• Developers can save a lot of time and money by using pre-trained foundation models instead of having to start from scratch when training a language model.
• The first is a generative LLM for information extraction, open-ended question and answer, classification, text generation, and summarization.

Amazon Web Services Inc. has recently expanded its reach into artificial intelligence software development by releasing several new tools for generative AI training and deployment on its cloud platform.

The business described new services in a post on the AWS Machine Learning blog, including the capacity to build and train foundation models, which are extensive, pre-trained language models that lay the groundwork for particular natural language processing tasks.

Deep learning techniques are generally used to train foundation models on enormous volumes of text data, enabling them to become adept at understanding the subtleties of human language and produce content nearly indistinguishable from that written by humans.

When training a language model, developers can save time and money using pre-trained foundation models instead of starting from scratch. A foundation model for text generation, sentiment analysis, and language translation is the Generative Pre-trained Transformer (GPT) from OpenAI LLC.

LLM Choices

Bedrock’s brand-new service makes foundation models from various sources accessible through an API. The Jurassic-2 multilingual large language models from AI21 Labs Ltd., which produce text in Spanish, French, German, Portuguese, Italian, and Dutch, and Anthropic’s PBC’s Claude LLM, a conversational and text processing system that follows moral AI system training principles are included. Users can use the API to access Stability AI Ltd. and Amazon LLMs.

According to Swami Sivasubramanian, Vice President of database, analytics, and machine learning at AWS, foundation models are pre-trained at the internet scale. They can therefore be customized with comparatively little additional training. He used the example of a fashion retailer’s content marketing manager, who could give Bedrock as few as 20 examples of effective taglines from past campaign examples with relevant product descriptions. Bedrock will then automatically generate effective social media posts, display ad images, and web copy for the new products.

In addition to the Bedrock announcement, AWS is releasing two new Titan large language models. The first is a generative LLM for information extraction, open-ended question and answer, classification, text generation, and summarization. The second LLM converts text prompts into numerical representations, including the meaning of the text and helps build contextual responses beyond paraphrasing.

No mention of OpenAI, in which Microsoft Corp. is a significant investor, was made in the announcement. Still, given the market’s demand for substantial language models, this shouldn’t be a problem for Amazon.

Although AWS is behind Microsoft and Google LLC in bringing its LLM to market, Kandaswamy argued that this shouldn’t be considered a competitive disadvantage. He said, “I don’t think anyone is so behind that they have to play catchup. It might appear that there is a big race, but the customers we speak with, other than very early adopters, have no idea what to do with it.”

Hardware Boost

Additionally, AWS is upgrading its hardware to provide training and inference on its cloud. New, network-optimized EC2 Trn1n instances now offer 1,600 gigabits per second of network bandwidth, or about a 20% performance increase, and feature the company’s exclusive Trainium and Inferentia2 processors. Additionally, the business’s Inf2 instances, which use Inferentia2 for inferencing of massively multi-parameter generative AI applications, are now generally available.

CodeWhisperer, an AI coding companion that uses a foundation model to produce code suggestions in real-time based on previous code and natural language comments in an integrated development environment, is another product whose availability has been announced. The tool is accessible from some IDEs and supports Python, Java, JavaScript, TypeScript, C#, and ten other languages.

Sivasubramanian wrote, “Developers can simply tell CodeWhisperer to do a task, such as ‘parse a CSV string of songs’ and ask it to return a structured list based on values such as artist, title and highest chart rank.” CodeWhisperer produces “an entire function that parses the string and returns the list as specified.” He said that developers who used the preview version reported improvement of 57% in speed with a 27% higher success rate.

As many players attempt to capitalize on the success of proofs of a concept like ChatGPT, the LLM landscape will likely remain dispersed and chaotic for the foreseeable future. As Google’s Natural Language API has in speech recognition, it’s unlikely that any one model will come to dominate the market, according to Kandaswamy.

He said, “Just because a model is good at one thing doesn’t mean it’s going to be good with everything. It’s possible over two or three years everybody will offer everybody else’s model. There will be more blending and cross-technology relationships.”

• With Charmed Kubeflow on AWS, users can now quickly launch and manage their machine learning workloads.
• In 2022, 35% of organizations were expected to adopt AI, according to IBM’s Global AI Adoption Index.

