Filesystems Archives - Page 8 of 15

Storage Performance Considerations for AI Data Paths

By cfheoh | June 17, 2019 - 10:50 am |June 17, 2019 100Gigabit Ethernet, Algorithm, Analytics, API, Artificial Intelligence, Big Data, Cloud, Composable Infrastructure, Data, Data Fabric, Data Management, Data Privacy, Data Security, Digital Transformation, Drivescale, E8 Storage, Edge Computing, Elastifile, Excelero, Filesystems, High Performance Computing, Hyperconvergence, Industry 4.0, Infiniband, Intel, Liqid, Lustre, Machine Learning, Mellanox Technologies, NVMe, Object Storage, Performance Benchmark, Performance Caching, Quantum Corporation, RDMA, Software-defined Datacenter, Storage Optimization, Storage Tiering, ThinkParq, Vast Data, Virtualization, WekaIO

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The hype of Deep Learning (DL), Machine Learning (ML) and Artificial Intelligence (AI) has reached an unprecedented frenzy. Every infrastructure vendor from servers, to networking, to storage has a word to say or play about DL/ML/AI. This prompted me to explore this hyped ecosystem from a storage perspective, notably from a storage performance requirement point-of-view.

One question on my mind

There are plenty of questions on my mind. One stood out and that is related to storage performance requirements.

Reading and learning from one storage technology vendor to another, the context of everyone’s play against their competitors seems to be “They are archaic, they are legacy. Our architecture is built from ground up, modern, NVMe-enabled“. And there are more juxtaposing, but you get the picture – “We are better, no doubt“.

Are the data patterns and behaviours of AI different? How do they affect the storage design as the data moves through the workflow, the data paths and the lifecycle of the AI ecosystem?

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Whither HPC, HPE?

By cfheoh | May 26, 2019 - 8:07 pm |May 26, 2019 Acquisition, Analytics, Artificial Intelligence, Big Data, Business Continuity, Cloud, Cloudian, Cohesity, Commvault, Cray Inc, Data Archiving, Data Direct Networks, Data Management, Data Protection, Datera, Deep Learning, Filesystems, High Performance Computing, HPE, HPE Simplivity, Hyperconvergence, Machine Learning, NAS, Nexenta, Object Storage, Qumulo, Scale-out architecture, Server SAN, Simplivity, Tintri, WekaIO, Zerto

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HPE is acquiring Cray Inc. Almost 3 years ago, HPE acquired SGI. Back in 2017, HPE partnered WekaIO, and invested big in the latest Series C funding of WekaIO just weeks ago.

Cray, SGI and WekaIO are all strong HPC technology companies. Given the strong uptick in the HPC market, especially commercial HPC, we cannot deny HPE’s ambition to become the top SuperComputing and HPC vendor in the industry. Continue reading →

Did Cloud Kill LTFS?

By cfheoh | May 21, 2019 - 10:39 am |May 21, 2019 Acquisition, Backup, Business Continuity, Cloud, Data, Data Archiving, Data Availability, Data Domain, Data Management, Data Protection, Deduplication, DellEMC, Disks, EMC, ExaGrid, Falconstor, Filesystems, HDS, HPE, IBM, LTO, NAS, NetApp, Object Storage, Quantum Corporation, Strongbox, Veritas

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I like LTFS (Linear Tape File System). I was hoping it would take off but it has not. And looking at its future, its significance is becoming less and less relevant. I look if Cloud has been a factor in the possible demise of LTFS in the next few years.

What is LTFS?

In a nutshell, Linear Tape File System makes LTO tapes look like a disk with a file system. It takes a tape and divides it into 2 partitions:

Index Partition (XML Index Schema with file names, metadata and attributes details)
Data Partition (where the data resides)

Diagram from https://www.snia.org/sites/default/orig/SDC2011/presentations/tuesday/DavidPease_LinearTape_File_System.pdf

It has a File System module which is implemented in supported OS of Unix/Linux, MacOS and Windows. And the mounted file system “tape partition” shows up as a drive or device.

Assassination attempts

There were many attempts to kill off tapes and so far, none has been successful.

