F5 Networks, Rakuten Mobile come together to support cloud-native mobile network, prepare for 5G-ready service rollout

F5 Networks announced that it has partnered with Rakuten Mobile, the mobile network subsidiary of Rakuten Group, to support the company’s October launch of the initial fully virtualized, cloud-native mobile network and its future deployment of 5G. The carrier will leverage F5’s network functions virtualization (NFV) capabilities to optimize its new mobile network and accelerate its path to 5G services in 2020.

Through this partnership, Rakuten Mobile, Inc. is collaborating with F5 to scale and evolve their cloud-native network design architecture to increase scalability and flexibility without sacrificing control. 

F5 has provided a full-suite N6/SGi-LAN solution consisting of virtualized CGNAT, SGi Firewall, DNS Transparent Cache, and IP Traffic Optimization Functions to deliver enhanced Mobile Broadband (eMBB) services. 

F5’s NFV capabilities and offerings enabled Rakuten Mobile to simplify and optimize service orchestration; ensure application availability, performance, and security; deliver improved freedom and agility in deployment of services; and enable a higher throughput, low-latency network and allow predictable scaling for services.

Earlier this year, F5 announced several new solutions and enhancements designed to allow service providers to launch 5G services. These offerings enable service providers to maximize the investments in their current 4G networks, while optimizing their infrastructures with the scale to securely deploy emerging 5G.

Rakuten has also been making headlines in Japan with its forays into 5G innovation, in partnership with firms such as Nokia, Altiostar, Cisco, Mavenir, Intel, Qualcomm, Quanta and NEC. The fact that Rakuten, unlike existing telecommunication companies, has no outdated and legacy infrastructure to maintain is a significant advantage. 

Rambus achieves GDDR6 performance at 18 Gbps; aimed at AI, ML, data center, autonomous driving systems that need higher bandwidth memory

Rambus Inc. announced it has achieved 18 Gbps performance with the Rambus GDDR6 Memory PHY. Running at the industry’s fastest data rate of 18 Gbps, the Rambus GDDR6 PHY IP delivers peak performance four-to-five times faster than current DDR4 solutions and continues the company’s longstanding tradition of developing leading-edge products. 

The Rambus GDDR6 PHY pairs with the companion GDDR6 memory controller from the recent acquisition of Northwest Logic to provide a complete and optimized memory subsystem solution.

Increased data usage in applications such as artificial intelligence, machine learning, data center, networking and automotive systems is driving a need for higher bandwidth memory. The coming introduction of high-bandwidth 5G networks will exacerbate this challenge. 

Working closely with memory partners, the Rambus GDDR6 solution gives system designers more options in selecting the memory system that meets both their bandwidth and cost requirements.

Rambus GDDR6 PHY achieves high speed of up to 18 Gbps, delivering a maximum bandwidth of up to 72 GB/s; complete and optimized memory subsystem solution with companion GDDR6 memory controller; offers PCB and package design support – allowing customers to bring their high-speed designs to production; and provides access to Rambus system and SI/PI experts helping ASIC designers to ensure maximized signal and power integrity for devices and systems.

It also features LabStation development environment that enables quick system bring-up, characterization and debug, and supports high-performance applications including networking, data center, ADAS, machine learning and AI.

The Rambus GDDR6 PHY will be fully compliant to the JEDEC GDDR6 (JESD250) standard, supporting up to 16 Gbps per pin, and is available on TSMC 7nm process. The GDDR6 interface supports 2 channels, each with 16 bits for a total data width of 32 bits. 

With speeds up to 16 Gbps per pin, the Rambus GDDR6 PHY will offer a maximum bandwidth of up to 64 GB/s. This PHY will be available in advanced FinFET nodes for leading-edge customer integration. The Rambus system-aware design methodology used for IP Cores delivers a customer focused experience with improved time-to-market and first-time-right quality. 

