More than 40 years after arriving in Tucson, computing giant IBM is still churning out innovations in data-storage technology from its labs at the University of Arizona Science and Technology Park.
IBM
IBMNoise is currently quantum computing’s biggest challenge as well as its most significant limitation. IBM is working to reduce that noise in the next few years through various types of quantum error management until true quantum error correction (QEC) is attained.
Here is why reducing noise is so important. A quantum bit (qubit) is the basic unit of information for quantum computers, and the longer a qubit can maintain its quantum state, the more computational operations it can perform. Unfortunately, qubits are very sensitive to environmental noise, which can come from a quantum computer’s control electronics, wiring, cryogenics, other qubits, heat, and even external factors such as cosmic radiation. Noise is problematic because it can cause a qubit’s quantum state to collapse (a condition called decoherence) and thus create errors. An uncorrected error can cascade into an avalanche of errors and destroy an entire computation.
This type of noise originates at the atomic level, and even though it can't be completely eliminated, it can be managed.
Quantum advantage and noise
Despite media hype, there is no documented evidence that current quantum computers are more powerful than classical supercomputers. Even so, there is no question that quantum computers have an indisputable advantage. Most experts believe it's only a matter of time before quantum computing demonstrates its superiority compared to classical supercomputers. When that occurs, quantum computing will have achieved what is commonly referred to as “quantum advantage.”
IBM defines quantum advantage as a significant improvement in quantum algorithm runtime for practical cases over the best classical algorithm. Its blog further states that the algorithm needed to prove quantum advantage must have an efficient representation as quantum circuits, and there should be no classical algorithm capable of simulating those circuits efficiently.
But here’s the dilemma: For quantum computers to achieve quantum advantage, besides improving qubit coherence, gate fidelities, and speed of circuit execution, we must also significantly increase computational qubit counts. But upping the number of qubits also increases noise and qubit errors. Therefore, managing noise and qubit errors is critical to the long-term success of quantum computing.
Although error correction is common in classical computers and in certain types of memory hardware, we can’t use the same techniques in quantum computers because the laws of quantum mechanics make it impossible to clone unknown quantum states.
Quantum error correction (QEC) is a complex engineering and physics problem. And despite its importance and the number of years that have been invested thus far in the search for a solution, quantum error correction remains elusive and still appears to be many years away. Until full error correction becomes available, IBM is researching other error management solutions.
Quantum error management
Quantum error mitigation will fill the gap before Quantum Error Correction achieves practical ... [+]
IBMThe above IBM chart compares the exponential scaling of error-mitigated quantum circuits to the exponential scaling of classical computers. The crossover point is where quantum error mitigation becomes competitive with classical solutions.
IBM has a long history of error correction research, beginning with David DiVincenzo’s investigations in 1996. In 2015, it developed the first system to detect quantum bit flip and phase flip errors. Today, almost every corporate and academic quantum computing program has some form of error correction research in progress because of the importance of quantum error correction.
IBM currently looks at quantum error management through the lens of three methods: error suppression, error mitigation, and error correction. Setting aside error correction for the moment, let’s consider the other two approaches.
Error suppression is one of the earliest and most basic methods of handling errors. It typically modifies a circuit, uses pulses of energy to keep a qubit in its quantum state longer, or directs pulses at idle qubits to undo any unwanted effects caused by neighboring qubits. These types of error suppression are known as dynamic decoupling.
Error mitigation is the method that IBM believes will bridge the gap between today’s error-prone hardware and tomorrow’s fault-tolerant quantum computers. Error mitigation’s interim purpose is to enable early achievement of quantum advantage.
IBM has done more continuous error mitigation research than any other institution. Through that work, IBM has developed multiple approaches to error mitigation, including probabilistic error cancellation (PEC) and zero-noise extrapolation (ZNE).
Effective quantum error correction would eliminate almost all noise-related errors. It is worth noting that QEC exponentially suppresses errors with increasing code size. At any finite code size, errors will always be present. For optimum results, it will be important to pick a code size that suppresses errors just enough for the target application.
But until QEC becomes available, it appears that quantum error mitigation provides the fastest path to quantum advantage.
Dialable error reduction
IBM
IBMIBM recently announced the integration of error suppression and error mitigation into Qiskit Runtime primitives Sampler and Estimator. As beta features, these allow a user to trade speed for fewer errors. IBM's roadmap projects the final release of these features in 2025.
There is overhead associated with compiling, executing, and classical post-processing of error mitigation techniques. The amount of overhead varies depending on the type of error mitigation used. IBM introduced a new simplified option for the primitives called a “resilience level” that allows users to dial in the cost/accuracy tradeoff needed for their work. Sampler and Estimator will automatically apply dynamical decoupling error suppression to circuits at optimization levels 1 through 3. Resilience 0 offers no error mitigation, Resilience 1 is measurement error mitigation, Resilience 2 provides biased error mitigation (via ZNE), and Resilience 3 enables unbiased estimators (via PEC).
