Category Archives: Blog

The Technology Behind Storageless Data

Hammerspace provides storageless data. That statement itself will raise many questions about the specific use cases that Hammerspace can solve. The use cases are merely the shape and form of the fundamental Hammerspace solution, namely separating metadata from data so that they can be orchestrated independently of one another. The goal of this blog is to take the reader quickly through the evolution of the abstraction we call a “file”, with the hope that it makes all the use cases Hammerspace addresses readily apparent. The reader is expected to be familiar with basic storage concepts.

Knock-out the Persistent Data Dilemma with Storageless Data from Hammerspace

Cut the tethers of data gravity and stop worrying about storage

If we want to truly go cloud-native and realize the promise of Kubernetes to enable workload portability across any environment, a storage infrastructure-centric approach isn’t going to get us there.  Storage will always wrestle with the consequences of data gravity.  To go cloud-native and have true portability of workloads, we  must use technology that makes complicated enterprise storage obsolete without forcing rip-and-replace. To enable persistent data orchestration across the hybrid cloud and overcome the data gravity generated by siloed storage infrastructure, we must make data storageless.

The advantage of storageless data orchestration

  • Pay-as-you-go

An elastic consumption model based on capacity means that you only pay for what you use as you scale up or down.

  • App data portability

Instant access to data from the cloud to the edge using live data mobility automated by ML-driven data placement optimization.  Operating at file and container-level granularity, this allows users self-service their data management while avoiding disruptive data migrations and the expense of unnecessary copies.

  • Use any storage

Data resides on storage systems but is not bounded by the physical infrastructure. So, persistent data management in Kubernetes is greatly simplified by managing through metadata to abstract data from the infrastructure.

  • Ubiquitous data services

Enterprise data services are defined by the data, not the storage, allowing users to self-service their data management anywhere, from the cloud to the edge, without refactoring their apps.

Storageless data orchestration makes workflows trivial

Data becomes storageless when it is freed from the tethers of the storage infrastructure that  it lives on and defines its characteristics. By using a global file system built on a metadata engine, Hammerspace serves data from block, file, or object storage infrastructure to workloads located anywhere – on-demand. Data services are tied to the data through the metadata to be ubiquitous from the cloud to the edge. This simplifies data orchestration at scale by making app data portable, protected, and high performance – what Kubernetes does for containers, Hammerspace does for data.  Complicated data management workflows like DR, Backup, or Test/Dev that used to require a lot of copying and disruption are now fully automated and self-serviced by users.

How do I get started with storageless data?

Try 10-Tb of Hammerspace for free in the cloud..  Available in AWS Marketplace, Google Marketplace, and Azure.

  • All features are included with unlimited nodes and availability zones.
  • 8×5 Support is available directly from the Hammerspace team through email and Slack.
  • On-premises to cloud (Hybrid cloud support is available.
  • Read more here for details.

About Hammerspace

Hammerspace is storageless data for hybrid cloud Kubernetes environments.  By untethering data from the infrastructure, Hammerspace overcomes data gravity to provide dynamic and efficient hybrid cloud storage as a fully automated, consumption-based resource. Users self-service their persistent data orchestration to enable workload portability from the cloud to the edge.

To learn more, visit us at www.hammerspace.com or on Twitter @Hammerspace_Inc

 

 

What is Data Orchestration?

Background

Kubernetes understood its limitations and, therefore, left storage out. Provisioning compute is a distinctly different discipline than provisioning storage. Kubernetes introduced the notion of Persistent Volumes (PV) and Persistent Volume Claims (PVC) to manage the challenge of providing persistent storage to non-persistent applications, such as Kubernetes Pods. They are APIs that decouple the what from the how or, in other words, consumption from implementation details. It is a highly useful disaggregation that turns infrastructure into reusable storage pools for Kubernetes Pods.

Data Antigravity

Hammerspace has taken an identical approach to Kubernetes by decoupling data from the underlying infrastructure. This approach frees data from the limitations of storage infrastructure. The explosive growth of data has amplified challenges such as silos, sprawl, data placement, and management of capacity and performance. Finding data across disparate silos has become increasingly difficult leading to assets being created over and over again leading to more and more copies. Building silos inevitably leads to stranded or insufficient performance and capacity driving costs higher. Moving data between silos or to new components not only drives costs higher but also leads to dreaded maintenance windows and downtime. Data, in short, has gravity! By decoupling data from those limitations, Hammerspace removes the silo boundaries reducing costs, increase collaboration by making it ubiquitous, and the usefulness of data. Hammerspace is anti-gravity for data!

