Instance Data Storage & Quota

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Hornbill provides a very flexible elastic storage scheme that gives customers unlimited cloud storage where you only pay for what you actually use.

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How does Hornbill measure space used

Hornbill only measures space used by your instances data, it does not measure disk space used by our software or any infrastructure components we deploy in order to deliver the Hornbill service. The measurement is broken down into two separate domains known as "Disk Storage" and "Database Storage". We separate these two for good reason. For "Database Storage" the underlying database we use (MariaDB) and its storage engine determine the space utilised for a given database (each customer instance has its own dedicated database). For "Disk Storage" this is where we store files (see explanation of our Content Addressable File Store technology) below, each customer also has their own CAFS store.

Disk Storage

The following elements of your instance contribute towards disk storage usage

  • File Attachments (e-mails, posts, entity records, requests, tasks etc...)
  • Content Indexes
  • Embedded Images
  • Documents (uploaded into Document Manager)
  • Installed Apps
  • Any other large binary object

Database Storage

The following elements of your instance contribute towards database storage usage

  • Posts and comments in activities
  • Tasks
  • Customer, Contact and other Database Record
  • Documents (created in Document Manager)
  • Business Processes
  • Reports
  • Any dynamic content thats added to your database through the API's, forms and integrations

Data Encryption

All data is physically stored on SSD or Hard Disks and is block-level encrypted at rest at all times. Furthermore, data is stored in a RAID configured disk set, spread across multiple physical disks making impossible to extract any meaningful data without having all physical disks in a set to extract from. We use the industry-strength AES256 encryption scheme throughout and have a comprehensive key management system ensuring every physical and virtual server has its own set of string, unique keys for encryption.

Data Segregation

Hornbill has been designed with special attention paid to the security of data, specifically, we wanted to achieve the maximum isolation between each customer's data as possible while still getting the benefit of multi-tenancy in deployment and upgrades. Hornbill is designed to deliver the best of both worlds to our customers by adopting a hybrid data isolation model. To best explain Hornbill's data isolation model we first need to describe the more traditional models.

Multi-Instance Model

This model provides a high-level of data isolation because a fully independent instance of the software, database, and other components are running in full isolation for each and every customer. Typically this is delivered by providing a dedicated instance of an operating system (Linux or Windows etc) upon which a copy of the service providers software is running as well as the data set needed to support the customer's specific instance. An example of this kind of SaaS architecture might be ServiceNow and Myservicedesk.com (Supportworks in the cloud).

Advantages

  • Data Isolation is achieved at the operating system level
  • Compute resources can be allocated/dedicated to individual customers
  • Customers can run specific versions of the vendor's software in their specific instance

Disadvantages

  • Web-scale expandability is difficult to achieve, compute resources are finite as they are tied to virtual machine/operating system compute resources
  • Customers may find themselves not able to upgrade, the flexibility of running/locking down on individual versions of the software creates this problem as the software designers are not forced into considering upgradability of every customer's individual changes/customizations, this is especially true when customizations require code to be developed as part of the customization

Multi-Tenant

This model provides data isolation at the application layer which means that every customer's data is stored in the same database and the application code ensures that data for each customer is only served to that customer. Properly implemented it is generally safe and reliable and has many large scale proven applications deployed today. There are some big advantages but these are mostly weighted to the benefit of a service provider who in turn delivers benefits back to the customer through economies of scale and therefore price (in theory at least). Salesforce.com is a good example of a solution that adopts this model.

Advantages

  • Web-scale expandability is easier to achieve as the same compute resources are shared with all customers at the same
  • All customers are on the same version of the software, that means all customers get all upgrades all of the time (think Facebook or Gmail)
  • Any customisations done by customers for their own use have to be completely isolated (and therefore protected) during updates - this imposes the right behaviours on the software designers and development teams

Disadvantages

  • Customers have no control over the versions of the software they use, they have to be prepared to consume the software as a service
  • The risk of data leaking is moved up the stack to the application layer, this means that the risk of unexpected data exposure is higher than lower-level data isolation.
  • Code developed in the application layer could expose data unintentionally.

Hornbill's Model

There are pros and cons to both of the models described above and there are many more ways to deliver a SaaS solution than just those two extremes. Hornbill adopted a model that could best be described as a combination of those two approaches. It's hard to put a name to what we have built but we would describe it as having true multi-tenant architecture but with enterprise-class data isolation. The best way to explain this would be to set out what our primary design goals were at the time of designing our architecture and what we ultimately implemented.

  • Number one on our agenda is we wanted a data isolation model comparable with that found in a multi-instance mode.
    • Data access requires a two-phase model for controlling access. Every data storage scheme implements at least two layers of access control, the first of which is *instance awareness*, meaning every request for access to data has to be identifiable against a specific instance for every request and to every storage container, if the storage container does not belong to the instance then the request will fail.
    • Each customers data is fully isolated at the lowest possible level, each customer has their own database, with isolation provided at the database security level (so this is independent of Hornbill's own code and implemented at the infrastructure level away from the application code) using a unique system account per instance.
    • Each customer's file storage has to be fully isolated at the filesystem level and held within its own container, access to which is again fully instance context-aware. In addition to this, within a container, file storage uses a content addressable system which guarantees that addressable content is unique to its actual content, so even if there was some accidental cross-contamination of customers data someone would need to guess the content ID (which is a cryptographically strong SHA-256 checksum of the actual content) which for all practical purposes is unachievable in any way that would create a usable exploit.
  • Web applications run on our front end servers - all customers use the exact same versions of software running on the same front end servers so compute resources can scale-out infinitely horizontal based on load and demand.
  • Application servers also scale-out horizontally without any theoretical limit. In practice, we organize our application services into POD's which providing workload distribution, durability and resilience to hardware or network failures.
  • All customers run the same version of our software stack, this forces good discipline and behavior in our software design, development, test and deployment teams.

Content Addressable File Store

As a general rule, storing large objects such as images, files, videos and other large binary objects it is very inefficient to use an RDBMS as a storage scheme. SQL servers are great for structured data but are far from ideal for storing things like files. Hornbill stores large objects using our own CAFS technology, CAFS stands for "Contact Addressable File Store" which unlike a conventional filesystem has some very unique and desirable properties.

  • Content is located by its unique fingerprint which is derived from the actual content of the file being stored.
  • Every unique piece of content is atomic and movable
  • Content inside a CAFS storage is automatically de-duplicated, in other words the way the CAFS works guarantees that any content stored will only ever be stored once so its very space efficient.
  • Content can be easily distributed across physical storage devices/servers/locations/geographies with minimal system management overhead.
  • Stale content (that is content that is rarely accessed or is effectively soft archived) can be moved to lower cost storage dynamically ensuring the most accessed and most up to date data is always held on and served high performance storage.

The bottom line is, our storage scheme is fast, efficient and capable of effectively unlimited storage, delivered elastically and with no administrative overhead placed on our customers for management. Read more about whats under the hood here Content Addressable File Store

Storage Quota and Utilisation

Every Hornbill instance comes with 30Gb of storage and additional storage can be purchased if needed. We audit storage utilisation daily can keep up to ten years of storage utilisation history on the following basis: -

  • Daily Database storage used for the last 90 days rolling
  • Monthly Database storage used for the last 120 months rolling
  • Daily Disk storage used for the last 90 days rolling
  • Monthly Disk storage used for the last 120 months rolling

Your storage information can be seen in the Hornbill Administration tool under the "Subscription Overview" section.

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