Canonical Ltd., an Ubuntu software provider, released its machine learning operations toolset Charmed Kubeflow on Amazon Web Services Inc.’s cloud marketplace.

Charmed Kubeflow is available as a software application on AWS, simplifying the deployment and management of machine learning workloads for businesses. The software is an enterprise-grade variant of Kubeflow, an open-source MLOps toolkit designed to work with Kubernetes, the ubiquitous container orchestration software for application containers. It provides various utilities that make operating artificial intelligence on Kubernetes simpler.

Canonical says Charmed Kubeflow on AWS helps enterprises experiment with machine learning processes. It occurs when an increasing number of organizations demonstrate an outsized interest in artificial intelligence and machine learning. According to IBM Corporation’s Global AI Adoption Index, 35% of businesses will adopt AI in 2022. With the proliferation of generative AI initiatives such as ChatGPT, interest in the technology is proliferating.

Charmed Kubeflow on AWS, according to Canonical, is designed for businesses looking to launch their AI and machine learning initiatives because it is simple to deploy and offers unlimited computing power to experiment without limitations.

Charmed Kubeflow creates a trustworthy application layer for model development, iteration, and production deployment by automating machine learning workflows. Additionally, it offers complete visibility into those workloads so teams can evaluate any difficulties and precisely plan their infrastructure expansion needs.

Users can deploy their models on end devices after the complete experimental phase. Simultaneously, Charmed Kubeflow will guard against cyberattacks with frequent scanning, patching, and updates to the most recent version of the machine learning libraries in use. Users may move artifacts from the Charmed Kubeflow appliance to an AWS or data center deployment for production-grade deployments.

According to Aaron Whitehouse, senior director of public cloud enablement at Canonical, Charmed Kubeflow is the best platform for businesses looking to experiment with machine learning for the first time. He said, “The Charmed Kubeflow appliance on AWS gives companies a great way to test out machine learning possibilities quickly and easily, with a clear pathway to a scalable hybrid/multi-cloud deployment if those pilot projects are successful.”

A fully managed version of Charmed Kubeflow on AWS is now accessible through the AWS Marketplace for businesses needing infrastructure support.

• The new platform is composed of composable, standardized building blocks that can be configured for various software-defined storage requirements, including switches, commodity storage, and compute nodes.
• The brand-new GreenLake for Block Storage is touted as the first scale-out, disaggregated block storage to offer a 100% data availability guarantee.

In addition to announcing new disaster and backup recovery data services with uptime guarantees, Hewlett Packard Enterprise Co. recently launched an offering of hybrid file and block storage which will be available on-premises with as-a-service pricing.

The company’s two-year-old HPE Alletra Storage platform, which aims to provide on-premises storage with cloud-like management, is the foundation for the new file and block offerings.

Alletra Storage MP is the new modular storage solution that scales independently and supports block and file stores on the same hardware.

No matter the workload or storage protocol, the company said that a single cloud platform is used to deploy, manage, and orchestrate data and storage services.

The new platform comprises composable, standardized building blocks that can be configured for various software-defined storage requirements, including switches, commodity storage, and compute nodes. The hardware will be offered as-a-service through HPE’s GreenLake portfolio, enabling customers to manage on-premises equipment like a cloud service.

Dave Vellante, the Chief Analyst at the market research firm Wikibon, said, “HPE has declared 2023 the year of storage. This is a positive in that a focus on storage could bring about a mix of higher gross-margin business.”

High-Speed File Storage

GreenLake for File Storage is a service that manages workloads having intense data with a capacity of hundreds of gigabytes per second. The service, which combines flash storage from Vast Data Inc. and GreenLake cloud management, is based on a disaggregated, shared-everything, modular architecture created for the exabyte scale, according to HPE.

The newly-launched GreenLake for Block Storage has been named as the first scale-out, disaggregated block storage that guarantees 100% data availability. In addition to being optimized for mixed workloads, HPE offers a better price/performance ratio than previous storage platforms.

According to Simon Watkins, Senior Manager of worldwide product marketing for HPE storage and cloud data services, a user of the company’s 3PAR 7000/8000 storage array can switch to GreenLake for Block Storage and get comparable performance for half the cost, 66% better price/performance, and a 100% availability guarantee with cloud-like management.