Among the “tape-killer” technologies, I think the most prominent one is the VTL (Virtual Tape Library). There were many VTLs I encountered during my days in mid-2000s. NetApp had Alacritus and EMC had Clariion Disk Libraries. There were also IBM ProtecTIER, FalconStor VTL (which is still selling today) among others and Sepaton (read in reverse is “No Tapes’). Sepaton was acquired by Hitachi Data Systems several years back. Continue reading →

Figuring out storage for Kubernetes and containers

By cfheoh | April 16, 2019 - 6:44 pm |April 16, 2019 Amazon Web Services, API, Cloud, Containers, Data, Data Archiving, Data Availability, Data Management, Data Protection, Data Security, Docker, Edge Computing, Elastifile, Fibre Channel, Filesystems, Google, Hyperconvergence, Kubernetes, NFS, Openstack, Performance Benchmark, Performance Caching, Robin.io, Snapshots, Software Defined Storage, Storage Optimization, Virtualization, VMware

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Oops! I forgot about you!

To me, containers and container orchestration (CO) engines such as Kubernetes, Mesos, Docker Swarm are fantastic. They scale effortlessly and are truly designed for cloud native applications (CNA).

But one thing irks me. Storage management for containers and COs. It was as if when they designed and constructed containers and the containers orchestration (CO) engines, they forgot about the considerations of storage and storage management. At least the persistent part of storage.

Over a year ago, I was in two minds about persistent storage, especially when it comes to the transient nature of microservices which was so prevalent and were inundating the cloud native applications landscape. I was searching for answers in my blog. The decentralization of microservices in containers means mass deployment at the edge, but to have the pre-processed and post-processed data stick to the persistent storage at the edge device is a challenge. The operative word here is “STICK”.

Two different worlds

Containers were initially designed and built for lightweight applications such as microservices. The runtime, libraries, configuration files and dependencies are all in one package. They were meant to do simple tasks quickly and scales to thousands easily. They could be brought up and brought down in little time and did not have to bother about the persistent data stored by the host. The state of the containers were also not important to the application tasks at hand.

Today containers like Docker have matured to run enterprise applications and the state of the container is important. The applications must know the state and the health of the container. The container could be in online mode, online but not accepting data mode, suspended mode, paused mode, interrupted mode, quiesced mode or halted mode. Each mode or state of the container is important to the running applications and the container can easily brought up or down in an instance of a command. The stateful nature of the containers and applications is critical for the business. The same situation applies to container orchestration engines such as Kubernetes.

Container and Kubernetes Storage

Docker provides 3 methods to local storage. In the diagram below, it describes:

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WekaIO controls their performance destiny

By cfheoh | March 17, 2019 - 5:33 pm |March 17, 2019 Amazon Web Services, Analytics, Appliance, Big Data, CIFS, Cloud, Deep Learning, Filesystems, Flash, High Performance Computing, Infiniband, Linux, Lustre, Machine Learning, Mellanox Technologies, NAS, NetApp, NFS, NVMe, Object Storage, PCIe, Performance Benchmark, Performance Caching, RDMA, Scale-out architecture, SMB, Software Defined Storage, Storage Field Day, Storage Optimization, Storage Tiering, Tech Field Day, Virtualization, WekaIO, Western Digital

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[Preamble: I have been invited by GestaltIT as a delegate to their Tech Field Day for Storage Field Day 18 from Feb 27-Mar 1, 2019 in the Silicon Valley USA. My expenses, travel and accommodation were covered by GestaltIT, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

I was first introduced to WekaIO back in Storage Field Day 15. I did not blog about them back then, but I have followed their progress quite attentively throughout 2018. 2 Storage Field Days and a year later, they were back for Storage Field Day 18 with a new CTO, Andy Watson, and several performance benchmark records.

Blowout year

2018 was a blowout year for WekaIO. They have experienced over 400% growth, placed #1 in the Virtual Institute IO-500 10-node performance challenge, and also became #1 in the SPEC SFS 2014 performance and latency benchmark. (Note: This record was broken by NetApp a few days later but at a higher cost per client)

The Virtual Institute for I/O IO-500 10-node performance challenge was particularly interesting, because it pitted WekaIO against Oak Ridge National Lab (ORNL) Summit supercomputer, and WekaIO won. Details of the challenge were listed in Blocks and Files and WekaIO Matrix Filesystem became the fastest parallel file system in the world to date.

