Storage in a shiny multi-cloud space

The multi-cloud for infrastructure-as-a-service (IaaS) era is not here (yet). That is what the technology marketers want you to think. The hype, the vapourware, the frenzy. It is what they do. The same goes to technology analysts where they describe vision and futures, and the high level constructs and strategies to get there. The hype of multi-cloud is often thought of running applications and infrastructure services seamlessly in several public clouds such as Amazon AWS, Microsoft® Azure and Google Cloud Platform, and linking it to on-premises data centers and private clouds. Hybrid is the new black.

Multicloud connectivity to public cloud providers and on-premises private cloud

Multi-Cloud, on-premises, public and hybrid clouds

And the aspiration of multi-cloud is the right one, when it is truly ready. Gartner® wrote a high level article titled “Why Organizations Choose a Multicloud Strategy“. To take advantage of each individual cloud’s strengths and resiliency in respective geographies make good business sense, but there are many other considerations that cannot be an afterthought. In this blog, we look at a few of them from a data storage perspective.

In the beginning there was … 

For this storage dinosaur, data storage and compute have always coupled as one. In the mainframe DASD days. these 2 were together. Even with the rise of networking architectures and protocols, from IBM SNA, DECnet, Ethernet & TCP/IP, and Token Ring FC-SAN (sorry, this is just a joke), the SANs, the filers to the servers were close together, albeit with a network buffered layer.

A decade ago, when the public clouds started appearing, data storage and compute were mostly inseparable. There was demarcation of public clouds and private clouds. The notion of hybrid clouds meant public clouds and private clouds can intermix with on-premise computing and data storage but in almost all cases, this was confined to a single public cloud provider. Until these public cloud providers realized they were not able to entice the larger enterprises to move their IT out of their on-premises data centers to the cloud convincingly. So, these public cloud providers decided to reverse their strategy and peddled their cloud services back to on-prem. Today, Amazon AWS has Outposts; Microsoft® Azure has Arc; and Google Cloud Platform launched Anthos.

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Intel is still a formidable force

It is easy to kick someone who is down. Bad news have stronger ripple effects than the good ones. Intel® is going through a rough patch, and perhaps the worst one so far. They delayed their 7nm manufacturing process, one which could have given Intel® the breathing room in the CPU war with rival AMD. And this delay has been pushed back to 2021, possibly 2022.

Intel Apple Collaboration and Partnership started in 2005

Their association with Apple® is coming to an end after 15 years, and more security flaws surfaced after the Spectre and Meltdown debacle. Extremetech probably said it best (or worst) last month:

If we look deeper (and I am sure you have), all these negative news were related to their processors. Intel® is much, much more than that.

Their Optane™ storage prowess

I have years of association with the folks at Intel® here in Malaysia dating back 20 years. And I hardly see Intel® beating it own drums when it comes to storage technologies but they are beginning to. The Optane™ revolution in storage, has been a game changer. Optane™ enables the implementation of persistent memory or storage class memory, a performance tier that sits between DRAM and the SSD. The speed and more notable the latency of Optane™ are several times faster than the Enterprise SSDs.

Intel pyramid of tiers of storage medium

If you want to know more about Optane™’s latency and speed, here is a very geeky article from Intel®:

The list of storage vendors who have embedded Intel® Optane™ into their gears is long. Vast Data, StorOne™, NetApp® MAX Data, Pure Storage® DirectMemory Modules, HPE 3PAR and Nimble Storage, Dell Technologies PowerMax, PowerScale, PowerScale and many more, cement Intel® storage prowess with Optane™.

3D Xpoint, the Phase Change Memory technology behind Optane™ was from the joint venture between Intel® and Micron®. That partnership was dissolved in 2019, but it has not diminished the momentum of next generation Optane™. Alder Stream and Barlow Pass are going to be Gen-2 SSD and Persistent Memory DC DIMM respectively. A screenshot of the Optane™ roadmap appeared in Blocks & Files last week.

Intel next generation Optane roadmap

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Persistent Storage could stifle Google Anthos multi-cloud ambitions

To win in the multi-cloud game, you have to be in your competitors’ cloud. Google Cloud has been doing that since they announced Google Anthos just over a year ago. They have been crafting their “assault”, starting with on-premises, and Anthos on AWS. Anthos on Microsoft® Azure is coming, currently in preview mode.

Google CEO Sundar Pichai announcing Google Anthos at Next ’19

BigQuery Omni conversation starter

2 weeks ago, whilst the Google Cloud BigQuery Omni announcement was still under wraps, local Malaysian IT portal Enterprise IT News sent me the embargoed article to seek my views and opinions. I have to admit that I was ignorant about the deeper workings of BigQuery, and haven’t fully gone through the works of Google Anthos as well. So I researched them.