Data Orchestration

The ability to abstract data from underlying storage infrastructure is unique to Hammerspace. It separates the ‘how’ (data management) from the ‘what’ (storage management). In other words, it is not necessary to become a storage expert just to provision storage resources to an application. This is exactly what makes up data orchestration. This is also what makes Hammerspace distinctly different from legacy storage or data management solutions. What Kubernetes has done for applications, Hammerspace does for data management. So how do we go from managing storage silos to orchestrating data? The data orchestration journey involves four interdependent steps. They are  decoupling, assimilation, objectives, and portability.

Decoupling

The first step in the data orchestration journey is the decoupling of data from the limitations of the underlying infrastructure. Decoupling infrastructure removes legacy storage ills such as silos, sprawl, out-of-control copies, the lack of business-level controls, and downtime due to forklifts and software upgrades. To orchestrate data, we must first liberate data from its infrastructure limitations.

Assimilation

Data gravity is another major obstacle in data orchestration. The topic often comes up and is generally assumed to be an intractable problem constrained by the laws of physics, but what if there were a more elegant solution? Hammerspace has the ability to assimilate the metadata of unstructured storage silos. This effectively tears down the walls between disparate storage solutions. By first decoupling silos and then assimilating their metadata the walls between, for example, a NetApp and an Isilon cluster we can now treat it as a single pool of resources. Hammerspace metadata assimilation unites siloed data and makes it possible to perform data management without data gravity.

Objectives

Epistemology, the science of knowledge, outlines two distinct areas: the what and the how. Knowing what something is versus how to accomplish it. This important distinction is not restricted to a classroom discussion on symbolic logic. It pertains directly to how we leverage technology to accomplish business objectives. Hammerspace Objectives are declarative statements that define the desired end-state through the metadata without having to make infrastructure changes.

Declaring the intent of data (i.e. its desired end-state) is vastly simpler than having to define every single step to be taken (imperative policies) to accomplish the desired end-state. We have already removed silo boundaries and data gravity in previous steps. We can now leverage declarative policies, called objectives in Hammerspace nomenclature to replace error-prone imperative policies to accelerate business outcomes.

Portability

This is the crowning jewel in data orchestration. The subsequent steps of removing silo boundaries, removing data gravity and declaring desired business outcomes has paved the way for the final challenge in data orchestration: how to make data portable. Hammerspace Global Namespace allows underlying infrastructure to be addressed as a single resource pool. NFS workloads can access and consume exports with universal naming consistency regardless of location. SMB workloads can access globally consistent UNC paths.

Hammerspace Global File System serves NFS v3 and v4.2 as well as SMB v2 and v3 with full multi-protocol access and preservation of SMB ACLs. Hammerspace also provides a fully featured Container Storage Interface (CSI) for any-and-all Kubernetes workloads. The Hammerspace CSI plug-in provides Kubernetes Persistent Volumes that deliver block volumes, local file storage volumes, as well as shared storage volumes. Hammerspace makes data portable and ubiquitous.

Conclusion

Data Orchestration relies on the subsequent steps of decoupling data from infrastructure, metadata assimilation, leveraging declarative statements to accelerate business outcomes, and mobilizing it to make it ubiquitously available to all applications, end-users, and workloads. Decoupling data from infrastructure frees data from legacy storage limitations. It unites disparate storage silos into cohesive resource pools. Metadata assimilation removes data gravity that ultimately makes data easier to manage and distribute according to business intent. Objectives, in turn, allows you to declare the desired end-state without having to figure out every single step to be taken. Hammerspace-powered machine learning knows how to perform the necessary steps to produce the desired end-state you declare with an objective. It is important to note that Hammerspace Objectives can be implemented through GUI, CLI, or API.

Hammerspace has rich custom metadata options, such as tagging, descriptors, and classification. A Hammerspace Objective can be as simple as a GUI checkbox that delivers non-disruptive data migration from one vendor to another, from one data center to another, from a data center to a public cloud, or even between clouds. Objectives can also take the form of custom scripts that powers a highly sophisticated workflow or data pipeline. Hammerspace delivers the power to free data from infrastructure silos, removing data gravity, accelerating business outcomes, and making file data available on planet-scale.