Control, control and control

I studied WekaIO’s architecture prior to this Field Day. And I spent quite a bit of time digesting and understanding their data paths, I/O paths and control paths, in particular, the diagram below:

Starting from the top right corner of the diagram, applications on the Linux client (running Weka Client software) and it presents to the Linux client as a POSIX-compliant file system. Through the network, the Linux client interacts with the WekaIO kernel-based VFS (virtual file system) driver which coordinates the Front End (grey box in upper right corner) to the Linux client. Other client-based protocols such as NFS, SMB, S3 and HDFS are also supported. The Front End then interacts with the NIC (which can be 10/100G Ethernet, Infiniband, and NVMeoF) through SR-IOV (single root IO virtualization), bypassing the Linux kernel for maximum throughput. This is with WekaIO’s own networking stack in user space. Continue reading →

StorPool – Block storage managed well

By cfheoh | March 13, 2019 - 8:34 am |March 13, 2019 100Gigabit Ethernet, API, Cloud, Clusters, Data Availability, Data Management, Disks, Filesystems, High Performance Computing, iSCSI, Linux, Lustre, Nexenta, NVMe, Openstack, Performance Benchmark, Performance Caching, Scale-out architecture, Server SAN, Software Defined Storage, Storage Field Day, Storage Optimization, Storpool, Tech Field Day, Virtualization, VMware

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Storage technology is complex. Storage infrastructure and data management operations are not trivial, despite what the hyperscalers like Amazon Web Services and Microsoft Azure would like you to think. As the adoption of cloud infrastructure services grow, the small and medium businesses/enterprises (SMB/SME) are usually left to their own devices to manage the virtual storage infrastructure. Cloud Service Providers (CSPs) addressing the SMB/SME market are looking for easier, worry-free, software-defined storage to elevate their value to their customers.

Managed high performance block storage

Enter StorPool.

StorPool is a scale-out block storage technology, capable of delivering 1 million+ IOPS with sub-milliseconds response times. As described by fellow delegate, Ray Lucchesi in his recent blog, they were able to achieve these impressive performance numbers in their demo, without the high throughput RDMA network or the storage class memory of Intel Optane. Continue reading →

Clever Cohesity

By cfheoh | March 11, 2019 - 7:28 pm |March 11, 2019 Analytics, API, Appliance, Artificial Intelligence, Backup, Big Data, Business Continuity, Cloud, Clusters, Cohesity, Data, Data Archiving, Data Availability, Data Management, Data Protection, Data Security, Deep Learning, Disaster Recovery, Edge Computing, eDiscovery, Filesystems, Fog Computing, Hadoop, Hadoop Clusters, Hyperconvergence, Interica, Machine Learning, Object Storage, Scale-out architecture, Software Defined Storage, Storage Field Day, Tech Field Day, Veritas

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This is clever. This is very smart.

The moment the Cohesity App Marketplace pitch was shared at the Storage Field Day 18 session, somewhere in my mind, enlightenment came to me.

The hyperconverged platform for secondary data, or is it?

When Cohesity came into the scene, they were branded the latest unicorn alongside Rubrik. Both were gunning for the top hyperconverged platform for secondary data. Crazy money was pouring into that segment – Cohesity got USD250 million in June 2018; Rubrik received USD261 million in Jan 2019 – making the market for hyperconverged platforms for secondary data red-hot. Continue reading →

VAST Data must be something special

By cfheoh | February 28, 2019 - 9:59 pm |March 1, 2019 Analytics, Artificial Intelligence, Big Data, CIFS, Cloud, Clusters, Composable Infrastructure, Data, Data Fabric, Data Management, Data Protection, Deduplication, Edge Computing, Filesystems, High Performance Computing, Infiniband, Machine Learning, NAS, NFS, NVMe, Object Storage, Scale-out architecture, Software Defined Storage, Tech Field Day, Vast Data, XtremIO

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Vast Data coming out bash!

The delegates of Storage Field Days were always the lucky bunch. We have witnessed several storage technology companies coming out of stealth at these Tech Field Days. The recent ones in memory for me were Excelero and Hammerspace. But to have one where the venerable storage doyen, Mr. Howard Marks, Vast Data new tech evangelist, to introduce the deep dive of Vast Data technology was something special.