Having done some small works on Qubida (defunct) and Talend several years ago, I have grasped useful data analytics and data enablement concepts, and so BigQuery fitted into my understanding of BigQuery Omni quite well. That triggered my interests to write this blog and meshing the persistent storage conundrum (at least for me it is something to be untangled) to Kubernetes, to GKE (Google Kubernetes Engine), and thus Anthos as well.

For discussion sake, here is an overview of BigQuery Omni.

An overview of Google Cloud BigQuery Omni on multiple cloud providers

My comments and views are in this EITN article “Google Cloud’s BigQuery Omni for Multi-cloud Analytics”.

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Falconstor Software Defined Data Preservation for the Next Generation

Falconstor® Software is gaining momentum. Given its arduous climb back to the fore, it is beginning to soar again.

Tape technology and Digital Data Preservation

I mentioned that long term digital data preservation is a segment within the data lifecycle which has merits and prominence. SNIA® has proved that this is a strong growing market segment through its 2007 and 2017 “100 Year Archive” surveys, respectively. 3 critical challenges of this long, long-term digital data preservation is to keep the archives

  • Accessible
  • Undamaged
  • Usable

For the longest time, tape technology has been the king of the hill for digital data preservation. The technology is cheap, mature, and many enterprises has built their long term strategy around it. And the pulse in the tape technology market is still very healthy.

The challenges of tape remain. Every 5 years or so, companies have to consider moving the data on the existing tape technology to the next generation. It is widely known that LTO can read tapes of the previous 2 generations, and write to it a generation before. The tape transcription process of migrating digital data for the sake of data preservation is bad because it affects the structural integrity and quality of the content of the data.

In my times covering the Oil & Gas subsurface data management, I have seen NOCs (national oil companies) with 500,000 tapes of all generations, from 1/2″ to DDS, DAT to SDLT, 3590 to LTO 1-7. And millions are spent to transcribe these tapes every few years and we have folks like Katalyst DM, Troika and more hovering this landscape for their fill.

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Reap at low tide

[ Note: This article was published on Linkedin more than 6 months ago. Here is the original link to the article ]

[ Update (Apr 13 2020): Amid the COVID-19 pandemic and restricted movement globally,  we can turn our pessimism into an opportunistic one ]

Nature has a way of teaching us. What works and what doesn’t are often hidden in plain sight, but we human are mostly too occupied to notice the things that work.

Why are they not spending?

This news appeared in my LinkedIn feed. It read “Malaysian Banks Don’t Spend Enough on Tech“. It irked me immensely because in a soft economy climate (the low tide), our Malaysian financial institutions should be spending more on technology (reaping the opportunity) to get ahead.

Why are the storks and the egrets in my page photo above waiting and wading in the knee-deep waters? Because at low tide, when the waves ebb, food is exposed to them abundantly. They scurry for shrimps, small crabs, cockles, mussels and more. This is nature’s way.

From the report, the technology spending average among the Malaysian banks is pathetic.

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The negative domino effect on SMEs

When the banks are not spending on technology, the other industries, especially the SMEs (small medium enterprises) follow suit. The “penny pinching” and “tightening purse string” effect permeates across industries, slowly and surely putting the negative effect in tech spending into a volatile spin-cycle.

From a macro-economic point of view, spending slows down. Buying less means lesser demands and effectively, lowering supply, and it rolls on. The law of demand and supply just got dumped into an abyss.

A great opportunity for those who see it

When I was an engineer at Sun Microsystems more than 2 decades ago, I read a comment delivered by one of the executives. It said “When times are bad, those who know will get the best parts“. I took his comment to heart because what he said held true, even until today.

This is the best time, when the country is experiencing an economic downturn. When the competitors are holding back and may be reeling from the negative effects of the economy, the banks are in the best position to grab the best deals. This is the time to gain market share, when the competition is holding back for fear that the economy will become softer.

Furthermore, with the low interest rates across the board, there is no better time than the present to step up the tech spending. Banks should know this very well but I am perplexed.

That is why the Malaysian banks must kick start their tech spending campaign now. And the SMEs will follow, overturning the downturn with demands of spending for the best “parts”. The supply “factories” are fired up again, and will lead to a positive growth to the economy.