Cloud Experience On-Premises

The latest offering “brings the speed and agility of the cloud experience to your on-prem storage,” Watkins wrote. “HPE GreenLake for Block Storage simplifies operations across the lifecycle — from rapid deployment to automated provisioning to invisible upgrades.”

With GreenLake for Block Storage requiring a monthly subscription fee, Alletra Storage MP will be sold on a capital expenditure basis.

Backup, recovery, and disaster recovery are now all supported by GreenLake in a unified manner. Using the global cloud platform from HPE, GreenLake for Disaster Recovery offers continuous data protection across numerous virtual machines in a unified, automated manner.

By utilizing unified management and a single data catalog for workloads running on private and public clouds, GreenLake for Backup and Recovery secures on-premises and cloud workloads. Additionally, it offers entirely as a service orchestration based on policy and billing based on consumption.

Although HPE has no on-premises alternative to S3 object storage of Amazon Web Services Inc., HPE is reportedly close to launching one.

HPE has historically squeezed storage R and amp;D and had to catch up through acquisitions, according to Vellante. Nevertheless, these updates are a positive sign that the company is getting the best out of homegrown and outside technologies. He said, “While many of those acquisitions have paid off, Antonio Neri is setting a course better balancing organic investments, partnering and acquisition. This announcement contains all three, with HPE storage OS intellectual property, the VAST file system and Infosight AIOps from Nimble.”

• AWS Supply Chain includes logistics models that automatically arrange inventory records in a unified format, facilitating analysis to address the problem.

AWS Supply Chain, a cloud-based inventory monitoring and forecasting application, was made generally available by Amazon Web Services Inc. recently. It was first introduced at the cloud giant’s re:Invent conference in December.

Retailers must prevent scenarios where a store lacks inventory to satisfy customer demand. They must also watch out that store owners don’t buy more of a particular item than is required. In some cases, excess inventory must be thrown away, which can reduce a retailer’s profit margins.

AWS Supply Chain is designed in such a way that it helps companies avoid such issues. This cloud-based application can map the locations of a retailer’s stores, logistics facilities, and other distribution centers. When you click on a facility, a panel that displays the likelihood of product shortages or overstocking appears.

AWS Supply Chain gathers inventory information from a retailer’s logistics applications to track product availability in the background. Records are frequently kept in multiple formats by these applications. AWS Supply Chain includes ML models that automatically arrange inventory records in a unified format, facilitating analysis to address the problem.

AWS claims the models also produce a data lake to store the gathered data. They can identify supply chain problems and produce remediation recommendations using that data lake.

The app can identify a nearby logistics hub where a product is in stock if a store is about to run out. It occasionally generates not just one but several recommendations for resolving supply chain problems. The application ranks the recommendations to assist supply chain teams in choosing the best course of action.

In a blog post, Danilo Poccia, the Chief Evangelist for AWS in Europe, the Middle East, and Africa, said, “Recommendation options are scored by the percentage of risk resolved, the distance between facilities, and the sustainability impact. Supply chain managers can also drill down to review the impact each option will have on other distribution centers across the network.”

In addition to assisting retailers with inventory issues, AWS Supply Chain can forecast future product availability. It has a tool for forecasting customer demand based on previous sales records and other information. A retailer can use the application’s forecasts to determine whether it has enough inventory to meet future demand and place additional orders as needed.

AWS Supply Chain is now generally available and includes several improvements that weren’t present in the preview version.

The company has facilitated the application’s integration with SAP SE’s S/4HANA enterprise resource planning system. S/4HANA is used by many businesses to store inventory information that AWS Supply Chain can use to monitor product availability. Additionally, the application is getting interface upgrades and an automation feature to help users prepare their data more quickly.

• Amazon Web Services, Inc. has announced call analytics for the Amazon Chime software development kit, making real-time audio call insights easier and cheaper to gather.
• Amazon Chime SDK is a collection of components for adding a message, audio, video, and screen-sharing features to online and mobile apps.

Amazon Web Services Inc. recently said it would enable call analytics for the Amazon Chime software development kit, making collecting insights from real-time audio calls more accessible and less expensive.