Error mitigation will be available on all cloud-accessible IBM systems. As the resilience number increases, so does the cost. Resilience 3 produces the fewest errors but could require 100,000X more computation time.
Dr. Blake Johnson, IBM Quantum Platform Lead, explained the rationale for IBM’s implementation of this option for error mitigation services.
“We have some very advanced users that want to do everything themselves,” Dr. Johnson said. “They don't want us touching their circuits. That’s fine with us, so we make that possible. But we are seeing more and more users who look at a quantum computer like you would look at a toaster. They don’t understand how it works. They just want to push a button and make the right thing happen. So, we decided to enable certain things as defaults if it doesn’t have a sampling overhead and if there isn’t an additional cost to run it.”
Quantum error correction
Thanks to error correction research conducted by the entire quantum computing community, significant progress has been made on QEC over the past decade. Even so, it is likely that years of more research will be required to find a workable solution.
One of the early challenges of quantum error correction was determining if an error had been made without destroying a qubit's quantum state by measuring it. In 1995, Peter Shor developed a breakthrough solution to circumvent the problem. Rather than storing the quantum state in a single qubit, Shor’s system encoded quantum information in a logical qubit distributed across nine physical qubits. The scheme enabled errors to be detected by monitoring the system's parity rather than destroying the quantum state with direct measurements.
IBM is currently investigating many approaches to quantum error correction, including some similar to Shor’s code. This class of error correction code is called quantum Low-Density Parity Check (qLDPC). LDPC is not new. It is used in many classical error correction applications, such as Wi-Fi and 5G.
According to IBM, qLDPC offers the following advantages:
The research opportunities and diverse methods for quantum error correction are too numerous to cover here, but having many options is a good problem to have. If a fault-tolerant quantum computer is ever to be realized, we must find a solution for error correction, and the more options we have, the better our chances.
IBM’s quantum roadmap reflects the complexity of the problem. It shows an error correction solution becoming available sometime beyond 2026. Indeed, it will likely take several years beyond that.
Wrapping up
As quantum hardware continues to improve, there is a high probability that quantum error mitigation, as implemented by IBM's roadmap, will facilitate the early achievement of quantum advantage. Presently, error mitigation has an exponential runtime influenced by how many qubits are needed and the circuit depth. But improvements in speed, qubit fidelity, and error mitigation methods are expected to considerably reduce that overhead.
It is IBM's goal for error mitigation to provide a continuous development path to error-correction. Once QEC is attained, it will enable us to build fault-tolerant quantum machines running millions of qubits in a quantum-centric supercomputing environment. These machines will have the ability to simulate large many-body systems, optimize complex supply chain logistics, create new drugs and materials, model and react to sophisticated financial market behavior, and much more.
Fault-tolerant quantum computers will signal that a new era of quantum-centric scientific investigation has arrived. And with that new capability will come the potential to responsibly change the world.
Analyst notes
Follow Paul Smith-Goodson on Twitter for current information and insights about Quantum, AI, Electromagnetics, and Space
Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys,Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler.
Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movand
Note: Moor Insights & Strategy writers and editors may have contributed to this article.
The MarketWatch News Department was not involved in the creation of this content.
Dec 01, 2022 (The Expresswire) -- As per Market Growth Report, Data Storage market size will be USD million and it is expected to reach USD million by the end of 2027, with a CAGR of % during 2021-2027.
Data Storage Market is expected to reach multi million by 2027, in valuation to 2021, Over the few years the Data Storage Market will reach a magnificent spike in CAGR in terms of revenue. Report is spread across 97 Pages and provides exclusive data, information, vital statistics, trends, and competitive landscape details in this niche sector.
What are the Key Industry Development in Data Storage Market?
Data Storage in this report refers to an Enterprise Storage System as a set of storage elements, including controllers, cables, and (in some instances) host bus adapters, associated with three or more disks. A system may be located outside of or within a server cabinet and the average cost of the disk storage systems does not include infrastructure storage hardware (i.e. switches) and non-bundled storage software.
In the Spanish market, the main Data Storage players include HPE, NetApp, Dell EMC, IBM, Pure Storage, etc. The top five Data Storage players account for approximately 59% of the total market. In terms of type, Hybrid Storage Arrays is the largest segment, with a share over 42%. And in terms of application, the largest application is IT and Telecom, followed by BSFI.
Market Analysis and Insights: Global Data Storage Market
In 2021, the global Data Storage market size will be USD million and it is expected to reach USD million by the end of 2027, with a CAGR of % during 2021-2027.
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Global Data Storage Scope and Market Size
Data Storage market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Data Storage market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2016-2027.
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Which are the prominent Data Storage Market players across the Globe?