Rambus offers flexible delivery of IP cores and will work directly with the customer to provide a full system signal and power integrity analysis, creating an optimized chip layout. In the end, the customer receives a hard macro solution with a full suite of test software for quick turn-on, characterization and debug.

Dotscience announces advancements to deploy and monitoring for ML models to unblock AI in enterprises

Dotscience announced on Wednesday new platform advancements that offer the easiest way to deploy and monitor machine Learning models on Kubernetes clusters, making Kubernetes simple and accessible to data scientists. New Dotscience Deploy and Monitor features simplify the act of deploying ML models to Kubernetes and setting up monitoring dashboards for the deployed models with cloud-native tools Prometheus and Grafana, reducing the time spent on these tasks from weeks to seconds. 

Dotscience now also enables hybrid and multi-cloud scenarios where, for example, model training can happen on-prem using an attached Dotscience runner, and models can then be deployed to a Kubernetes cluster in the cloud for inference using a Dotscience Kubernetes deployer. 

Dotscience also announced a joint effort with S&P Global to develop best practices for collaborative, end-to-end ML data and model management that ensure the delivery of business value from AI.

While other solutions on the market aim to solve only specific parts of ML development and operations, requiring further integration work in order to provide end-to-end functionality, Dotscience enables data science and ML teams to own and control the entire model development and operations process, from data ingestion, through training and testing, to deploying straight into a Kubernetes cluster, and monitoring that model in production to understand its behavior as new data flows in. 

Furthermore, alongside the built-in Jupyter environment, Dotscience users can now use any development environment they like by using the Dotscience Python library.

Data science and ML teams can use Dotscience to ingest data, perform data engineering, train and test models and then deploy them to CI for further testing before final deployment to production with a single click, command or API call where the models can then be statistically monitored.

Dotscience’s Deploy gives users the ability to handle both building the ML model into a Docker image and deploying it to a Kubernetes cluster; hand the entire CI/CD responsibility over to existing infrastructure, if preferred, or use lightweight built-ins; and track deployment of the ML model back to the provenance of the model and the data it was trained on to maintain accountability across the entire ML lifecycle.

Dotscience’s statistical monitoring feature allows ML teams to define which metrics they would like to monitor on their deployed models and then bring those metrics straight back into the Dotscience Hub interface where the team first developed the model. This allows ML teams to “own” the health of the model throughout the entire development lifecycle and avoids integrations with other monitoring solutions and costly handovers between teams. 

By enabling data science teams to own the monitoring of their models, Dotscience brings the notion of integrated DevOps teams to ML, eliminating silos, maximizing productivity and minimizing mean time to recovery (MTTR) if there are issues with a model.

“While there are visionaries like S&P in the market who also recognize the need for reproducibility, provenance and enhanced collaboration in the model development phase of the lifecycle, our push to simplify deployment and monitoring of AI/ML is based on the market insight that many businesses are still struggling with deploying their ML models, blocking any business value from AI/ML initiatives,” said Luke Marsden, CEO and founder of Dotscience. 

“In addition, monitoring models in ML-specific ways is not obvious to software-focused DevOps teams. By dramatically simplifying deployment and monitoring of models, Dotscience is making MLOps accessible to every data scientist without forcing them to set up and configure complex and powerful tools like Kubernetes, Prometheus and Grafana from scratch,” Marsden added.

Vault12 introduces personal cryptocurrency security offering, engages friends and family to safeguard crypto assets

Vault12 launched its initial personal cryptocurrency security solution to provide distributed, decentralized backup of crypto assets for individual users. Vault12 uses the principles of Hierarchical Threshold Shamir's Secret Sharing and advanced proprietary technology to enable an individual's network of trusted friends and family, known as Guardians, to safeguard their crypto assets. 

Vault12 is a cryptographic security platform to provide end-to-end management of encrypted shards, ensuring that no one has to manually deal with cryptographic components. To incentivize Guardians to help secure users' Vaults, Guardians will be paid in Ethereum. The company is backed by Winklevoss Capital, True Ventures, Naval Ravikant and Data Collective. 

