESS chain will randomly distribute the data segments of replicas to different storage miners, so even if a particular storage miner encounters data deletion, loss, or hacker attacks, PoDR² can retrieve data from other storage miners to provide retrieval and recovery, maximizing the protection of user data storage security.

It is worth mentioning that under the PoDR² mechanism, the CESS system will periodically check the data on storage miners (i.e., check and prove whether the data stored by the storage nodes is valid, exists, or has been modified), ensuring the authenticity and availability of the data.

Stepping beyond the issue of single points of failure, it reflects how various systems can anticipate risks in advance and implement mechanisms to avoid them, providing data disaster recovery solutions. From the perspective of data availability, CESS's multi-replica recoverable storage proof mechanism maximally ensures data availability. From a security standpoint, CESS slices, redundantly stores, and then distributes data to storage miners, achieving global data redundancy and recoverability. CESS truly addresses the single point of failure faced by decentralized cloud storage systems, providing the industry with a multi-replica recoverable storage proof mechanism (PoDR²) based on data ownership, and achieving efficiency in encoding and decoding that far exceeds similar projects. Users can securely store data while flexibly and efficiently accessing it.