● Along with this survey you also get their Product Information Types (123, All-Flash Arrays, Hybrid Storage Arrays, HDD Arrays ), Applications (123, IT and Telecom, BFSI, Healthcare, Education, Manufacturing, Media and Entertainment, Energy and Utility, Retail and e-Commerce, Others), and Specification. Detailed profiles of the Top major players in the industry:123, HPE, NetApp, Dell EMC, IBM, Pure Storage, Hitachi, Fujitsu, Huawei, Western DigitalData Storage Market Effect Factor Analysis.
● Technology Process/Risk Considering Substitute Threat and Technology Progress InData Storage Industry. ● Data Storage Market research contains an in-depth analysis of report complete data on factors influencing demand, growth, opportunities, challenges, and restraints, and Analysis of Pre and Post COVID-19 Market.What Overview Data Storage Market Says?
● This Overview Includes Diligent Analysis of Scope, Types, Application, Sales by region, types and applications. ● Data Storage Market, USD Forecast till Data StorageWhat Is Data Storage Market Competition
● considering Manufacturers, Types and Application? Based on Thorough Research of Key FactorsData Storage Market Manufacturing Cost Analysis
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What are Industry Insights?
The Global Data Storage market is expected to rise at a considerable rate during the forecast period, between 2023 and Data Storage. In 2021, the market is rising at a steady rate and with the expanding adoption of strategies by key players, the market is expected to rise over the projected horizon.
What are the top key players in the Data Storage Market?
● HPE
● NetApp
● Dell EMC
● IBM
● Pure Storage
● Hitachi
● Fujitsu
● Huawei
● Western Digital
and more;
Key Stakeholders:
● Raw material suppliers ● Distributors/traders/wholesalers/suppliers ● Regulatory bodies, including government agencies and NGO ● Commercial research and development institutions ● Importers and exporters ● Government organizations, research organizations, and consulting firms ● Trade associations and industry bodies ● End-use industriesGet a demo PDF of report -https://www.marketgrowthreports.com/enquiry/request-sample/19858062
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Data Storage Market - Competitive and Segmentation Analysis:
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Research Methodology:
Research report world follows a primary and secondary methodology that involves data based on top-down, bottom-up approaches, and validation of the estimated numbers through research. The information used to estimate market size, share, and forecast of various segments-sub segments at the global, country level, regional level is derived from the unique sources and the right stakeholders.
Data Storage Market Growth rate or CAGR exhibited by a market certain forecast period is calculate on the basic types, application, company profile and their impact on the market. Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia, etc. Paid data sources include third-party authentic industry databases.
On the basis of product typethis report displays the production, revenue, price, market share and growth rate of each type, primarily split into:
● All-Flash Arrays
● Hybrid Storage Arrays
● HDD Arrays
On the basis of the end users/applicationsthis report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including:
● IT and Telecom
● BFSI
● Healthcare
● Education
● Manufacturing
● Media and Entertainment
● Energy and Utility
● Retail and e-Commerce
● Others
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Target Audience of Data Storage Market:
● Manufacturer / Potential Investors ● Traders, Distributors, Wholesalers, Retailers, Importers and Exporters. ● Association and government bodies.Data Storage Market - Regional Analysis:
Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Data Storage in these regions, from 2015 to 2027, covering
● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)This Data Storage Market Research/Analysis Report provide Answers to following Questions:
● How Porter's Five Forces model helps you to study Data Storage Market? ● What Was Global Market Status of Data Storage Market? What Was Capacity, Production Value, Cost and PROFIT of Data Storage Market? ● What is the major industry objective of the report? What are the critical discoveries of the report? ● What are the TOP 10 KEY PLAYERS of Data Storage Market? ● What Should Be Entry Strategies, Countermeasures to Economic Impact, and Marketing Channels for Data Storage Industry? ● On what Parameters Data Storage Market research is carried out? ● Which Manufacturing Technology is used for Data Storage? What Developments Are Going On in That Technology? Which Trends Are Causing These Developments? ● Which PLAYERS hold a LION’s SHARE in the Data Storage Market? ● What is the market size and growth rate of Data Storage Market by various segmentation? ● What are the Key Industry Development in Data Storage Market?Get a demo PDF of report -https://www.marketgrowthreports.com/enquiry/request-sample/19858062
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With tables and figures helping analyse worldwide Global Data Storage market trends, this research provides key statistics on the state of the industry and is a valuable source of guidance and direction for companies and individuals interested in the market.