Cryptocurrency assets are routinely stored in local hardware and software wallets or in centralized online accounts. Unfortunately, these approaches have significant drawbacks and weaknesses. Exchanges are vulnerable to hacks and theft, while wallets are often lost or keys are forgotten by owners, resulting in billions of dollars in lost cryptocurrency that will never be retrieved. 

Designed to be used alongside traditional hardware, software and online wallets, Vault12 helps cryptocurrency owners, ICO investors, professional cryptocurrency traders, and high net worth investors safeguard their assets without storing anything in the cloud.

Instead of leaving recovery phrases or private keys centralized in a single place, with a single person, on a single device or within a single organization, the platform conveniently enables users to store crypto assets in a storage system that is not located on any cloud server, but only on a distributed network of people and devices. 

Vault12 marries decentralized cryptography with a decentralized storage network to form an infrastructure that protects cryptocurrencies with full owner control, complete privacy, reliability, and high availability. Owners of crypto assets can quickly set up digital Vaults that are quantum-resistant and highly resilient to attacks on any part of the cryptostorage infrastructure. Users will be able to access their assets by requesting approval from their Guardians, who will be paid in Ethereum for their services. 

"Safeguarding money is necessary for the crypto economy to flourish," said Cameron Winklevoss of Winklevoss Capital. "Vault12's distributed, decentralized, and server-less approach to security helps reduce friction associated with securing crypto assets. We look forward to seeing the company continue to innovate in the crypto security space." 

"One of the unresolved challenges for the mass adoption of cryptocurrency and the blockchain economy is the continued challenge and burden associated with securing crypto assets," said Max Skibinksy, co-founder and CEO of Vault12. "Previously, to keep our digital money safe, we had to keep our extremely valuable cryptographic backups on pieces of paper and store them in traditional banks. It was ironic. We built Vault12 to be an innovative, convenient solution that replaced this cumbersome process." 

"Security is the lifeblood of industry, commerce and leisure," said Jon Callaghan, co-founder of True Ventures. "As more people use decentralized applications, they will need a way to back up their crypto wallets and exchange accounts. Vault12 provides a simple and natural way to reduce risks and combat the fear of forgetting seed phrases and private keys."

"Today's world relies heavily on our social circle in both our personal lives and our professional lives. That's why we're taking a more social approach to cryptography and entrusting our loved ones to guard our assets," said Blake Comagere, co-founder and COO of Vault12. "Today we're safeguarding crypto. In the future, we plan to safeguard everything from legal documents to house keys and more." 

Druva extends platform with comprehensive protection and automation for cloud workloads; provides support for Slack and Microsoft teams

Druva Inc. announced new capabilities providing coverage for cloud workloads, strategic integrations and automated functionality, to accelerate any enterprises’ journey to the cloud. The updates include support for Slack and Microsoft Teams, new advanced backup, recovery and global policy capabilities for AWS workloads, as well as integrations with ServiceNow, Splunk and Okta. 

The latest enhancements ensure greater control and protection of data residing across these new cloud workloads, while also making it accessible for critical business insights and analytics.

Druva is bringing enterprises a comprehensive and scalable way to seamlessly protect and utilize data in the same place it’s being created. These new features and support continue Druva’s promise to deliver leading technology for protecting and managing data, no matter where it resides - endpoints, data center or cloud workloads.

Customers can now preserve the integrity of communication / conversations on the platform for e-discovery, compliance and legal hold requirements. Added to Druva’s support for Microsoft Office 365, delivers data protection for Teams workloads and enabling admins to seamlessly and quickly recover from scenarios where data gets deleted due to accidental deletion/rogue user or in the event of a ransomware attack.