Get Started with Hammerspace Data Orchestration Today

Take a look at how you can modernize workloads and eliminate silos with Hammerspace data orchestration by going to the URL below.

https://hammerspace.com/10-tb/

Talkin’ the Talk

In this first of a five-part series, we are going to start simple. If you know this stuff, great, but some of it is unfamiliar then this piece should explain what Kubernetes is, how it operates, and the basic language you need to know to sound like an expert.  

Where did Kubernetes come from?
Kubernetes is an open-source project governed by the Cloud Native Computing Foundation (CNCF), which is a subsidiary of the Linux  Foundation​, and was gifted to the Linux Foundation by Google in 2015.   Kubernetes traces its roots directly from the Borg project, which was Google’s internal container-oriented cluster management system.    Kubernetes is often referred to in shorthand as K8s simply because there are 8 letters between the “K” at the beginning of the word, and the “S” at the end. 

What is Kubernetes?
Kubernetes, in its simplest form is an orchestrator of  containerized applications, but such a broad statement requires explanation. A container is the smallest possible entity for delivering an application. It usually consists of a single application and only the environment it needs to run. This allows applications to become truly portable throughout the entire software development lifecycle without running into environment conflicts that are so common when applications share an entire operating system. A software developer can, subsequently, wrap the newly created code into a self-contained structure, a container, consisting only of the application and its particular dependencies. Containers ensure a consistent environment of dependencies as the new code moves from development to quality assurance testing, to integration, to production delivery that are almost always hosted on separate systems. Containers make applications independent of system-level changes enabling things like microservice architectures. In other words, containers do not care about changes to its outside environment because it already has everything it needs within itself. This self-sufficiency throughout the software development lifecycle is what makes Continuous Integration / Continuous Deployment (CI/CD) possible. The purpose of CI/CD is, of course, to accelerate our production pipeline so we get to market faster.  Kubernetes solves an additional challenge made possible by containerization, namely scalability and portability. By orchestrating containers we can easily and rapidly create thousands and thousands of copies at virtually any location to address rapidly changing workloads. Let’s look at an example to which most of us can relate.  Every time you talk to Alexa, Siri, or Google an orchestrator, such as Kubernetes, fires up a container for the duration of the question. Once your question or conversation terminates so does the container. The system resources the container required are subsequently released and repurposed to be available for another container to use. Containers Orchestration allows instant scalability and elasticity with predictable consistency and quality that was previously impossible. Events like Black Monday online sales would probably crash within minutes without Container Orchestration. Delivery of software and fixes would take months instead of days or weeks.  

A Glossary of Kubernetes Terms: 

Container:  A container is a standardized structure which can store and run applications or services. If your application has been re-architected into micro-services, now each micro-service can be stored in its own container, along with everything it needs to run (settings, libraries, dependencies etc.), creating a closed operating environment so the container can run on any machine. 

Docker:   Docker is not, as many people believe, a competitor to Kubernetes. Rather it is the leading open-source containerization technology, controlling some 95% of the market. The two technologies are used together. Docker allows you to “create” containers and Kubernetes helps you to “manage” containers.

Pods:  A pod is the unit of scheduling in Kubernetes and holds one or more containers. Containers that are part of the same pod are guaranteed to be scheduled together onto the same machine and can share state via local volumes. 

Nodes:   Nodes are the hardware components and are comprised of either a virtual machine hosted in the cloud, or a physical machine in a data center.   Nodes can also be thought of as CPU/RAM resources to be used by a cluster and not just as a virtual machine, since a pod is not constrained to any given machine, but can move freely across all available resources as needed. 

Cluster:   A cluster is a series of nodes that are aware of each other and connect together to run the containerized applications being orchestrated by Kubernetes. By pooling their resources, the nodes make the cluster more powerful than the individual machines that compose it. Kubernetes moves pods around the cluster as nodes are scaled (added/removed). 

Services:  A Kubernetes Service is an abstraction which defines a logical set of pods running somewhere in your cluster, that all provide the same functionality. When created, each Service is assigned a unique IP address, which is tied to the lifespan of the Service and will not change while the Service is alive. Pods can be configured to talk to the Service and know that communication to the Service will be automatically load-balanced out to some pod that is a member of the Service. 

Labels:  A common set of labels allows tools to work together, describing objects in a common manner that all tools can universally understand. In addition to supporting tooling, the recommended labels describe applications in a way that can be queried.