Detailed TOC of Global Data Storage Market Research Report 2023
1 Introduction
1.1 Objective of the Study
1.2 Definition of the Market
1.3 Market Scope
1.3.1 Market Segment by Type, Application and Marketing Channel
1.3.2 Major Regions Covered (North America, Europe, Asia Pacific, Mid East and Africa)
1.4 Years Considered for the Study (2015-2027)
1.5 Currency Considered (U.S. Dollar)
1.6 Stakeholders
2 Key Findings of the Study
3 Market Dynamics
3.1 Driving Factors for this Market
3.2 Factors Challenging the Market
3.3 Opportunities of the Global Data Storage Market (Regions, Growing/Emerging Downstream Market Analysis)
3.4 Technological and Market Developments in the Data Storage Market
3.5 Industry News by Region
3.6 Regulatory Scenario by Region/Country
3.7 Market Investment Scenario Strategic Recommendations Analysis
4 Value Chain of the Data Storage Market
4.1 Value Chain Status
4.2 Upstream Raw Material Analysis
4.3 Midstream Major Company Analysis (by Manufacturing Base, by Product Type)
4.4 Distributors/Traders
4.5 Downstream Major Customer Analysis (by Region)
5 Global Data Storage Market-Segmentation by Type
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6 Global Data Storage Market-Segmentation by Application
7 Global Data Storage Market-Segmentation by Marketing Channel
7.1 Traditional Marketing Channel (Offline)
7.2 Online Channel
8 Competitive Intelligence Company Profiles
9 Global Data Storage Market-Segmentation by Geography
9.1 North America
9.2 Europe
9.3 Asia-Pacific
9.4 Latin America
9.5 Middle East and Africa
10 Future Forecast of the Global Data Storage Market from 2023-2027
10.1 Future Forecast of the Global Data Storage Market from 2023-2027 Segment by Region
10.2 Global Data Storage Production and Growth Rate Forecast by Type (2023-2027)
10.3 Global Data Storage Consumption and Growth Rate Forecast by Application (2023-2027)
11 Appendix
11.1 Methodology
12.2 Research Data Source
Continued;.
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More than 40 years after arriving in Tucson, computing giant IBM is still churning out innovations in data-storage technology from its labs at the University of Arizona Science and Technology Park.
And Big Blue’s Tucson engineers are also keeping its customers’ data safe in the ever-changing, increasingly hazardous world of cyberspace.
One example is the recently rolled out IBM Diamondback Tape Library, a high-capacity, archival tape-storage system designed for organizations needing to securely store hundreds of petabytes of data — each one equal to more than 220,000 DVD movies.
IBM says its Diamondback’s main benefits include low power usage, high-capacity storage at about a quarter of the cost of spinning hard-disk drives.
But its timely selling point involves an inherent ability of removable tape media: to disconnect data from the internet and private networks vulnerable to online attacks.
The ability to physically “air-gap” data can help protect big users against ransomware — when a hacker blocks access to networks or data and demands a ransom to release it — and other cyber threats, IBM says.
Calline Sanchez, IBM vice president in charge of the Tucson storage-system development, said the company worked with some of its “hyperscale” customers — companies like cloud-computing services that store tremendous amounts of data — to help design the Diamondback.
“We decided to really work with our partners, our clients and users and discuss what we want to do from an air-gap perspective, or cyber resiliency perspective,” said Sanchez, a UA alumna who also is IBM’s state executive for Arizona and her native New Mexico.
With data breaches and ransomware attacks now a constant threat, IBM says it’s seeing its big-data customers increasingly turn to tape for data resilience.
“From an air-gap perspective it somewhat detaches itself from the genuine base infrastructure of a data center, so it’s self-sustaining,” said Sanchez. “It’s truly this idea of sustainable block storage of data, where it’s not easily accessible at all, from the outside world.”
Calline Sanchez, IBM Vice President and Tucson site leader, says the company’s latest tape storage system can protect data from hackers by removing it from any network.
While tape data storage was seen as a fading technology years ago as faster hard-disk drive and solid-state “flash” storage advanced, sales of tape have surged amid the seemingly endless growth in data.
Sales of tape media for so-called “Linear Tape Open“ or LTO Ultrium — an industry-standard tape technology provided by a consortium comprised of IBM, Hewlett Packard and Quantum Corp., rose a record 40% in 2021 to 148 exabytes of capacity (an exabyte is equal to about 1000 petabytes, or a billion gigabytes), according to the Silicon Valley-based LTO Program.
LTO tape is arguably the lowest-cost, simplest practice to recover from ransomware attacks, said Phil Goodwin, research vice president at the IT research firm IDC.
“Ransomware and malware are threats that will not go away,” Goodwin said as part of the LTO Program’s sales report. “Magnetic tape is an established, understood and proven technology that can be an invaluable tool for defeating ransomware.”
The IBM Diamondback Tape Library, a high-density archival storage system with removable tape cartridges that are transported and accessed as needed by a robotic assembly.
Sanchez credits tape’s resurgence to its sustainability and energy efficiency, as well as its ability to air-gap against cyber threats.
“It’s lower cost than the other storage media types like diskettes or hard disk drives, as well as flash drives,” she said. “And that’s part of the reason why now tape is feeding primarily the back-end infrastructure of cloud environments.”
Like most of IBM’s data storage systems developed over the past four decades, the Diamondback was developed at the company’s multi-building campus at the UA Tech Park on South Rita Road.