According to the firm, Amazon Chime SDK call analytics helps developers construct real-time call transcriptions, analyze speech tone, and search for specific speakers. AWS is also enhancing the Amazon Chime SDK section of the AWS Management Console to facilitate incorporating these new features into audio apps.

Amazon Chime SDK is a collection of components for adding message, audio, video, and screen-sharing features to online and mobile apps in real-time. For instance, developers may utilize it to integrate video into a health app, allowing consumers to initiate a video conversation with their doctor straight through the app.

Sébastien Stormacq, Amazon’s principal developer advocate, stated that there are instances in which customers may wish to record and analyze calls conducted through their audio apps. The new voice analytics capability is intended to produce real-time insights based on these calls by extracting emotion from speech cues to detect displeasure and impatience. It operates by analyzing lexical and linguistic information, i.e., what was said, in conjunction with acoustic and tone information, i.e., how it was said.

According to Stormacq, this speech tone analytics will be provided to the customer’s chosen data lake, allowing them to develop dashboards capable of visualizing this data.

Amazon illustrated how this might operate in the financial business, where trading room supervisors frequently record all talks for regulatory purposes. Stormacq stated that voice tone analysis would assist supervisors in monitoring for risk and compliance. In addition, the insights can help traders in increasing their efficiency.

Healthcare, the public sector, telecommunications, and insurance are some businesses that might benefit from voice analysis.

The new speaker search function is intended to discover and identify call participants. Based on a database of known voices, it can identify particular speakers after hearing only a few seconds of their speech. This, according to Stormacq, can assist with duties such as accelerating caller lookup and enhancing call transcripts with identity identification.

Amazon has upgraded the AWS Management Console to make it simpler for developers to utilize these new features. To evaluate a call, developers may simply select the AWS artificial intelligence service, such as voice analytics, Amazon Transcribe, or Amazon Transcribe Call Analytics.

To view these insights, customers may choose Amazon QuickSight or Tableau, whose dashboards can then be incorporated into various apps, wikis, and portals, according to Amazon. Developers may obtain pre-built dashboards as AWS CloudFormation templates rather than developing their own.

Finally, call analytics may be used to produce real-time alerts by publishing specified events to Amazon EventBridge, which then forwards these notifications to the user’s AWS account or any supported third-party application.

Constellation Research Inc.’s Liz Miller told a leading media house that developers would embrace the new call analytics features in Chime since speech and emotion data of this type is essential for training new AI and machine learning models.

Liz Miller said, “This latest SDK gives Chime and AWS customers exactly what they need to turn voice into action. While AI and ML have been announced by almost every major contact center provider, the interesting part of the AWS announcement is that this is really about providing teams building tomorrow’s experiences with the developer toolkits they need to accelerate time to value.”

Amazon stated that Amazon Chime SDK call analytics fees will be usage-based, with customers being charged per minute of audio data examined. Amazon Chime SDK call analytics are presently available in Asia Pacific (Singapore), the US East (Ohio, N. Virginia), and Europe (Frankfurt) regions of AWS, with additional areas to be added in the future.

• With USD 20 million in additional funding, Cado Security intends to expand internationally while accelerating its sales and marketing efforts.
• Both the Microsoft Azure Marketplace and the AWS Marketplace sell Cado Security. Riot Games Inc., Sandia National Laboratories, J Sainsbury Plc, Sophos Ltd., and Wyndham Hotels and amp; Resorts Inc. are a few notable clients.

Cado Security Ltd., a startup developing a cloud forensics and incident response platform, recently announced that it has raised USD 20 million in new funding for product development and further global expansion.

Regarding incident response in the cloud, Cado Security, founded in 2020, positions itself as providing forensic-level details without forensic-level effort. The company’s platform supports complex multi-cloud environments, systems, and regions while leveraging the cloud’s scale, speed, and automation to speed up forensics and incident response.

Compared to what previously took days, Cado users can analyze data in minutes with forensic-level detail to understand the full impact of cloud incidents. The platform automates data collection and examines hundreds of data sources, including disk, memory, and logs from cloud providers.

According to the company, the platform automatically surfaces critical incident details, such as the root cause, compromised roles and assets, and a full timeline of events. It also supports one or more concurrent investigations at once.