IP-Per-Pod:  Kubernetes makes it easy to run off-the-shelf open-source applications because it is able to give every pod and service its own IP address, allowing pods to be treated much like VMs or physical hosts, with access to the entire port space. This is by no means a complete list of the terms surrounding Kubernetes, and we will continue to add to it with each newsletter. Next month we will dive into how to identify and qualify a Kubernetes deal. 

Hammerspace announces version 4.4.0

Hammerspace announces a new software release, version 4.4

 

Hammerspace is thrilled to announce the general availability of version 4.4 which adds an expanded portfolio of services and features to help businesses with their SDS and hybrid multi-cloud needs.

 

With this release, Hammerspace adds a number of Enterprise features including support for larger number of shares, migrating data directly between different cloud tiers and WORM. In addition to that, a number of Usability enhancements for UI and data assimilation are included in this release as well. Furthermore, Hammerspace now supports Enterprise RedHat Linux 7.8 NFS v4.2 clients with version 4.4.

 

Last-but-not-least, Hammerspace version 4.4 also offers tech preview of the Universal Global Namespace, Synchronous Data Mirroring and a Capacity Planning tool that helps customers better plan their capacity needs over time.

 

With these new capabilities, Hammerspace customers can easily consume data across hybrid and multi-cloud environments without compromising on security, performance, availability, or ease of use.

 

New Features in version 4.4

 

Support for large number of Shares

With version 4.4, Hammerspace can now scale up to hundreds of shares in a cluster.

Cloud to Cloud Mobility

When moving files between cloud tiers, data had to be rehydrated to NAS before getting uploaded to the destination cloud bucket. In Hammerspace version 4.4, this extra hop has been removed, so data can now be migrated directly from one cloud bucket to another.

Capacity reporting when adding new volumes

Hammerspace version 4.4 has the ability to detect and report used volume capacity when adding a new volume to the cluster. In addition to that, auto detection is built in to avoid data movement in order to balance capacity unless initiated by the user. This helps reduce any unexpected data movement when new storage volumes are added.

WORM support

Hammerspace now allows setting WORM specific attributes for WORM_EXPIRY and LEGAL_HOLD_EXPIRY dates. Once they are set, they cannot be deleted, they can only be changed to be effective at a later date for the data in the share. WORM support can be enabled using objectives across files, directories and shares, giving customers finer grained control over different types of files.

 

Functional Enhancements in version 4.4

GUI Scalability improvements

Along with the added support for more shares, a number of enhancements have also gone into Hammerspace version 4.4 for improving GUI responsiveness when handling large number of shares, volumes and storage nodes.

Assimilation enhancements and Performance improvements

Hammerspace supports assimilating third party NFS and SMB data, non-disruptively into its active namespace without making any changes to the original data. With this latest release, Hammerspace has added a number of usability enhancements focused on additional logging, non-disruptive error handling, ability to cancel assimilations and a better UI experience. In addition to that, this release also contains substantial performance improvements when assimilating NFS and SMB data.

 

Technology Preview Features

A technology preview feature is functionality exposed in the product for customers to test. The feature is not supported for Production usage however it is generally made available with full product support in the sub-sequent release.

Capacity planning analysis

HS provides customers with tools that help them plan their storage needs by allowing them to simulate data uploads to cloud without actually moving any data, while taking into account storage efficiency features like data compression and dedupe.

Synchronous Data Mirroring

As a tech preview feature, Hammerspace can now synchronously mirror data to different volumes for increased resiliency.

Global File System

Customers can now deploy a single namespace across different geographical sites and replicate data and metadata across these sites. The data in global shares are available Read-Write on multiple sites at the same time. Initial support goes up to 16 sites concurrently active on the same share.

 

NFS Client Support

Additional NFSv4.2 Client Support

Hammerspace has added support for Red Hat Enterprise Linux 7.8 clients for NFS 4.2 access in version 4.4. Red Hat Enterprise Linux 7.7 clients are already supported for NFSv4.2 access.

 

 

For more in-depth details on these features, go to https://hammerspace.com/blog/

 

To download the release and purchase a license, contact us at https://hammerspace.com/contact/

 

Hammerspace announces version 4.3.0

Hammerspace announces a new software release, version 4.3.0

 

Hammerspace is thrilled to announce the general availability of version 4.3 which adds an expanded portfolio of services and features to help businesses with their SDS and hybrid multi-cloud needs.

