Schneider Electric brings out its initial integrated rack with immersed, liquid-cooled IT for data centers

Schneider Electric, alongwith Avnet and Iceotope, announced on Monday  creation its commercially-available integrated rack with chassis-based, immersive liquid cooling. Optimized for compute-intensive applications, the solution combines a high-powered GPU server with Iceotope's liquid cooling technology to increase energy efficiency. 

Avnet integrates the liquid-cooled server with Schneider Electric's NetShelter liquid-cooled enclosure system for simple deployment into data centers or edge computing environments. The system is EcoStruxure Ready since the solution is available with next generation data center management software, EcoStruxure IT Expert, and digital service EcoStruxure Asset Advisor. 

This liquid-cooled solution is ideal for applications such as big data analytics, artificial intelligence, and machine-learning algorithm training development, where high compute demands more energy use. In a recent report published by Gartner, liquid cooling was identified as a technology to watch. 

The parallel-processing power of Graphical Processing Units, known as GPUs, makes them efficient processor for a growing number of applications including AI, big data analytics, data mining, and more. The chips are increasingly power dense with thermal design power ratings reaching 400 watts or more. 

This makes traditional data center air-cooled architectures impractical, or costly and less efficient than liquid-cooled approaches where the server is partially submerged in a dielectric fluid. 

Liquid cooling delivers efficiency removing the need for air conditioning, while offering the same processing power with less energy. It is also silent as it does not include industrial drone from fans and pumps; delivers resilience as all components are in a sealed module that resists dust and smoke; and comes in a compact size to offer smaller and more flexible footprint.

Analyst Henrique Cecci advised data center operators "maximize cooling energy efficiencies by employing modern liquid cooling solutions1." Liquid cooling offers greater efficiency, lower operating costs, smaller footprint, increased reliability, and nearly silent operation despite the high-power density of the GPUs. Avnet, Iceotope, and Schneider Electric plan to expand the offering as demand grows by welcoming other server OEMs into the partnership. 

"Schneider Electric is committed to making data centers more sustainable and liquid cooling is a very compelling approach," said Kevin Brown, CTO and SVP of Innovation, Secure Power, Schneider Electric, who is presenting on liquid cooling at the Gartner conference. "This latest development marks a significant step toward industrializing chassis-based immersion solutions which offer the efficiency and effectiveness of tanks based solutions while providing the compatibility and serviceability of more traditional, 'direct-to-chip' liquid-cooling designs.  Given the growth of compute-intensive applications, we believe this approach is very promising."

HPE, Cray release comprehensive HPC and AI offerings optimized for exascale computing on premises, in the cloud, or as-a-service

Hewlett Packard Enterprise (HPE) announced Thursday that it will deliver comprehensive high-performance computing (HPC) and Artificial Intelligence (AI) portfolio for the exascale era, which is characterized by explosive data growth and new converged workloads such as HPC, AI, and analytics.

The addition of Cray Inc., which HPE recently acquired, bolsters HPE’s HPC and AI solutions to now encompass an end-to-end supercomputing architecture across compute, interconnect, software, storage and services, delivered on premises, hybrid or as-a-Service. Now every enterprise can leverage the same foundational HPC technologies that power the world’s fastest systems, and integrate them into their data centers to unlock insights and fuel new discovery.

Digital transformation is driving new data-intensive workloads and real-time analytics operating at an unprecedented scale. New software, compute, interconnect, and storage capabilities are required for customers to unlock the potential of their data and accelerate innovation. 

HPE delivers solutions for any experience from single, small systems all the way to exascale-class supercomputers with tailored software, interconnect and storage capabilities. This includes solutions for modeling and simulation in weather forecasting, manufacturing and energy sectors, and AI and big data analytics in precision medicine, autonomous vehicles, geospatial imaging and financial services.

SnapLogic harnesses AI to build end-to-end integrations; improve connectivity with Salesforce, Coupa, and Delta Lake by Databricks

SnapLogic introduced a new breakthrough AI capability to help citizen and expert integrators complete integrations faster and more easily, boosting user productivity and enabling IT and development teams to focus on more strategic, high value tasks. 

The new feature, called Pipeline Synthesis, leverages SnapLogic’s machine learning-based engine, Iris AI, to infer user intent and organizational insight to instantly build and suggest new, complete, end-to-end integration pipelines to solve an integration task at hand. 

In addition to the new Pipeline Synthesis feature, the November 2019 release of the SnapLogic Intelligent Integration Platform also includes additional Iris AI enhancements, new Kubernetes support, and enhanced connectivity with Salesforce, Coupa, and Delta Lake by Databricks.

New and enhanced capabilities in this month’s release of the SnapLogic Intelligent Integration Platform advance usability, connectivity, and performance for customers. 

The update will provide an enhanced Mapper AutoLink function that simplifies source-to-target mappings and provides relevance scoring highlighting the accuracy of mappings, improving productivity for less technical users. In addition, the release includes improved algorithms to support the development of pipelines with multiple endpoints. 

Customers can now integrate the deployment of Snaplexes in their Kubernetes-based DevOps processes allowing Snaplexes to be spun up as needed to manage their infrastructure.