Both the Microsoft Azure Marketplace and the AWS Marketplace sell Cado Security. Riot Games Inc., Sandia National Laboratories, Sophos Ltd., J Sainsbury Plc, and Wyndham Hotels and amp; Resorts Inc. are a few notable clients.

Co-founder and chief executive of Cado Security, James Campbell, said in a statement, “As a platform purpose-built for the cloud, we are providing the solutions needed so that security teams can drastically speed up incident response in the cloud. Nearly half of today’s breaches are cloud-based, and with more than 60% of corporate data currently stored in the cloud, it’s more important than ever to provide cutting-edge solutions that enable organizations to appropriately handle this increasing risk in cloud environments.”

Eurazeo S.A. and Ten Eleven Ventures LLC took the lead in the Series B round. Cado Security has raised USD 31.5 million in total, including the latest round. Post investors like Blossom Capital LLP and CyLon Ventures Ltd. invested again.

• The new partnership will allow developers to deploy neural networks on SageMaker in just a few clicks.
• Amazon SageMaker and AWS-designed chips will let the team and larger machine learning community turn the latest research to reproducible models that anyone can build on.

Hugging Face Inc., the operator of a well-known platform that hosts machine learning models, is collaborating with Amazon Web Services Inc. to streamline the development of its artificial intelligence projects.

There was an existing collaboration going on since early 2021 which got expanded when the companies announced the partnership on February 21, 2023.

Adam Selipsky, AWS Chief Executive Officer, said, “Generative AI has the potential to transform entire industries, but its cost and the required expertise puts the technology out of reach for all but a select few companies. Hugging Face and AWS are making it easier for customers to access popular machine learning models to create their own generative AI applications with the highest performance and lowest costs.”

New York-based Hugging Face has received over USD 160 million in a recent funding round. It operates a platform that resembles GitHub, which helps developers to host open-source AI models plus technical assets such as training datasets. It allows storing code for over 100,000 neural networks.

Additionally, Hugging Face will use AWS as its preferred public cloud in accordance with the new collaboration. The business is also launching a new integration with the machine learning platform Amazon SageMaker. Developers can use the platform’s more than six cloud services to train, deploy, and create AI models.

With just a few clicks, developers will be able to deploy neural networks hosted by Hugging Face on SageMaker thanks to the new integration. After uploading an AI model in SageMaker, it can be trained by using AWS Titanium chips-powered cloud instances. The chips are curated exclusively for AI training tasks.

Neural networks deployed from Hugging Face to AWS work with many types of cloud instances, including the ones powered by AWS Inferentia accelerator series. These are basically the chips optimized to perform inference, or the tasks of running AI models right after the training phase gets completed.

Clement Delangue, CEO of Hugging Face, said, “The future of AI is here, but it’s not evenly distributed. Amazon SageMaker and AWS-designed chips will enable our team and the larger machine learning community to convert the latest research into openly reproducible models that anyone can build on.”

It adds essence to Hugging Face AWS Deep Learning Containers that the company already offers to developers as a part of the partnership. The containers make Hugging Face’s AI models available in prepackaged format which is easy to deploy in public cloud environments.

• Uber believes that the new cloud deal will help it channelize the resources toward strategic initiatives and core strengths while the company continues to expand and explore new markets.
• Uber deal is significant for both Google Cloud and Oracle as they compete against their cloud infrastructure market rivals, Microsoft Corp. and Amazon Web Services.

Uber Technologies Inc., a ride-hailing company, announced its multicloud strategy, the latest seven-year strategic cloud collaboration with Oracle Corp. With this development, Uber will shift a major chunk of its crucial workloads to Oracle Cloud Infrastructure.

Meanwhile, the company also disclosed expanding its partnership with Google Cloud, its existing partner. Uber mentioned it has been working with Google to “reimagine the customer experience for Uber users, drivers and merchants and modernize its cloud infrastructure.”

Uber believes that the new cloud deals will help it channelize the resources toward strategic initiatives and core strengths while the company continues to expand and explore new markets. As per the company, the way to its profitability will be catalyzed by working in conjunction with Google and Oracle.