With this release, Hammerspace adds Data Encryption support in addition to usability enhancements like Alert cleanups upon Event recovery, GUI support for SMB assimilation, supporting one end point for all protocol access and preventing non-compliant NFSv4.2 clients from accessing the Anvil. Hammerspace is also now available in Amazon GovCloud for customers with additional security requirements.

Last-but-not-least, Hammerspace version 4.3 also offers tech preview of the Universal Global Namespace, WORM and a Capacity Planning tool that helps customers better plan their capacity needs over time.

With these new capabilities, Hammerspace customers can easily consume data across hybrid and multi-cloud environments without compromising on security, performance, availability, or ease of use.

 

New in v4.3.0

Data encryption support with on-premises Key Management support

In flight and at rest encryption of data when transferring it to and storing it in public-cloud buckets/containers is a primary concern for customers wanting to mobilize their data into the public-cloud. Additionally, customers want to have full control over the keys used for data encryption and also want the data encrypted on-premises using their keys before it leaves to get persisted in public-cloud buckets. Finally, customers would like a simple and single unified mechanism to encrypt their data across their private, hybrid and multi-public-cloud environments.

Hammerspace now supports encrypting user data when copying files to object-volumes using nCipher HSM.

NFS 4.2 client white listing support

Hammerspace supports Red Hat Enterprise Linux 7.7 clients for NFS 4.2 access and prevents any non-compliant NFS 4.2 client from accessing data by automatically redirecting connections to NFS v3.

Single end point access across protocols

In the past, customers had to access the Hammerspace namespace over different export end points based on the access protocol (NFS v3, SMB or NFS 4.2). Starting from version 4.3, Hammerspace is now accessible via the same end points across all protocols.

GUI support for SMB data assimilation

Hammerspace supports assimilating third party data into its active namespace without making any changes to the original data. With the latest release, Hammerspace has added GUI support for non-disruptive assimilation of SMB data into its namespace in addition to improving the performance of assimilating large number of files in the same directory.

Amazon GovCloud support

Hammerspace is now also available in the AWS GovCloud Marketplace. This allows Public sector customers with additional security requirements to deploy and start using Hammerspace in GovCloud at the click of a button.

Usability enhancements

Hammerspace version 4.3 contains a number of usability enhancements targeted at optimizing event processing, alert cleanup as well as only showing uncleared events on GUI or CLI login.

 

Technology Preview Features

A technology preview feature is functionality exposed in the product for customers to test. The feature is not supported for Production usage however it is generally made available with full product support in the sub-sequent release.

Capacity planning analysis

HS provides customers with tools that help them plan their storage needs by allowing them to simulate data uploads to cloud without actually moving any data, while taking into account storage efficiency features like data compression and dedupe.

Worm support

Hammerspace now allows setting objectives to enable WORM support across files, directories and shares, giving customers finer grained control over different types of files.

Global File System

Customers can now deploy a single namespace across different geographical sites and replicate data and metadata across these sites. The data in global shares are available Read-Write on multiple sites at the same time. Initial support goes up to 16 sites concurrently active on the same share.

 

 

For more in-depth details on these features, go to https://hammerspace.com/blog/

 

To download the release and purchase a license, contact us at https://hammerspace.com/contact/

 

 

 

 

 

 

Hammerspace Verified as Citrix Ready

Los Altos, CA, January 14th, 2020– Hammerspace is pleased to announce that its Hybrid Cloud File Service, which enables Citrix® Virtual Apps and Desktop users to access data across multiple locations and/or within the public cloud transparently, easily and quickly, have officially been verified as Citrix Ready®.

The Citrix Ready technology partner program offers robust testing, verification, and joint marketing for Digital Workspace, Networking, and Analytics solutions–with over 30,000 verifications listed in the Citrix Ready Marketplace. Hammerspace completed a rigorous testing and verification process for its Hammerspace Cloud File Service to ensure compatibility with Citrix Virtual Apps and Desktops, providing confidence in joint solution compatibility in order to replicate or migrate your Citrix virtual desktops data to any hardware platform within the Citrix environment.

Hammerspace helps reduce delays and improve response times when running virtual desktops from the hybrid cloud. Now, data is readily available, as it follows the user regardless of where they are located, greatly improving their virtual desktop experience, while also giving administrators far greater control and management of how and where this data is protected and stored.