The new platform offers automated disaster recovery that simplifies setup of disaster recovery (DR) plans within AWS environments with the ability to create cross-account DR plans as well as cross-region support. Additionally, Amazon Relational Database Service (RDS) resources can also now be included as part of DR plans, and users can also automate the creation of production-like environments for Dev/QA purposes with a single click.

Splunk users can integrate with Druva’s protected data and enable a complete visibility, security and analysis across all enterprise and IoT data assets. This is also available via Splunk’s native application. A RESTful API-based integration (or via ServiceNow’s native application) helps reduce IT operational overhead by enabling ServiceNow users to report on IT tickets originating from Druva and get end-to-end visibility across all enterprise data assets.

The offering also assists automated user on-boarding and off-boarding without the need for any on-premises components and mitigate configuration needs with Druva’s pre-configured app on Okta Integration Network. Druva is now also part of the Okta Identity Network.

New SpyCloud offering, Third Party Insight, helps to measure and mitigate supply chain breach risks

SpyCloud launched Tuesday their new Third Party Insight solution to help companies understand risk and remediate exposures to the potential threat of account takeover emanating from supply chain vendors. Businesses can use this tool to evaluate risks presented by vendors, partners or acquisition targets based on several factors that stem from the threat of account takeovers.

Third Party Insight provides SpyCloud customers with a risk ranking (specific to the threat of account takeover) for each third party they work with, plus specific data on executive credentials, potentially infected employees, and the rate of password reuse across exposed data. 

Companies can share this data with partners for free and work with them to remediate exposures, reducing the risk of a breach due to account takeovers in their supply chain.  

Some of the most infamous data breaches occurred after the compromise of a third-party account. Memorably, Target's systems were reportedly compromised in 2013 after an HVAC vendor's credentials were used to access Target's web services for vendors, eventually leading to the propagation of credit card-stealing malware on point of sale systems.

More recently in March 2019, Citrix, which provides virtual private network services to most of the Fortune 1000, fell victim to a breach that emanated from an account takeover attack. Criminals had access to emails, project files, employee information and more over a six-month period before the breach was detected. 

"Your employees are open doors to your network, your data and your intellectual property, but your third-party relationships extend that attack surface even further," explained David Endler, chief product officer and co-founder of SpyCloud. "Our new Third Party Insight solution gives businesses a way to evaluate supply chain risks and work cooperatively with their vendors to mitigate them, in turn strengthening their overall security posture while building goodwill with key partners and suppliers."

"In addition to helping assess how vendors and partners may increase your attack surface, Third Party Insight can also help you understand exposures you may inherit through mergers and acquisitions," said Ted Ross, CEO and co-founder of SpyCloud. "When news of an acquisition leaks to the press, the parties involved become ideal targets for criminals. We can now proactively improve the security posture of these parties ahead of these events."

Deep Analysis releases data on state of the digital process automation market trends

Over the past five years, the digital process automation market was reborn (and renamed) as business process management (BPM) products became lighter, easier, and faster to deploy, according to data released by Deep Analysis, showcasing market trends from 2020 to 2025. Much of this change can be attributed to low-code design/development approaches by the vendor community. 

In parallel, many customers jettisoned large-scale, Lean, and Six Sigma transformation projects and embraced smaller-scoped efforts relying on iterative, agile methodologies for a steady stream of process improvements delivered in weeks rather than months. 

This low-code trend (which actually began with BPM software’s inception) coupled with the debut of robotic process automation (RPA) technology for highly manual, repetitive work has reshaped existing digital process automation market. 

BittWare, Achronix introduce enterprise-class PCIe accelerator product featuring 7nm Speedster7t FPGA

BittWare, a Molex company, has collaborated with Achronix Semiconductor to introduce the S7t-VG6 PCIe accelerator product—a feature-rich PCIe card sporting the new Achronix 7nm Speedster7t FPGA. 

