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Value stream management tames DevOps chaos at Eli Lilly

Pharma giant Eli Lilly discovered that simply using software delivery automation tools doesn’t bring about IT efficiency — achieving that goal required a top-down view and detailed measurements of IT and business processes, a practice known as value stream management.

Eli Lilly began searching for a way to sort out multiple DevOps pipeline tools and processes five years ago, as the company’s use of tools such as Heroku PaaS, Atlassian Jira application lifecycle management and CloudBees Jenkins continuous integration tools increased, but so did software testing and delivery delays.

Despite the use of IT automation tools such as Chef, procuring a software testing environment could take up to 30 days, and deployment processes often became bogged down in compliance-related approval processes.

“Our environments were managed via Excel, and even the Excel [spreadsheets] didn’t make sense,” said Marvin Stigter, head of platform services in the test management office at Eli Lilly. “And then we had project managers sitting up in the middle of the night, coordinating [jobs] between onshore and offshore [teams].”

That year, Eli Lilly execs became aware of Plutora, and the company eventually chose to deploy it over a competing value stream management product from their incumbent IT service management vendor ServiceNow.

Value stream management is an IT product category created by Forrester Research analysts in 2002. The term stems from value stream mapping, a practice with a long history in Lean manufacturing environments such as Toyota.

Marvin Stigter, head of platform services, test management office, Eli LillyMarvin Stigter

Value stream mapping documents the repeatable steps required to deliver a product or service to a customer, and then analyzes them to make improvements. Value stream management tools apply these principles to software delivery, measure the performance of DevOps teams against improvement goals, and in some cases, orchestrate DevOps workflow automation.

Value stream management is a growing product category. In its third-quarter 2020 Wave report on value stream management tools, Forrester assessed 11 products, from vendors that also included Digital.ai, Tasktop, Targetprocess, IBM, ConnectAll, CloudBees, Atlassian, GitLab and Blueprint.

Eli Lilly evolves from DevOps efficiency to COVID-19 data management

It took IT pros at Eli Lilly 18 months to master Plutora’s value stream management products, Stigter said. The process included creating some custom webhooks to integrate earlier versions of the Plutora product with third-party tools such as Jira. However, once that was finished, the Plutora tool had a transformative effect on Lilly’s software delivery, Stigter said.

“Since that time, we have not had one bad release go out,” he said. “It was way clearer to everybody how to make the right decision at the right time than before, [where] our release schedule was nobody knew about it until something went wrong.”

It was way clearer to everybody how to make the right decision at the right time than before, [where] our release schedule was nobody knew about it until something went wrong.
Marvin StigterHead of platform services, Eli Lilly

Value stream management measured the time it took to complete certain tasks, such as standing up a testing environment or signing an approval request. It also pinpointed the cause of lags. The Plutora tool sent automated email reminder messages to people about 15 minutes before they were expected to contribute to a process, in order to keep pipelines running on time. Plutora also added automated schedule adjustments to optimize these processes, rescheduling certain tasks and updating the right people with notifications to make delivery as fast as possible.

“You do have to be careful with the emails … you can use it the wrong way as well and get overwhelmed,” Stigter said. “But if you implement [them] correctly, it’s a huge timesaver.”

In fact, value stream management also allowed Stigter to calculate precisely how much of his team’s time was saved. Building a new test environment now takes five hours at most, compared to the previous maximum of 30 days. Blackout periods for software updates shrank from as much as two full days down to between two and four hours. Between optimized team workflows and automation bots deployed via Plutora, Stigter estimates the company has saved about $16 million per year since 2017.

This year, Eli Lilly has begun to expand its use of the Plutora tool beyond the software delivery lifecycle to workflows such as clinical trials of a potential treatment for COVID-19. Plutora helped streamline the process of loading report data from clinical trial sites into a data warehouse, tracking how many reports have been loaded and visualizing the inflow of data for business and IT stakeholders.

“Our customers in our senior management [now] get a higher level of detail with what’s going on, so we kill all the manual communications saying, ‘Hey, where are you? What’s going on?'” Stigter said. “When COVID came down, we had [study data] uploaded within two days, which had never happened before. Normally, at a minimum, it’s five weeks.”

Plutora reveals value stream management roadmap

Stigter and his team have begun to beta test new Plutora product features set for release later this year, including enhancements to how the tool orchestrates multistep automation tasks.

“If you have code in Chef that you want to kick off, now somebody doesn’t have to do it manually,” Stigter said. “If you have two or three different automations, one after another, [Plutora] will now also go automatically to the next one.”