The Hammerspace hybrid cloud file service successfully passed a series of tests established by Citrix and is compatible with all the latest versions of Citrix Virtual Apps and Desktops, including the long term service release versions 7.6 LTSR and 7.15 LTSR and more importantly with the Citrix Cloud based Citrix Virtual Apps and Desktops Service.

“We are committed to working closely with trusted partners – including the Citrix Ready partner ecosystem – in order to provide the highest quality experience for our customers,” says Tony Asaro, Director of Channel Sales, Hammerspace. “The Hammerspace hybrid cloud file service combined with Citrix Virtual Apps and Desktops service ensures customer confidence in joint solution compatibility.”

About Hammerspace
Hammerspace is a hybrid cloud file service that smashes the complexity of managing and protecting data on the hybrid-multi-cloud, eliminating the challenges of making unstructured data cloud-native and independent of the infrastructure. With non-disruptive, ML-driven data management, Hammerspace reduces the complexity of adopting hybrid, multi-site or Kubernetes workflows.

Holly Hagerman | Senior Partner
hollyh@connectmarketing.com
C: 801-368-6928

Persistent Data Protection for Kubernetes in the Enterprise

Kubernetes is a portable and extensible platform that provides orchestration of containerized applications. It facilitates declarative configuration and automation of workloads and services. In essence, Kubernetes frees applications from the underlying infrastructure through disaggregation without losing control of said workloads and services. The business outcome is improved time to market by accelerating the time it takes to build and deliver applications and services to customers.

Most containerized applications are stateless and short-lived, so their data only needs to persist for as long as the app runs; but what happens when stateful apps like databases are containerized and managed by Kubernetes?  The data processed and generated by stateful applications persists and must be protected against data loss, but how do you do this in a Kubernetes native way, without purchasing specialized infrastructure?  Hammerspace can protect persistent data across any cluster, cloud, or storage without DevOps or IT learning anything new or specific to any infrastructure.

The Hammerspace Difference

Hammerspace is a data-centric software solution that disaggregates data from its underlying infrastructure while retaining full control over the data. Kubernetes has transformed how applications are managed and delivered. Hammerspace is now transforming how data is managed and delivered. Hammerspace software can be spun up with ease in AWS, GCP, Azure, or on premises as virtual machines or on bare-metal hardware.

Kubernetes Container Storage Interface

The Hammerspace Container Storage Interface (CSI) driver is a full-featured implementation that supports both File and Block Persistent Volumes (PV) for Kubernetes. Functions such as volume create, volume delete, get capacity, volume stats, volume stage and unstage are fully supported.

Universal Global Namespace for Kubernetes

Hammerspace provides a single source of truth for data that stretches across hybrid multi-cloud infrastructures. Our Universal Global Namespace presents a unified view of data unbound from its underlying infrastructure. Where data resides geographically, and what platform it is stored on no longer matters. Global data visibility and accessibility make it fast and easy to access data across sites. Data is transferred on-demand when needed, and by policy if desired.

 

Data Protection

Hammerspace offers Active-Active Data Protection and Recovery. Snapshots can quickly be created and scheduled. By scheduling frequency and retention in a few simple steps you have declared the intent of a data set, and thus a Service Level Objective. Snapshots can be moved or/and copied anywhere across your storage resources, regardless of location. Once Kubernetes is connected to Hammerspace CSI driver, you manage storage resources and data protection through the Hammerspace API, CLI, or GUI.

Data Recovery

With Hammerspace, data is automatically recovered from snapshot if the active data is not available. Snapshots can be moved and/or copied anywhere to another storage volume regardless of location or performance tier across your infrastructure. This affords organizations the ability to choose the right blend of cost/performance. Declarative policies can automatically recover data from snapshot to Tier 1 without administrator action.

DevTest

The ability to restore data for DevTest refreshes is a key function to accelerate time to market. Hammerspace Toolkit allows fine-grained control over DevTest refresh copies, such as metadata tagging and descriptors. This can be easily automated through scripting. You can find additional information and usage examples on the Hammerspace GitHub page. Developers and other constituents can perform DevTest refresh on-demand through self-service.

Service Level Objectives for Kubernetes

Hammerspace Service Level Objectives offer full control over your data. Service Level Objectives are declarative policies that define desired end-state business objectives. This vastly simplifies and enhances controls over your data; where it lives, how it is stored, how it is consumed, as well as its availability, durability, and a number of other things. Hammerspace delivers an unprecedented ability to manage and deliver data. File-granular declarative policies accompanied by machine learning enable automated transitions in the hybrid multi-cloud.