Analysts stated that the deals are victorious for both Google and Oracle, perceiving Uber’s brand recognition. However, Oracle received considerably larger share in the contract worth over a billion dollars.

JP Morgan’s analyst Mark Murphy reported to investors, “Our sense is that Oracle’s portion of the contract likely includes a broader footprint than just Uber Freight, and Oracle may be handling 60-80% of the direct infrastructure/economics in this arrangement. We believe this is one of the 10-figure wins that Oracle had already booked and announced during its recent October quarter, and we are just learning of the logo today.”

It is evident that Uber will shut its own on-premises data centers and shift entire IT workloads to Google Cloud and Oracle.

Uber’s Chief Executive Dara Khosrowshahi said, “Uber is revolutionizing the way people, products, and services move across continents and through cities. To deliver on that promise for customers while building value for shareholders, we needed a cloud provider that will help us maximize innovation while reducing our overall infrastructure costs. Oracle provides an ideal combination of price, performance, flexibility, and security to help us deliver incredible customer service, build new products and increase profitability.”

Oracle announced that collaborating with Uber will also penetrate to other areas of collaboration. It has chosen Uber as the ride-hailing partner for employees to eat and travel globally. Oracle is also planning to continue with Uber for miscellaneous delivery and retail services.

Derrick Wood, analyst Cowen Inc., said, “This is a net new win for Oracle OCI and a notable competitive win over AWS, reinforcing the growing momentum and market share gains it has been driving over the last several quarters and giving us confidence that this momentum should continue.”

Uber deal is significant for both Google Cloud and Oracle as they compete against their cloud infrastructure market rivals, Microsoft Corp. and Amazon Web Services.

Martin Peers from a renowned media company, analyzed that AWS could have been a better choice for Uber, from a technical point of view. This is because AWS knows the business better as it has already served Lyft Inc., Uber’s rival for years. However, Uber’s decision is a function of pricing structure, as Google Cloud and Oracle are estimated to provide service at a cost lower than AWS’ offerings.

Despite receiving a smaller share of the deal, Google Cloud is keen on playing a major role in modernizing Uber’s customer experience. This can be accomplished by “technical investments” in Google Ads, Maps, and Cloud to help Uber reduce the price per trip, explore new revenue channels, and enhance in-house analytics. Besides, it assured to assist Uber in augmenting the mobile application performance.

Khosrowshahi said, “Our partnership with Google centers around a shared commitment to putting customer experience at the forefront of everything we do.”

• IBM Envizi ESG Suite, IBM Content Services, IBM Planning Analytics with Watson, and IBM App Connect Enterprise are the four offerings provided by IBM.
• In addition to the four software offerings, IBM is also releasing its IBM Z and Cloud Modernization Stack on the AWS Marketplace.

IBM Corp. has just announced that it will offer more software offerings through AWS Marketplace, operated by Amazon Web Services Inc.

The AWS Marketplace is a digital catalog where users can browse and purchase software developed by AWS’s many business partners. The items can be installed in AWS setups with less work than would normally be required. In addition to software, businesses also have access to other resources, such as consulting services and data sets.

IBM and AWS formed a partnership in May so that IBM could provide more of its software through AWS Marketplace. As a result of the collaboration, more than 50 of IBM’s software offerings are now accessible via the AWS Marketplace.

The business has just announced that it will provide four additional applications with software-as-a-service pricing through the AWS Marketplace.

IBM Envizi ESG Suite, IBM Content Services, IBM Planning Analytics with Watson, and IBM App Connect Enterprise are the four offerings provided by IBM. A single price is charged as a software-as-a-service pricing model, which includes the cost of the software and the infrastructure to run it.

The first of IBM’s four offerings on the AWS Marketplace is the Envizi ESG Suite, which aids businesses in tracking the success of their ESG (environmental, social, and governance) endeavors. IBM claims that its software can gather over 500 different types of information related to an organization’s ESG efforts. Dashboards are created to make data visualization and analysis more efficient.

IBM’s second item on the AWS Marketplace is Planning Analytics with Watson, a business planning tool. It helps businesses monitor vital indicators like revenue and predict how those measures will shift in the future. IBM claims that corporate decision-makers can use the data produced by the software.