IBM built what is now the UA Tech Park in the early 1980s to house storage systems development and manufacturing facilities that employed some 5,000 people in an initial 10 buildings comprising more than 1.3 million square feet.
As part of a major restructuring in 1988, IBM moved the manufacturing part of the operation and nearly 3,000 jobs to San Jose, California, but kept its storage research and development units going.
The company sold its sprawling campus on South Rita Road to the UA in 1994, but stayed on as a tenant.
Today, its storage development labs are still going strong, with about 1,000 workers spread across more than 600,000 square feet in four buildings.
IBM’s local operation — which last week was awarded the Large Company Innovator of the Year at the Governor’s Celebration of Innovation Awards— generates more than 400 patents annually, Sanchez said.
IBM has about 1,000 workers spread across more than 600,000 square feet in four buildings at the UA Tech Park.
At the Tech Park, IBM develops and tests a range of storage systems and media, including disk, tape and flash systems.
Inside the reliability testing lab at the Tech Park’s 9032 Building, IBM engineers have been conducting final testing on brand-new Diamondback Tape Library systems, which are about the size of a narrow refrigerator, with rows of shelving holding palm-sized tape cartridges.
With a constant hum of clicks and whirs, a robotic shuttle moves back and forth inside the Diamondback cabinet, plucking and mounting barcoded tape cartridges according to a preset program.
Each cartridge can hold 18 terabytes, or 1,000 gigabytes of data, and a full Diamondback packs 1,548 LTO cartridges, for total storage of 27 petabytes that can be up and running within 30 minutes of delivery, said Shawn Nave, an IBM mechanical engineer who helped develop the Diamondback.
A row of Diamondbacks were undergoing testing last week, and like all the products tested in the lab they will be put through their paces.
“As part of this testing, we run it until the wheels fall off, and see what happens,” said Nave, one of many UA alumni at IBM’s local operation.
A nearby building houses labs that subject the IBM hardware to extremes of temperatures and other environmental challenges, Sanchez noted.
As the world continues to generate more and more data, the engineers and scientists at the Tucson-area IBM site will continue to innovate to keep up, said Sanchez, whose 22 years with IBM include a year-long stint in 2008 working for Nick Donofrio, a well-known tech figure who led IBM’s technology and innovation strategies for a decade before retiring in 2008 after 44 years with Big Blue.
Sanchez likens IBM’s storage systems and services to the Wizard of Oz hiding behind his curtain, remaining unseen while making everything happen.
“That is from a back-end infrastructure perspective what IBM provides — we make it easier for these enterprises, because it’s totally easy to consume large amounts of data on these significant systems,” she said.
“Where like right now in our lab, we’re not just talking about petabytes. We’re talking about how to serve exabytes (each 1,000 petabytes), as well as zettabytes (1,000 exabytes).”
Sanchez
“Because we just know in a short period of time, we’re going to have research institutions coming to us and saying, ‘Hey, Calline, we’ve outgrown our two petabytes of research data we have in all U.S. research, universities, we need you to start building based on exabytes or possibly zettabytes.’ And to me, that’s crazy.”
IBM engineers are working to increase data storage and efficiency using artificial intelligence, which essentially programs machines to “think” like humans, but Sanchez doesn’t like that term.
“I like more ‘augmented intelligence,’ for the betterment of humankind, and what is great about working in data storage is you continue to think in that direction,” she said. “Because you’ve got to figure out the physics of how to store an immense amount of data that is being created by people on this Earth and with the devices like this.”
The CHSF Hospital Centre in Corbeil-Essonnes, southeast of the French capital, has been the victim of a computer attack that began late Saturday night.
Security researchers recently probed IBM Cloud’s database-as-a-service infrastructure and found several security issues that granted them access to the internal server used to build database images for customer deployments. The demonstrated attack highlights some common security oversights that can lead to supply chain compromises in cloud infrastructure.
Developed by researchers from security firm Wiz, the attack combined a privilege escalation vulnerability in the IBM Cloud Databases for PostgreSQL service with plaintext credentials scattered around the environment and overly permissive internal network access controls that allowed for lateral movement inside the infrastructure.
Wiz’ audit of the IBM Cloud Databases for PostgreSQL was part of a larger research project that analyzed PostgreSQL deployments across major cloud providers who offer this database engine as part of their managed database-as-a-service solutions. Earlier this year, the Wiz researchers also found and disclosed vulnerabilities in the PostgreSQL implementations of Microsoft Azure and the Google Cloud Platform (GCP).
The open-source PostgreSQL relational database engine has been in development for over 30 years with an emphasis on stability, high-availability and scalability. However, this complex piece of software was not designed with a permission model suitable for multi-tenant cloud environments where database instances need to be isolated from each other and from the underlying infrastructure.
