[ 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 ]
“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?”
[ 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 ]
A funny photo (below) came up on my Facebook feed a couple of weeks back. In an honest way, it depicted how a developer would think (or the lack of thinking) about the storage infrastructure designs and models for the applications and workloads. This also reminded me of how DBAs used to diss storage engineers. “I don’t care about storage, as long as it is RAID 10“. That was aeons ago 😉
The world of developers and the world of infrastructure people are vastly different. Since cloud computing birthed, both worlds have collided and programmable infrastructure-as-code (IAC) have become part and parcel of cloud native applications. Of course, there is no denying that there is friction.
Containerized applications are quickly defining the cloud native applications landscape. The container orchestration machinery has one dominant engine – Kubernetes.
In the world of software development and delivery, DevOps has taken a liking to containers. Containers make it easier to host and manage life-cycle of web applications inside the portable environment. It packages up application code other dependencies into building blocks to deliver consistency, efficiency, and productivity. To scale to a multi-applications, multi-cloud with th0usands and even tens of thousands of microservices in containers, the Kubernetes factor comes into play. Kubernetes handles tasks like auto-scaling, rolling deployment, computer resource, volume storage and much, much more, and it is designed to run on bare metal, in the data center, public cloud or even a hybrid cloud.
[ 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.
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:
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.
[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]
This blog was not intended because it was not in my plans to write it. But a string of events happened in the Storage Field Day 19 week and I have the fodder to share my thoughts. Hadoop is indeed dead.
Warning: There are Lord of the Rings references in this blog. You might want to do some research. 😉
Storage metrics never happened
The fellowship of Arjan Timmerman, Keiran Shelden, Brian Gold (Pure Storage) and myself started at the office of Pure Storage in downtown Mountain View, much like Frodo Baggins, Samwise Gamgee, Peregrine Took and Meriadoc Brandybuck forging their journey vows at Rivendell. The podcast was supposed to be on the topic of storage metrics but was unanimously swung to talk about Hadoop under the stewardship of Mr. Stephen Foskett, our host of Tech Field Day. I saw Stephen as Elrond Half-elven, the Lord of Rivendell, moderating the podcast as he would have in the plans of decimating the One Ring in Mount Doom.
So there we were talking about Hadoop, or maybe Sauron, or both.
The photo of the Oliphaunt below seemed apt to describe the industry attacks on Hadoop.
In 2020, the intensity on the topic of Artificial Intelligence will further escalate.
One news which came out last week terrified me. The Sarawak courts want to apply Artificial Intelligence to mete judgment and punishment, perhaps on a small scale.
It is from one of my FreeNAS customers daily security run logs, emailed to our support@katanalogic.com alias. It is attempting a brute force attack trying to crack the authentication barrier via the exposed SSH port.
Just days after the installation was completed months ago, a bot has been doing IP port scans on our system, and found the SSH port open. (We used it for remote support). It has been trying every since, and we have been observing the source IP addresses.
The new Ransomware attack vector
This is not surprising to me. Ransomware has become more sophisticated and more damaging than ever because the monetary returns from the ransomware are far more effective and lucrative than other cybersecurity threats so far. And the easiest preys are the weakest link in the People, Process and Technology chain. Phishing breaches through social engineering, emails are the most common attack vectors, but there are vhishing (via voicemail) and smshing (via SMS) out there too. Of course, we do not discount other attack vectors such as mal-advertising sites, or exploits and so on. Anything to deliver the ransomware payload.
[Disclosure: I am 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 will be covered by GestaltIT, the organizer and I am 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]
This is NOT an advertisement for coloured balls.
This is the license to brag for the vendors in the next 2 weeks or so, as we approach the 2020 new year. This, of course, is the latest 2019 IDC Marketscape for Object-based Storage, released last week.
My object storage mentions
I have written extensively about Object Storage since 2011. With different angles and perspectives, here are some of them:
The thought of it has been on my mind since Commvault GO 2019. It was sparked when Don Foster, VP of Storage Solutions of Commvault answered a question posted by one of the analysts. What he said made a connection, as I was searching for the better insights to how Commvault and Hedvig would end up to be together.
Data Deluge is a swamp thing now
Several years ago, I heard Stephen Brobst, CTO of Teradata brought up the term “Data Swamp“. It was the anti- part of the Data Lakes, and this was back when Data Lakes and Hadoop were all the rage. His comments were raw, honest and it was leading to the truth out there.
[Disclosure: I was invited by Commvault as a Media person and Social Ambassador to their Commvault GO 2019 Conference and also a Tech Field Day eXtra delegate from Oct 13-17, 2019 in the Denver CO, USA. My expenses, travel, accommodation and conference fees were covered by Commvault, 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]
The waltz across the Commvault-Hedvig mine field will not be easy. Commvault will have a lot of open discussions about their acquisition of Hedvig and how Hedvig “primary storage platform” will fit into a “secondary storage framework” of Commvault. The outcome of this consummation is yet to appear as a structured form. The storyline will eventually form as Commvault’s diligence to define their strategy moving forward.
A lot of excitement and buzz were generated around the metallic, the Commvault venture into Software-as-a-Service (SaaS). The SaaS solution is targeted at the mid-market for organizations with 500-2500 staff count. Its simplicity and pricing were the 2 things which gave me a good feeling all over. There is even a 45-day trial for metallic.
Getting Brainy
My Day 2 itinerary was more specific because my agenda for this trip was to seek answers to the realization of Commvault-Hedvig.
Commvault took the distinction of using the vision of a DataBrain (#databrain) to define their strategy. From the picture below, the left and right hemisphere of the DataBrain forms the Storage Management piece on the left and Data Management on the right.
The Oil and Gas industry, especially in the upstream Exploration and Production (EP) sector, has been enjoying a renewed vigour in the past few years. I have kept in touch with the developments of the EP side because I always have a soft spot for the industry. I have engaged in infrastructure and solutions in the petrotechnical side in my days at Sun Microsystems back in the late 90s. The engagements with EP intensified in my first stint at NetApp, wearing the regional Oil & Gas consulting engineer here in South Asia for almost 6 years. Then, with Interica in 2014, I was dealing with subsurface data and seismic interpretation technology. EP is certainly an exciting sector to cover because there are so much technical work involved and the technologies, especially the non-IT, are breath taking.
I have been an annual registrant to the Digital Energy Journal events since 2013, except last year, and I have always enjoyed their newsletter. This week I attended Digital Energy 2-day conference again, and I was taken in by the exciting times in EP. Here are a few of my views and trends observation in this data renaissance.
Almost every single conversation I had in the past 3 years was either explaining what object storage is or “That is cheap storage right?”