Those multistep automation triggers have been inconsistent at times during tests, Stigter said, but continue to improve.

The upcoming Plutora release will also revamp how Plutora integrates with third-party data sources, replacing a RESTful API architecture with an event-driven system for faster data ingestion, with less custom integration required. This is similar to plans for IT automation vendor Puppet’s Relay product, which also aims to streamline IT automation workflows.

Stigter said he looks forward to faster, even real-time, data flows into Plutora’s dashboards as a possible result of the event-driven overhaul.

“[The] reports are just not real-time enough, and that’s really the lifeline of the tool,” he said. “[Without it,] if I say, ‘We saved a lot of time during this release over the weekend,’ nobody really understands what that means if they were not involved with it.”

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Intel makes new investments in AI startups

Intel Capital, the investment and venture capital arm of software giant Intel, invested $132 million in 11 startups in the AI, automation and chip design market.

Intel Capital has invested nearly $13 billion in more than 1,550 companies since its founding in 1991. The new round of startup investments, revealed May 12, highlight Intel’s continued efforts to ramp up its own AI products as it competes with other major chip and AI hardware and software players such as Nvidia and AMD.

The latest crop of vendors Intel is investing in are: Anodot, Astera Labs, Axonne, Hypersonix, KFBIO, Lilt, MemVerge, ProPlus Electronics, Retrace, Spectrum Materials and Xsight Labs.

The future is AI

For Intel, which sells hardware to power AI systems, investing in AI startups makes sense and builds synergy with its own business.

“The efficacy of AI often depends on strong processing capabilities,” said Alan Pelz-Sharpe, founder of market advisory and research firm Deep Analysis. “So, at one level Intel is invested heavily in supporting existing approaches to AI.”

Intel has long sold chips to power AI workloads, and over the last few years has invested heavily in AI hardware research and development. Last year, the Mountain View, Calif., vendor acquired Habana Labs, an Israel-based startup specializing in deep learning accelerators, for $2 billion to diversify its AI portfolio.

Venture funding increases
Venture funding increases

The acquisition built on Intel’s 2016 purchase of AI firm Nervana Systems, which enabled Intel to produce the Nervana NNP processors, a line of chips specifically designed for inferencing and training machine learning models. Intel discontinued the line this year in favor of building out chips based on Habana’s technology.

“We are moving away from generic AI capabilities to highly specialized, micro-implementations of AI that can be embedded and run at chip-level,” Pelz-Sharpe said. Intel, he said, will likely continue to embed more AI in its products over time.

Investing in startups

The 11 startups Intel Capital in which recently chose to invest likely not only benefit from the millions of dollars of funding but also from Intel’s deep expertise in complex processing, Pelz-Sharpe noted.

Intel investing in an AI startup is a huge endorsement of the startup itself.
Alan Pelz-SharpeFounder, Deep Analysis

“For some of these startups that could lead to being acquired by Intel in the future, but either way, Intel investing in an AI startup is a huge endorsement of the startup itself, so it’s not an investor that anyone would want to turn away,” he added.

Last year, Intel Capital invested $466 million across 36 new investments and 35 follow-on investments.

Other technology giants, including Microsoft, Amazon, Facebook and Alphabet, also invest heavily in startups in the AI market, and have frequently acquired AI startups over the last few years.

Funding for AI startups has skyrocketed over the past decade, with global private investments in AI startups having reached $37 billion in 2019, according to a report by Human-Centered Artificial Intelligence initiative at Stanford University.

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AWS AI tools focus on developers

AWS is the undisputed leader in the cloud market. As for AI, the cloud division of tech giant Amazon is also in a dominant position.

“Machine learning is at a place now where it is accessible enough that you don’t need Ph.Ds,” said Joel Minnick, head of product marketing for AI, machine learning and deep learning at AWS.

Partly, that’s due to a natural evolution of the technology, but vendors such as Google, AWS, IBM, DataRobot and others have made strides in making the process of creating and deploying machine learning and deep learning easier.

AWS AI

Over the last few years, AWS has invested heavily in making it easier for developers and engineers to create and deploy AI models, Minnick said, speaking with TechTarget at the AWS re:Invent 2019 user conference in Las Vegas in December 2019.

AWS’ efforts to simplify the machine leaning lifecycle were on full display at re:Invent. During the opening keynote, led by AWS CEO Andy Jassy, AWS revealed new products and updates for Amazon SageMaker, AWS’ full-service suite of machine learning development, deployment and governance products.