For those who knew Howard, he is fiercely independent, very storage technology smart, opinionated and not easily impressed. As a storage technology connoisseur myself, I believe Howard must have seen something special in Vast Data. They must be doing something extremely unique and impressive that someone like Howard could not resist, and made him jump to the vendor side. This sets the tone of my blog.

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Minio – the minimalist object storage technology

By cfheoh | February 7, 2019 - 10:57 am |February 7, 2019 Amazon Web Services, Analytics, API, Appliance, Big Data, Cloud, Data, Data Archiving, Data Fabric, Data Management, Data Protection, Data Security, Deep Learning, Disaster Recovery, Edge Computing, Filesystems, Flash, FreeNAS, HDS, High Performance Computing, Hitachi Vantara, Industry 4.0, Katana Logic, Linux, Machine Learning, Minio, NAS, NetApp, NFS, Object Storage, Openstack, Redhat, Scale-out architecture, Tech Field Day

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The Marie Kondo Konmari fever is sweeping the world. Her decluttering and organizing the home methods are leading to a new way of life – Minimalism.

Complicated Storage Experience

Storage technology and its architecture are complex. We layer upon layer of abstraction and virtualization into storage design until at some stage, choke points lead to performance degradation, and management becomes difficult.

I recalled a particular training I attended back in 2006. I just joined Hitachi Data Systems for the Shell GUSto project. I was in Baltimore for the Hitachi NAS course. This was not their HNAS (their BlueArc acquisition) but their home grown NAS based on Linux. In the training, we were setting up NFS service. There were 36 steps required to setup and provision NFS and if there was a misstep, you start from the first command again. Coming from NetApp at the time, it was horrendous. NetApp ONTAP NFS setup and provisioning probably took 3 commands, and this Hitachi NAS setup and configuration was so much more complex. In the end, the experience was just unworldly for me.

Introducing Minio to my world, to Malaysia

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Sleepless in Malaysia with Object Storage

By cfheoh | January 22, 2019 - 1:42 pm |January 22, 2019 Amazon, Amazon Web Services, Analytics, API, Big Data, Cloud, Cloudian, Clusters, Data Management, Deep Learning, DellEMC, Dropbox, Filesystems, Google, Hadoop, Hadoop Clusters, HDS, IDC, IoT, iSCSI, Linux, Machine Learning, Microsoft, Minio, NAS, NFS, Object Storage, OpenIO, Redhat, Security, swiftstack

Object Storage? What’s that?

For the past couple of months, I have been speaking with a few parties in Malaysia about object storage technology. And I was fairly surprised with the responses.

The 2 reports

For a start, I did not set out to talk about object storage. It kind of fell onto my lap. 2 recent Hitachi Vantara reports revealed that countries like Australia, Hong Kong and even South East Asian countries were behind in their understanding of what object storage was, and the benefits it brought to the new generation of web scale and enterprise applications.

In the first report, an IDC survey sponsored by Hitachi Vantara, mentioned that 41% of the enterprises in Australia are not aware of object storage technology. In a similar survey, this one pointing towards Hong Kong and China, the percentages were 38% and 35% respectively. I would presume that the percentages for countries in South East Asia would not fall too far from the apple tree.

How is Malaysia doing?

However, I worry that the percentage number could be far more dire in Malaysia. In the past 2 months, responses from several conversations painted a darker hue about object storage technology with the companies in Malaysia. These included a reasonable sized hosting company, a well-established systems integrator, a software development company, several storage practitioners in Openstack and a DellEMC’s regional consultant for unstructured data. The collective conclusion was object storage technology was relatively unknown (probably similar to the percentages to the IDC/Hitachi Vantara reports), but it appeared to be shunned at this juncture. In web scale applications, Redhat Ceph block and files appeared popular in contrast to Openstack Swift. In enterprise applications, it was a toss of iSCSI and NFS.

Image from https://zdnet4.cbsistatic.com/hub/i/r/2018/04/24/c79e9dfb-b4a9-46bb-b831-f2c57fdf8a1d/resize/470xauto/5e4846d1bc7a034c382baf6dcbb612ed/cloud-storage.jpg

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Category Archives: Filesystems