PostgreSQL has powerful features through which administrators can alter the server file system and even execute code through database queries, but these operations are unsafe and need to be restricted in shared cloud environments. Meanwhile, other admin operations such as database replication, creating checkpoints, installing extensions and event triggers need to be available to customers for the service to be functional. That’s why cloud service providers (CSPs) had to come up with workarounds and make modifications to PostgreSQL’s permission model to enable these capabilities even when customers only operate with limited accounts.
While analyzing IBM Cloud’s PostgreSQL implementation, the Wiz researchers looked at the Logical Replication mechanism that’s available to users. This feature was implemented using several database functions, including one called create_subscription that is owned and executed by a database superuser called ibm.
When they inspected the code of this function, the researchers noticed an SQL injection vulnerability caused by improper sanitization of the arguments passed to it. This meant they could pass arbitrary SQL queries to the function, which would then execute those queries as the ibm superuser. The researchers exploited this flaw via the PostgreSQL COPY statement to execute arbitrary commands on the underlying virtual machine that hosted the database instance and opened a reverse shell.
With a shell on the Linux system they started doing some reconnaissance to understand their environment, such as listing running processes, checking active network connections, inspecting the contents of the /etc/passwd files which lists the system’s users and running a port scan on the internal network to discover other servers. The broad port scan caught the attention of the IBM security team who reached out to the Wiz team to ask about their activities.
“After discussing our work and sharing our thoughts with them, they kindly gave us permission to pursue our research and further challenge security boundaries, reflecting the organization's healthy security culture,” the Wiz team said.
The gathered information, such as environment variables, told the researchers they were in a Kubernetes (K8s) pod container and after searching the file system they found a K8s API access token stored locally in a file called /var/run/secrets/kubernetes.io/serviceaccount/token. The API token allowed them to gather more information about the K8s cluster, but it turned out that all the pods were associated with their account and were operating under the same namespace. But this wasn’t a dead end.
K8s is a container orchestration system used for software deployment where containers are usually deployed from images — prebuilt packages that contain all the files needed for a container and its preconfigured services to operate. These images are normally stored on a container registry server, that can be public or private. In the case of IBM Cloud it was a private container registry that required authentication.
The researchers used the API token to read the configurations of the pods in their namespace and found the access key for four different internal container registries in those configuration files. The description of this newly found key in IBM Cloud’s identity and access management (IAM) API suggested it had both read and write privileges to the container registries, which would have given the researchers the ability to overwrite existing images with rogue ones.
However, it turned out that the key description was inaccurate and they could only obtain images. This level of access had security implications, but it did not pose a direct threat to other IBM Cloud customers, so the researchers pushed forward.
Container images can contain a lot of sensitive information that’s used during deployment and later gets deleted, including source code, internal scripts referencing additional services in the infrastructure, as well as credentials needed to access them. Therefore, the researchers decided to obtain all images from the registry service and use an automated tool to scan them for secrets, such as credentials and API tokens.
“In order to comprehensively scan for secrets, we unpacked the images and examined the combination of files that made up each image,” the researchers said. “Container images are based on one or more layers; each may inadvertently include secrets. For example, if a secret exists in one layer but is deleted from the following layer, it would be completely invisible from within the container. Scanning each layer separately may therefore reveal additional secrets.”
The JSON manifest files of container images have a “history” section that lists historical commands that were executed during the build process of every image. In several such files, the researchers found commands that had passwords passed to them as command line arguments. These included passwords for an IBM Cloud internal FTP server and a build artifact repository.
Finally, the researchers tested if they could access those servers from within their container and it turned out that they could. This overly permissive network access combined with the extracted credentials allowed them to overwrite arbitrary files in the build artifact repository that’s used by the automated IBM Cloud build process to create container images. Those images are then used in customer deployments, opening the door to a supply chain attack.
“Our research into IBM Cloud Databases for PostgreSQL reinforced what we learned from other
cloud vendors, that modifications to the PostgreSQL engine effectively introduced new
vulnerabilities to the service,” the researchers said. “These vulnerabilities could have been exploited by a malicious actor as part of an extensive exploit chain culminating in a supply-chain attack on the platform.”
While all of these issues have already been privately reported to and fixed by the IBM Cloud team, they are not unique to IBM. According to the Wiz team, the “scattered secrets” issue is common across all cloud environments.
Automated build and deployment workflows often leave secrets behind in various places such as configuration files, Linux bash history, journal files and so on that developers forget to wipe when deployment is complete. Furthermore, some developers accidentally upload their whole .git and CircleCI configuration files to production servers. Forgotten secrets commonly found by the Wiz team include cloud access keys, passwords, CI/CD credentials and API access tokens.
Another prevalent issue that played a critical role in the IBM Cloud attack is the lack of strict access controls between production servers and internal CI/CD systems. This often allows attackers to move laterally and gain a deeper foothold into an organization’s infrastructure.
Finally, private container registries can provide a wealth of information to attackers that goes beyond credentials. They can reveal information about critical servers inside the infrastructure or can contain code that reveals additional vulnerabilities. Organizations should make sure their container registry solutions enforce proper access controls and scoping, the Wiz team said.