Those products and updates included new and enhanced tools for creating and managing notebooks, automatically making machine learning models, debugging models and monitoring models.

SageMaker Autopilot, a new AutoML product, in particular, presents an accessible way for users who are new to machine learning to create and deploy models, according to Minnick.

In general, SageMaker is one of AWS’ most important products, according to a blog-post-styled report on re:Invent from Nick McQuire, vice president of enterprise research at CCS Insight. The report noted that AWS, due largely to SageMaker, its machine learning-focused cloud services, and a range of edge and robotics products, is a clear leader in the AI space.

“Few companies (if any) are outpacing AWS in machine learning in 2019,” McQuire wrote, noting that SageMaker alone received 150 updates since the start of 2018.

Developers for AWS AI

In addition to the SageMaker updates, AWS in December unveiled another new product in its Deep series: DeepComposer.

The product series, which also includes DeepLens and DeepRacer, is aimed at giving machine learning and deep learning newcomers a simplified and visual means to create specialized models.

Introduced in late 2017, DeepLens is a camera that enables users to run deep learning models on it locally. The camera, which is fully programmable with AWS Lambda, comes with tutorials and sample projects to help new users. It integrates with a range of AWS products and services, including SageMaker and its Amazon Rekognition image analysis service.

“[DeepLens] was a big hit,” said Mike Miller, director of AWS AI Devices at AWS.

DeepRacer, revealed the following year, enables users to apply machine learning models to radio controlled (RC) model cars and make them autonomously race along tracks. Users can build models in SageMaker and bring them into a simulated racetrack, where they can train the models before bringing them into a 1/18th scale race car.

An AWS racing league makes DeepRacer competitive, with AWS holding yearlong tournaments comprised of multiple races. DeepRacer, Miller declared, has been exceedingly successful.

“Tons of customers around the world have been using DeepRacer to engage and upskill their employees,” Miller said.

Dave Anderson, director of technology at Liberty Information Technology, the IT arm of Liberty Mutual, said many people on his team take part in the DeepRacer tournaments.

“It’s a really fun way to learn machine learning,” Anderson said in an interview. “It’s good fun.”

Composing with AI

Meanwhile, DeepComposer as the name suggests, helps train users on machine learning and deep learning through music. The product comes with a small keyboard that can plug into a PC along with a set of pretrained music genre models. The keyboard itself isn’t unusual, but by using the models and accompanying software, users automatically create and tweak fairly basic pieces of music within a few genres.

With DeepComposer, along with DeepLens and Deep Racer, “developers of any skill level can find a perch,” Miller said.

The products fit into Amazon’s overall AI strategy well, he said.

“For the last 20 years, Amazon has been investing in machine learning,” Miller said. “Our goal is to bring those same AI and machine learning techniques to developers of all types.”

The Deep products are just “the tip of the spear for aspiring machine learning developers,” Miller said. Amazon’s other products, such as SageMaker, extend that machine learning technology development strategy.

“We’re super excited to get more machine learning into the hands of more developers,” Miller said.

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New Amazon Kendra AI search tool indexes enterprise data

LAS VEGAS — Amazon Kendra, a new AI-driven search tool from the tech giant, is designed to enable organizations to automatically index business data, making it easily searchable using keywords and context.

Revealed during a keynote by AWS CEO Andy Jassy at the re:Invent 2019 user conference here,  Kendra relies on machine learning and natural language processing (NLP) to bring enhanced search capabilities to on-premises and cloud-based business data. The system is in preview.

“Kendra is enterprise search technology,” said Forrester analyst Mike Gualtieri. “But, unlike enterprise search technology of the past, it uses ML [machine learning] to understand the intent of questions and return more relevant results.”

Cognitive search

Forrester, he said, calls this type of technology “cognitive search.” Recent leaders in that market, according to a Forrester Wave report Gualtieri helped write, include intelligent search providers Coveo, Attivio, IBM, Lucidworks, Mindbreeze and Sinequa. Microsoft was also ranked highly in the report, which came out in May 2019. AWS is a new entrant in the niche.

“Search is often an area customers list as being broken especially across multiple data stores whether they be databases, office applications or SaaS,” said Nick McQuire, vice president at advisory firm CCS Insight.