In turn, IBM Content Services is a suite of programs that manage business content like documents. Users can navigate through files that are stored in a centralized repository via a search bar. With the help of a built-in data governance tool, IBM claims that businesses can control who has access to sensitive data.

IBM App Connect Enterprise is the company’s fourth software-as-a-service offering on the AWS Marketplace. It is a platform that facilitates building integrations between programs so that information can be shared between them. For instance, a shop owner could use the platform to connect the data from the store management system to its revenue forecasting application.

In addition to the four software offerings, IBM is also releasing its IBM Z and Cloud Modernization Stack on the AWS Marketplace. The new release comprises a set of technical resources made available to businesses to facilitate migrating mainframe applications to the cloud. A variety of related tasks, such as transmitting data from a mainframe workload to an AWS-deployed application, are also simplified by the solution.

Not all of IBM’s new announcements concerned the company’s software offerings. IBM also introduced a new consulting service called IBM Consulting Platform Services on AWS, which is aimed at making it simpler for businesses to manage their cloud applications. IBM has announced that it will do specific routine maintenance using AI-powered software.

Recently at AWS re:Invent 2022 in Las Vegas, IBM introduced its new consulting service and updated software. The corporation also unveiled an improved partner strategy at the occasion.

Now, businesses can utilize AWS committed expenditure to finance the purchase of IBM software from IBM resellers available on the AWS Marketplace. The term “committed expenditure” refers to the sum of money an organization has set aside specifically for its AWS infrastructure. Conversely, third-party software developers can now more readily incorporate IBM software into their own offerings and take advantage of IBM’s technical assistance, funding, and sales support.

• The data integration software from Striim can facilitate the data transfer between different information technology platforms.
• The company says that by giving quick access to what is happening across many real-time applications can help marketing supply chain operations, campaigning and other use cases that need up-to-the-minute information.

Striim Inc. has launched Striim Cloud on Amazon Web Services Inc., allowing clients to stream data to their AWS-based applications as soon as it is generated. This expands Striim’s real-time data integration capabilities.

Striim Cloud on AWS is now generally available and simplifies the delivery of real-time, autonomous data pipelines to just about any AWS-hosted application. Instead of waiting for the data to enter a target database or data warehouse as they usually would, businesses can run continuous queries, enrichment and analytics on live-streaming data.

Building apps that sit directly on the data pipeline makes it easier to increase their data capabilities without affecting performance, according to Striim.

Data movement between various information technology systems can be made accessible with the help of Striim’s data integration software. Significant configuration modifications are typically required to export vast amounts of data from a complicated program, such as a database. Technical difficulties also appear when a business wishes to keep utilizing an application after moving its data to a different setting.

It’s typically not enough to migrate the data once; any new data added to the old application must also be transferred over time. The platform from Striim can automatically synchronize data changes between systems. In the event of a failure, it can even pause that operation to prevent mistakes and duplicate entries.

According to Striim, AWS consumers will be a lucrative market for these skills. As it says, numerous industries are working hard to improve their responsiveness and dependability, including manufacturing, retail, logistics and supply chains.

Striim gives operations managers in those sectors access to the most recent data analytics architecture so they can use it to make informed business decisions thanks to its real-time approach to streaming data. Striim Cloud on AWS is designed to give businesses the real-time systems they need to ingest, process, query and analyze data as soon as it is generated.

Alok Pareek, Executive Vice President of Product and Co-founder of Striim, said, “The ability to make strategic business decisions in real-time is critical to competing successfully in today’s digital economy.” He added, “Striim Cloud is a powerful SaaS platform that runs natively on AWS, giving enterprise customers an invaluable advantage in reaching this goal.“

The company claims that giving quick access to what is happening across numerous real-time applications can better inform marketing campaigns, supply chain operations, and other use cases that require up-to-the-minute information. At the same time, their platform offers a consolidated picture of all the data pipelines a company uses. Due to Striim doing all the work in the background, adding new ones or changing current pipelines is considerably simpler.

“The ability to make strategic business decisions in real-time is critical to competing successfully in today’s digital economy,” said Alok Pareek. He added, “Striim Cloud is a powerful, SaaS platform that runs natively on AWS giving enterprise customers an invaluable advantage in reaching this goal.”