Copyright © 2022 IDG Communications, Inc.
International Business Machines (IBM -0.49%) has emerged as one of the few winners in big tech this year. The stock has surged nearly 7% year to date, compared to a 16% decline for the S&P 500 and much steeper declines for many tech stocks.
It's never a good idea to buy a stock solely because its price is rising, but IBM has a lot more going for it than a buoyant stock price. Here are three reasons to invest in this iconic century-old tech company.
IBM serves large companies and organizations. Some of those client relationships span decades, involving myriad products and services that are deeply embedded in day-to-day operations. A company running on IBM mainframes, like 45 of the top 50 banks, are going to continue to run on IBM mainframes for the foreseeable future.
IBM's cloud services are also pervasive in the largest of organizations. IBM Cloud is used at 94% of Fortune 50 companies, and Red Hat products and solutions are found at more than 94% of Fortune 500 companies. IBM's security products are used at two-thirds of Fortune 500 companies, and the top ten companies in financial services, telecom, automotive, healthcare, and public sector are clients of IBM's consulting arm.
Serving enterprise customers won't fully protect IBM from the impacts of a recession, but it can certainly minimize disruptions. Most of IBM's customers aren't going anywhere. They may look for ways to reduce spending, but many of the products and services IBM provides are mission critical. IBM's customer base will serve as a source of stability even in the most tumultuous of economic environments.
IBM has spent the better part of the last decade remaking itself for the cloud computing era. Legacy businesses have been jettisoned, and the company has repositioned itself as the leading provider of hybrid cloud computing solutions for the enterprise. Throughout this transformation, IBM has remained a solid producer of free cash flow.
For 2022, despite the rumblings in the economy, IBM expects to generate around $10 billion of free cash flow. This cash flow fully supports the dividend, which currently yields about 4.6%. At the current rate, IBM will spend just under $6 billion on dividend payments over the next year.
Investors shouldn't expect any significant dividend increases in the near term, at least until IBM boosts its free cash flow and further reduces its debt from the acquisition of Red Hat. IBM expects its cumulative free cash flow for the three-year period ending in 2024 to be $35 billion, so the company is predicting a meaningful increase in free cash flow over the next couple of years.
IBM is valued at just under $130 billion. With annual free cash flow of $10 billion, the stock trades at a price-to-free-cash-flow ratio of 13.
If you believe that IBM can grow revenue and free cash flow over time, the stock looks like a bargain. IBM's growth profile today looks a lot better than it did a few years ago. The company completed the spin-off of its managed infrastructure services business last year, which got rid of roughly $19 billion of slow-growing, low-margin revenue. IBM can now marshal its resources toward its best opportunities, which include hybrid cloud computing and artificial intelligence.
A recession may make it more difficult for IBM to hit its multi-year targets, but the company is in a good position to weather the storm. Shares of IBM have been going against the tide this year, but it's not too late to buy the stock.
IBM Corp. today debuted a new quantum processor dubbed Osprey that features 433 qubits, more than three times as many as its previous-generation chip.
IBM developed Osprey as part of a long-term research effort focused on developing a large-scale quantum computer. It’s believed that such a system would be capable of performing calculations too complex for even the most advanced conventional supercomputers. Large-scale quantum computers could help advance research in areas such as chemistry, artificial intelligence and logistics.
“The new 433 qubit ‘Osprey’ processor brings us a step closer to the point where quantum computers will be used to tackle previously unsolvable problems,” said IBM Director of Research Darío Gil. “We are continuously scaling up and advancing our quantum technology across hardware, software and classical integration to meet the biggest challenges of our time, in conjunction with our partners and clients worldwide.”
IBM’s new 433-qubit Osprey chip is reportedly based on superconducting transmon qubit technology. The same technology powers IBM’s previous-generation quantum chip, Eagle, which debuted in 2021 and features 127 qubits.
Qubits are the basic building blocks of a quantum computer: they store data and carry out calculations on that data. IBM’s new Osprey chip features qubits made from superconducting materials. Superconducting materials enable electricity to travel from one point to another without generating heat or losing energy.
Osprey uses a specific implementation of superconducting qubits known as transmon qubit technology. The technology, which was invented at Yale University in 2007, is designed to make quantum chips less susceptible to noise. Noise is the term for interference that can cause errors in a quantum chip’s circuits.
Osprey’s qubits don’t carry out calculations on their own, but rather rely on an external qubit control system to manage the process. The system uses microwave pulses to manage the qubits’ configuration. During the development of Osprey, IBM made extensive upgrades to this component of its quantum hardware portfolio.
The previous version of the qubit control system was powered by a field-programmable gate array, or FPGA. An FPGA is a chip that can be fine-tuned for a specific computing task to increase the speed at which it carries out the task. IBM has reportedly replaced the FPGA with an application-specific integrated circuit, a type of chip that can be fine-tuned even more extensively to further increase processing performance.