Unlike enterprise search technology of the past, [Kendra] uses ML to understand the intent of questions and return more relevant results.
Mike GualtieriAnalyst, Forrester

While vendors such as IBM and Microsoft have similar products, “the fact that AWS is now among the first of the big tech firms to step into this area illustrates the scale of the challenge” to bring a tool like this to market, he said.

During his keynote, Jassy touted the intelligent search capabilities of Amazon Kendra, asserting that the technology will “totally change the value of the data” that enterprises have.

Setup of Kendra appears straightforward. Organizations will start by linking their storage accounts and providing answers to some of the questions their employees frequently query their data about. Kendra then indexes all the provided data and answers, using machine learning and NLP to attempt to understand the data’s context.

Understanding context

“We’re not just indexing the keywords inside the document here,” Jassy said.

AWS CEO Andy Jassy announced Kendra at AWS re:Invent 2019
AWS CEO Andy Jassy announced Kendra at AWS re:Invent 2019

Meanwhile, Kendra is “an interesting move especially since AWS doesn’t really have a range of SaaS application which generate a corpus of information that AI can improve for search,” McQuire said.

“But,” he continued, “this is part of a longer-term strategy where AWS has been focusing on specific business and industry applications for its AI.”

Jassy also unveiled new features for Amazon Connect, AWS’ omnichannel cloud contact center platform. With the launch of Contact Lens for Amazon Connect, users will be able to perform machine learning analytics on their customer contact center data. The platform will also enable users to automatically transcribe phone calls and intelligently search through them.

By mid-2020, Jassy said, Amazon Kendra will support real-time transcription and analysis of phone calls.

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AI in advertising captures audiences with personalized ads

In 2017, Flipkart, the giant e-commerce vendor based in Bengaluru, India, got a cold-call email from AdGreetz. The email highlighted AdGreetz’s product, an AI in advertising platform that can generate thousands or millions of personalized ads quickly.

Intrigued, Flipkart, which is owned primarily by Walmart, struck up communication with AdGreetz, and decided to move ahead with a pilot project.

The first campaign AdGreetz did for Flipkart reached 200 million people across social media platforms, said Vijay Sharma, associate director of brand marketing and head of digital media at Flipkart.

Advertising flip

The audience, spread across different regions of India, was diverse, Sharma said.

“These are people of different types, in different cities, with different motivations, with different relationships with Flipkart,” he said.

We created a fairly complex, hard-working campaign, and that showed results.
Vijay SharmaAssociate director of brand marketing and head of digital media, Flipkart

To give the ads a more significant impact, AdGreetz and Flipkart created about a million creatives, or ad banners and other forms of created online advertising, each targeting different groups based on data collected over social media and Flipkart’s e-commerce platform. Depending on who they targeted, the ads varied dramatically, including different colors, voices and languages.

“We created a fairly complex, hard-working campaign, and that showed results,” Sharma said.

Since then, Flipkart has used AdGreetz to produce some 40 different campaigns, he said. The results have been mainly positive.

The first project took about two and a half months to complete, slowed by initial integrations and a lot of back-and-forth. Now, Vijay Sharma said, campaigns can be completed within a week.

AdGreetz, AI in advertising
Using AI, AdGreetz generates millions of personalized ads for Flipkart

AI in advertising

AdGreetz, a 2009 startup based in Los Angeles, uses a platform imbued with machine learning to quickly and automatically create millions of personalized advertisements, CEO and co-founder Eric Frankel said.

Taking a few templates and AI in advertising technology, along with data, including a consumer’s buying habits, location, age and gender, AdGreetz can automatically create personalized variations of those template ads. Advertisement forms include television spots, online banners and videos, emails, and physical product labels.

AdGreetz doesn’t keep consumer data used to create them, Frankel claimed.

The vendor’s relationship with Flipkart is close, probably closer than with any other customer AdGreetz has, Frankel said.

“They bought in from day one,” he said, adding that he thinks the relationship has been fruitful for Flipkart.

“They will probably be the most personalized company in the world,” he said.

Big results

For Flipkart, the ads campaigns have seen “big numbers,” according to Sharma. The company can create far more personalized ads than it did before using AdGreetz, back when marketing teams filled up Excel sheets with creatives, he said.

While the AdGreetz platform relies on AI in advertising, it still requires manual effort from Flipkart to operate.

“It’s not an end-to-end solution,” Sharma said.

The team first creates a creative and then works with AdGreetz to build it into a storyboard, which is then multiplied and personalized. Often, Flipkart needs to provide cultural context to the advertisements and tweak them before they go live.