This next generation product offers a range of breakthrough capabilities including low-cost and highly flexible GDDR6 memories that offer HBM-class memory bandwidth, high-performance machine learning processors and a revolutionary 2D network-on-chip for high bandwidth and energy-efficient data movement.

The S7t-VG6 offers a 7nm Achronix FPGA that is optimized for high-speed networking and fast, high-capacity memory access. Featuring a QSFP-DD (double-density) cage, the board supports up to 1x 400GbE or 4x 100GbE using the 56G PAM4-enabled Speedster 7t device. 

An additional QSFP port supports 2x 100GbE, and a 4x OCuLink connector supports NVMe attached storage. Sixteen channels of GDDR6 graphics DRAM handle high-bandwidth memory requirements, providing up to 512GB/s.

The BittWare VectorPath accelerator card is designed for high-performance and high-bandwidth data applications and features 1x400GbE and 2x100GbE interfaces; 8 banks of GDDR6 memory with 4 Tbps aggregate bandwidth; 20 Tbps 2D Network-on-Chip (NoC); 1 bank of DDR4 running at 2666MHz with ECC; PCIe compliance and certification; and 692K 6-input LUTs.

This enterprise-class product leverages BittWare’s extensive experience designing, qualifying, deploying and supporting accelerator cards. Its features include choice of thermal cooling options: passive, active or liquid; comprehensive Board Management Controller (BMC); support for Linux and Windows operating systems; developer toolkit: API, PCIe drivers, application example designs and diagnostic self-test; and option to purchase the S7t pre-integrated as a DELL or HPE server from BittWare TeraBox range.

The initial S7t-VG6 shipments are scheduled to begin by the second quarter of next year. 

INNIO debuts Jenbacher J620, its fast-start 3-megawatt natural gas generator offering for data centers

INNIO launched Tuesday its Jenbacher J620 fast-start natural gas generator for data centers. With data centers consuming about 3 percent of the total energy generated globally, a growing challenge is to deliver that electricity in a more reliable and environmentally sound way.

The Jenbacher J620 fast-start natural gas generators not only deliver significant advantages for data center backup operations, but they also provide benefits when running parallel to the grid and in island mode. With built-in fuel storage from the highly reliable natural gas grid, data center operators avoid limited run times and generator refueling. 

Compared to standby diesel-fueled generators, they also offer emissions reductions of up to 90 percent for nitrous oxide (NOx) and up to 25 percent for carbon dioxide (CO2), giving users the flexibility of longer run times. Together with the generator’s fast transient response, users can monetize what otherwise would be stranded assets.

The Jenbacher J620 fast-start natural gas generator provides full load under 45 seconds, along with the additional benefits that come with the ability to run on a variety of operating modes. It also offers data center customers proven reliability, reduced emissions and an opportunity to monetize stranded assets when providing benefits to the electric grid.

With most of the infrastructure being below ground, the natural gas grid is inherently more reliable than the electric grid for fuel supply to the J620 fast start generator.

With selective catalytic reduction (SCR) emissions technologies, NOx—which is frequently the limiting factor for permitting large-scale data centers—can be further reduced. As net global growth in data center electricity continues, these significant emissions reductions provided by natural gas generation will have increasing value for data center operators.

Lower emissions can provide greater run times, this allows natural gas generators to become assets. As the electric grid decarbonizes with increasing renewables, there is greater need for fast-start resources to provide balancing and ancillary service solutions. 

The Jenbacher J620 fast-start natural gas generator can engage in demand response, curtailable tariffs and/or emergency stand by participation, and avoid coincident peak charges. Add in lower, stable natural gas fuel costs, and it is easy to see how significant money can be made by savvy data center operators working in partnership with energy providers

“Along with the surge in data center electricity demand, the share of renewable energy is also increasing,” said Carlos Lange, president and CEO at INNIO. “Fast-start resources like our new Jenbacher J620 solution can balance and accommodate the instability of the electric grid and give data center operators the opportunity to better monetize assets.”