Bank Negara RMiT is that one opportunity

One thing which has been looming is Bank Negara, Malaysia’s Central Bank, RMiT (Risk Management in Technology) framework. A new version was released in July 2019, and to me as an outsider, is a great opportunity to grab the best parts. And some of these standards will come into effect in January 2020

Bank Negara is strongly encouraging banks to improve the security and the confidence of the country’s financial industry, and the RMiT framework is really a prod to increase tech spending. Unfortunately, in some of my business interactions with a few of the banks, the feet dragging practice is prevalent.

Nature’s lesson

The best time to have your best pick is at low tide. This is nature’s lesson for us. What are we waiting for?

StorageGRID gets gritty

[ Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies presented at the event. The content of this blog is of my own opinions and views ]

NetApp® presented StorageGRID® Webscale (SGWS) at Storage Field Day 19 last month. It was timely when the general purpose object storage market, in my humble opinion, was getting disillusioned and almost about to deprive itself of the value of what it was supposed to be.

Cheap and deep“, “Race to Zero” were some of the less storied calls I have come across when discussing about object storage, and it was really de-valuing the merits of object storage as vendors touted their superficial glory of being in the IDC Marketscape for Object-based Storage 2019.

Almost every single conversation I had in the past 3 years was either explaining what object storage is or “That is cheap storage right?

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DellEMC Project Nautilus Re-imagine Storage for Streams

[ Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies presented at this event. The content of this blog is of my own opinions and views ]

Cloud computing will have challenges processing data at the outer reach of its tentacles. Edge Computing, as it melds with the Internet of Things (IoT), needs a different approach to data processing and data storage. Data generated at source has to be processed at source, to respond to the event or events which have happened. Cloud Computing, even with 5G networks, has latency that is not sufficient to how an autonomous vehicle react to pedestrians on the road at speed or how a sprinkler system is activated in a fire, or even a fraud detection system to signal money laundering activities as they occur.

Furthermore, not all sensors, devices, and IoT end-points are connected to the cloud at all times. To understand this new way of data processing and data storage, have a look at this video by Jay Kreps, CEO of Confluent for Kafka® to view this new perspective.

Data is continuously and infinitely generated at source, and this data has to be compiled, controlled and consolidated with nanosecond precision. At Storage Field Day 19, an interesting open source project, Pravega, was introduced to the delegates by DellEMC. Pravega is an open source storage framework for streaming data and is part of Project Nautilus.

Rise of  streaming time series Data

Processing data at source has a lot of advantages and this has popularized Time Series analytics. Many time series and streams-based databases such as InfluxDB, TimescaleDB, OpenTSDB have sprouted over the years, along with open source projects such as Apache Kafka®, Apache Flink and Apache Druid.

The data generated at source (end-points, sensors, devices) is serialized, timestamped (as event occurs), continuous and infinite. These are the properties of a time series data stream, and to make sense of the streaming data, new data formats such as Avro, Parquet, Orc pepper the landscape along with the more mature JSON and XML, each with its own strengths and weaknesses.

You can learn more about these data formats in the 2 links below:

DIY is difficult

Many time series projects started as DIY projects in many organizations. And many of them are still DIY projects in production systems as well. They depend on tribal knowledge, and these databases are tied to an unmanaged storage which is not congruent to the properties of streaming data.

At the storage end, the technologies today still rely on the SAN and NAS protocols, and in recent years, S3, with object storage. Block, file and object storage introduce layers of abstraction which may not be a good fit for streaming data.

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Komprise is a Winner

[Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies to be presented at this event. The content of this blog is of my own opinions and views]

I, for one perhaps have seen far too many “file lifecycle and data management” software solutions that involved tiering, hierarchical storage management, ILM or whatever you call them these days. If I do a count, I would have managed or implemented at least 5 to 6 products, including a home grown one.

The whole thing is a very crowded market and I have seen many which have come and gone, and so when the opportunity to have a session with Komprise came at Storage Field Day 19, I did not carry a lot of enthusiasm.

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Open Source and Open Standards open the Future

[Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies to be presented at this event. The content of this blog is of my own opinions and views]

Western Digital dived into Storage Field Day 19 in full force as they did in Storage Field Day 18. A series of high impact presentations, each curated for the diverse requirements of the audience. Several open source initiatives were shared, all open standards to address present inefficiencies and designed and developed for a greater future.

Zoned Storage

One of the initiatives is to increase the efficiencies around SMR and SSD zoning capabilities and removing the complexities and overlaps of both mediums. This is the Zoned Storage initiatives a technical working proposal to the existing NVMe standards. The resulting outcome will give applications in the user space more control on the placement of data blocks on zone aware devices and zoned SSDs, collectively as Zoned Block Device (ZBD). The implementation in the Linux user and kernel space is shown below:

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