The instructions that the system generates to coordinate how Osprey’s qubits carry out calculations travel to those qubits via specialized wires. According to IBM, it has developed an improved wire design that requires 70% less space and can be manufactured at a lower cost.
After signals from the qubit control system reach Osprey, each signal must be routed to the relevant qubit within the chip. That task is performed by a component that IBM describes as a multilayer wiring system. It’s directly integrated into the Osprey chip.
IBM first implemented the multilayer wiring system in its previous-generation Eagle quantum processor. In the Eagle processor, the component is implemented as three layers of metal arranged atop one another. The component’s design is intended to reduce interference and thereby lower the risk of qubit errors.
IBM’s efforts to increase the reliability of its quantum chips also encompass software. Alongside Osprey, the company today debuted a new version of Qiskit Runtime, a software platform for creating algorithms that can run on its quantum chips. The new version provides access to error mitigation algorithms that enable developers to trade off qubit performance for increased calculation reliability.
Because they are susceptible to interference, quantum chips like Osprey must be deployed in specialized enclosures cooled to temperatures near absolute zero. IBM today introduced a new version of its quantum chip enclosure called the IBM Quantum System Two that is set to become available by the end of 2023.
The enclosure can hold multiple quantum chips with up to 4,158 qubit between them, according to the company. Moreover, it can accommodate the chips’ qubit control systems. IBM stated that up to three Quantum System Two enclosures can be linked together to create a quantum computing environment with as many as 16,632 qubits.
IBM plans to Strengthen its quantum computing hardware further over the coming years. In 2023, the company intends to introduce a next-generation quantum chip called Condor that will have more than twice as many qubits as Osprey.
Even further down the road, IBM plans to develop quantum chips that can be linked together for performance optimization purposes. The first such system is expected to arrive in 2024. According to IBM, the second chip in the series is set to arrive in 2025 and will provide the ability to create a multichip processor with 4,158 qubits.
IBM Corp. today announced that it’s making more products from its software portfolio available through Amazon Web Services Inc.’s AWS Marketplace.
AWS Marketplace provides access to a catalog of software products from the cloud giant’s partners. Companies can install the products in their AWS environments with less effort than the task would otherwise require. Additionally, companies have access to other offerings besides software, including consulting services and datasets.
IBM in May partnered with AWS to bring more of its applications to the AWS Marketplace. As part of the partnership, IBM has made more than 50 software products available to AWS Marketplace users. Today, the company announced that it will enable customers to purchase four more of its applications through the AWS Marketplace with software-as-a-service pricing.
The four offerings are IBM Envizi ESG Suite, IBM Planning Analytics with Watson, IBM Content Services and IBM App Connect Enterprise. They’re available under a software-as-a-service pricing model, which means that software and infrastructure fees are bundled into a single price.
Envizi ESG Suite, the first of the four products that IBM is bringing to the AWS Marketplace, helps companies measure the performance of their environmental, social and governance initiatives. IBM says that the software can collect more than 500 types of data about a company’s ESG initiatives. It visualizes the data in dashboards to ease analysis.
Planning Analytics with Watson, the second offering that IBM is making available via the AWS Marketplace, is a business planning application. It enables companies to track key metrics such as revenue and forecast how those metrics are likely to change in the future. According to IBM, executives can use the data provided by the application to inform their business decisions.
IBM Content Services, in turn, is a set of tools for managing business content such as documents. It stores files in a centralized repository that users can navigate with the help of a search bar. According to IBM, a built-in data governance tool enables companies to regulate how users access important business records.
The fourth product IBM is making available on a software-as-a-service basis through the AWS Marketplace is IBM App Connect Enterprise. It’s a platform for building integrations that allow applications to share data with one another. A retailer, for example, could use the platform to build an integration that syncs sales data from its store management software to a revenue forecasting application.
Alongside the four software products, IBM is bringing its IBM Z and Cloud Modernization Stack to the AWS Marketplace. The latter offering is designed to help companies modernize mainframe applications. The offering also eases a number of related tasks, such as sending data from a mainframe workload to an application deployed on AWS.
IBM’s software portfolio wasn’t the only focus of the updates the company announced today. The company also debuted a new consulting offering, IBM Consulting Platform Services on AWS, that promises to help enterprises more easily manage their cloud applications. IBM stated that it will use software with artificial intelligence to carry out certain maintenance tasks.
IBM’s new consulting offering and software updates made their debut today at AWS re:Invent 2022 in Las Vegas. During the event, the company also announced enhancements to its partner strategy.
Companies can now buy IBM software products that are listed on the AWS Marketplace from IBM resellers and use AWS committed spend to finance such purchases. Committed spend is the term for a budget that a company has allocated in advance to its AWS environment. Third-party software makers, in turn, can now more easily embed IBM software into their products as well as receive access to technical assistance, sales support and funding from the company.