Organizations can now designate critical pipelines to be part of automated regression testing. Users will get a report on pipeline behavior before and after a new SnapLogic platform release, giving them the assurances they need to upgrade with ease and confidence. This release adds support for Delta Lake, the open source storage layer created by Databricks, to help data engineers build high quality, reliable data lakes for improved analytics. 

New capabilities to modify API proxies and customize the API developer portal drive productivity gains for API Managers; with enhancements made to some of the more popular Snaps, including Salesforce, Coupa, Snowflake, and PostgreSQL to help drive greater connectivity and value for customers.

The release of the SnapLogic Intelligent Integration Platform is immediately available to all customers.

The World Bee Project adopts Oracle cloud storage and AI analytics tools to enhance goals and innovations

Oracle announced a partnership with The World Bee Project CIC in 2018, offering the use of its cloud storage and AI analytics tools to support the organization’s goals and innovations such as its BeeMark honey certification.

Oracle will be offering cloud computing technology and analytics tools to The World Bee Project to enable it to process data in collaboration with its science partner, the University of Reading, to enable science-based evidence to emerge.

The World Bee Project is a private organization that launches a global honeybee monitoring initiative to inform and implement actions to improve pollinator habitats, create more sustainable ecosystems, and improve food security, nutrition, and livelihoods by establishing a globally coordinated monitoring program for honeybees and eventually for key pollinator groups.

The World Bee Project is a UK Community Interest Company (CIC), designed for social enterprises that want to use their profits and assets for the public good. It is the UK equivalent of a US Benefit Corporation, known as B. Corp. The World Bee Project supports the emerging holistic paradigm where society and the environment are seen as an indivisible whole, and societies and individuals define wellbeing and prosperity.

The aim of the WBP is to create a “world hive network” of remotely monitored honeybee hives and bumble bee nests. This will generate significant new data on the impact of different factors on the health of bees, such as land use, agricultural practices and forage quality. The aim is to gain a deeper understanding of disease, parasites, predator species, and control measures, in part by comparing what’s going on in different parts of the world, where different factors and outcomes can be observed.

This is where the cloud storage and analytics will really come into its own, enabling global storage, access and analysis of the information gathered — and sufficient computing power to really make something of that data, using AI on the big data generated by the world hive network sensors.

So, for the global economy, for the bees themselves, for food producers and food consumers (that’s all of us), it’s great to see this collaboration between a non-profit group, academia and the tech industry to address this issue. It’s also pleasing to see Big Data analytics proving its worth in this way.

The World Bee Project Hive Network remotely collects data from varying environments through interconnected hives equipped with commercially available IoT sensors. The sensors combine colony-acoustics monitoring with other parameters such as brood temperature, humidity, hive weight, and apiary weather conditions. They also monitor and interpret the sound of a bee colony to assess colony behavior, strength and health.

The World Bee Project Hive Network’s multiple local data sources provide a far richer view than any single data source to harness and enable global-scale computation to generate new insights into declining pollinator populations.

After the data has been validated by The World Bee Project database it can be fed into Oracle Cloud, which uses analytics tools including AI and data visualization to provide The World Bee Project with new insights into the relationship between bees and their varying environments. These new insights can be shared with smallholder farmers, scientists, researchers, governments, and other stakeholders.

“The partnership with Oracle will absolutely transform the scene as we can link AI with pollination and agricultural biodiversity,” said Sabiha Malik, founder and executive president of The World Bee Project CIC. “We have the potential to help transform the way the world grows food and to protect the livelihoods of hundreds of millions of smallholder farmers, but we depend entirely on stakeholders such as banks, agritech, insurance companies, and governments to sponsor and invest in our work so that we can begin to step toward fulfilling our mission.”

Oracle is currently looking at funding models to support the expansion of The World Bee Project Hive Network to ensure a global view of the health of bee populations.

SnapLogic extends alliance with Databricks to boost data lake reliability; analyze big data workloads in the cloud

SnapLogic has expanded its partnership with Databricks with new support for Delta Lake, the open source storage layer created by Databricks that brings reliability to traditional data lakes. 

Together, the joint solution helps customers accelerate the integration, transformation, and processing of big data workloads into Delta Lake, increasing data quality and accelerating the time to value of advanced analytics and machine learning initiatives.

Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of existing data lake and is fully compatible with Apache Spark APIs. Delta Lake on Databricks allows users to configure Delta Lake based on their workload patterns and provides optimized layouts and indexes for fast interactive queries.

Delta Lake sits on top of Apache Spark. The format and the compute layer helps to simplify building big data pipelines and increase the overall efficiency of the pipelines.

Organizations are increasingly investing in data lakes to gain actionable insights into their growing data assets. However, the high volume and complexity of data often results in data quality, reliability and performance issues. 

Together, SnapLogic and Databricks are removing these roadblocks by providing a low-code, visual paradigm for data engineers to create and process data pipelines that leverage the full power of Delta Lake — including features like ACID transactions, scalable metadata handling, schema enforcement, and batch and streaming support.

“Databricks and SnapLogic are committed to delivering product innovations that help organizations reduce the time, effort, and skills needed to manage their big data initiatives so they can quickly turn their data into meaningful insights that drive the business forward,” said Craig Stewart, chief technology officer, SnapLogic. “By teaming up with Databricks, we aim to remove the key technical barriers to data lake and big data management so our customers can accelerate their analytics and machine learning initiatives and focus on delivering real business value.”