Non-Disruptive Data Mobility for Kubernetes

Hammerspace Data Mobility allows you to control where data lives, how it is presented to Kubernetes, as well as the performance and cost. This is just one example of something you can easily and simply control with Service Level Objectives all the way down to a file-granular level. It only takes a few mouse-clicks or a single CLI command to seamlessly move data from one location to another, from on premises to cloud, and back. And this happens without any interruption to applications, end-users, or business processes.

Summary

Hammerspace makes any storage native to Kubernetes, with multi-cluster support on any storage platform, local and over distance, allowing you to instantly start stateful applications anywhere. In addition, Hammerspace Universal Global Namespace, Non-Disruptive Data Mobility, and Service Level Objectives offer a complete solution for Kubernetes workloads and data protection. The operational simplicity of Hammerspace smashes storage silos, automates data recovery with file-granular controls, and moves data non-disruptively across any storage.

The Data Highway to NetApp Cloud Volumes

Nine out of ten companies, according to research by IDG, will have some part of their applications or infrastructure in the cloud by 2019, and the rest expect to follow by 2021. A key driver is the explosive growth of unstructured data. But how do you move your data from on-premises to cloud without disruptive downtime? There are two parts to solving that challenge. First, we need a cloud service. Second, we need something that can move that data without business interruption.

NetApp Cloud Volumes is a file storage service that runs on your choice of AWS, Azure, or GCP. Cloud Volumes supports a wide range of NFS- and SMB-based workloads. This brings us to the second challenge. How do we painlessly lift data into NetApp Cloud Volumes from a variety of on-premises NAS storage solutions without downtime? Or more specifically, how do we ensure that applications and end-users can read and write data continuously during cloud migration?

Hammerspace is a hybrid cloud file service that provides powerful data management capabilities to migrate data to Cloud Volumes simply, quickly, and without disruption to productivity. Hammerspace adds three powerful capabilities to NetApp Cloud Volumes:

  1. An active-active universal global namespace
  2. File-granular data management policy engine (aka Service Level Objectives)
  3. Non-disruptive live data mobility

The Hammerspace Difference

Universal Global Namespace

Hammerspace provides a single source of truth for data that stretches across your entire infrastructure. A global namespace virtualizes data to present a unified view of data to application workloads across mixed storage resources. Global data visibility and accessibility make it fast and easy to access data across sites. Data is transferred on-demand when needed, and by policy if desired. With a locally managed namespace available on each site, performance of the data and metadata is maintained without compromise while making the data available across distance.

Service Level Objectives

File-granular declarative policies and machine learning enable an automated transition to cloud. You control the volumes, shares, directories, files, or any combination thereof that you want to migrate to NetApp Cloud Volumes as well as the level of data protection and durability.

Live Data Mobility

Hammerspace data services support NFS, SMB, and S3; deploying advanced data layout techniques to seamlessly move data, such as files and snapshots, through the namespace, even during active read/write. WAN optimization keeps network traffic efficient with automatic global deduplication and compression, while data is encrypted end-to-end using customer managed KMS. Hammerspace calls this Data Mobility. Let’s take a closer look at how this works.

In the following example, an application opens a file and, subsequently, receives layout from Hammerspace. The application can now start I/O. Data Mobility is, subsequently, requested to move data set from one or more data center NAS to Cloud. Layout is then recalled, but file remains open (no data flush). A new layout is provided to the application without interruption (no I/O impact). The new write layout then points to the data mover (Hammerspace DSX) while the new read layout points to original source. The Data Mobility process starts to mirror data to Cloud Volumes.

 

When Data Mobility is completed, the same process is followed in reverse order. The layout pointing to the data mover and original source is recalled and replaced by new layout pointing to Cloud Volumes. The Data Mobility process completes without zero interruption to business processes.

Conclusion

 

NetApp Cloud Volumes Services comes in three flavors, one for each of the major three major cloud providers: Azure NetApp Files, Cloud Volumes Services for AWS, and Cloud Volumes Services for GCP. This allows customers to choose one or more, or any combination thereof, to support their business needs. NetApp and Hammerspace are enabling enterprises to adopt a hybrid multi-cloud strategy.