Sharma has spoken with some competing vendors, as they came highly rated. He said he’s keeping his options open, but for right now is sticking with AdGreetz.

He referenced Alibaba, the China-based tech and e-commerce giant. Alibaba, Sharma said, possesses the ability to create billions of personalized advertisements using AI in advertising and provides some of the most personalized marketing campaigns in the world.

“Hopefully,” Sharma said, “One day, we will also get there.”

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Microsoft to apply CCPA protections to all US customers

Microsoft is taking California’s new data privacy law nationwide.

The software giant this week said it will honor the California Consumer Privacy Act (CCPA) throughout the United States. When the CCPA goes into effect on Jan. 1, 2020, companies in California will be required to provide people with the option to stop their personal information from being sold, and will generally require that companies are transparent about data collection and data use.

The CCPA applies to companies that do business in California, collect customers’ personal data and meet one of the following requirements: have annual gross revenue of more than $25 million; buy, receive, sell or share personal data of 50,000 or more consumers, devices or households for commercial purposes; or earn 50% or more of their annual revenues from selling consumers’ personal data.

Julie Brill, Microsoft’s corporate vice president for global privacy and regulatory affairs and Chief Privacy Officer, announced her company’s plans to go a step further and apply the CCPA’s data privacy protections to all U.S. customers — not just those in California.

“We are strong supporters of California’s new law and the expansion of privacy protections in the United States that it represents. Our approach to privacy starts with the belief that privacy is a fundamental human right and includes our commitment to provide robust protection for every individual,” Brill wrote in a blog post. “This is why, in 2018, we were the first company to voluntarily extend the core data privacy rights included in the European Union’s General Data Protection Regulation (GDPR) to customers around the world, not just to those in the EU who are covered by the regulation. Similarly, we will extend CCPA’s core rights for people to control their data to all our customers in the U.S.”

Brill added that Microsoft is working with its enterprise customers to assist them with CCPA compliance. “Our goal is to help our customers understand how California’s new law affects their operations and provide the tools and guidance they will need to meet its requirements,” she said.

Microsoft did not specify when or how it will apply the CPAA for all U.S. citizens. In recent years the company has introduced several privacy-focused tools and features designed to give customers greater control over their personal data.

Fatemeh Khatibloo, vice president and principal analyst at Forrester Research, said Microsoft has an easier path to becoming CCPA compliant because of its early efforts to broadly implement GDPR protections.

“They’re staying very true to all the processes they went through under GDPR,” she said. “CCPA has some differences with GDPR. Namely, it’s got some requirements to verify the identity of people who want to exercise their rights. GDPR is still based on an opt-in framework rather than an opt-out one; it requires consent if you don’t have another legal basis for processing somebody’s data. The CCPA is still really about giving you the opportunity to opt out. It’s not a consent-based framework.”

Khatibloo also noted that Microsoft was supportive of the CCPA early on, and that Brill, who formerly served as commissioner of the U.S. Federal Trade Commission under the Obama administration, has a strong history on data privacy.

“She understands the extensive need for a comprehensive privacy bill in the U.S., and I think she also understands that that’s probably not going to happen in the next year,” Khatibloo said. “Instead of waiting for a patchwork of laws to turn up, I think she’s taking a very proactive move to say, ‘We’re going to abide by this particular set of rules, and we’re going to make it available to everybody.’ The other really big factor here is, who wants to be the company that says its New York customers don’t have the same rights that its California customers do?

Rebecca Herold, an infosec and privacy consultant as well as CEO of The Privacy Professor consultancy, argued that while CCPA does a good job addressing the “breadth of privacy issues for individuals who fall under the CCPA definition of a ‘California consumer,'” it falls short in multiple areas. To name a few criticisms, she pointed out that it doesn’t apply to organizations with under $25 million in revenue, it does not apply to all types of data or individuals such as employees, and that many of its requirements can come across as confusing.

But Herold said Microsoft’s move to apply CCPA for all 50 states makes sense and it’s something she recommends to her clients when consulting on new regional regulations. “When looking at implementing a wide-ranging law like CCPA, it would be much more simplified to just follow it for all their millions of customers, and not try to parse out the California customers from all others,” she said via email. “It is much more efficient and effective to simplify data security and privacy practices by treating all individuals within an organization’s database equally, meeting a baseline of actions that fit all legal requirements across the board. This is a smart and savvy business leadership move.”

Mike Bittner, associate director of digital security and operations for advertising security vendor The Media Trust, agreed that Microsoft’s move isn’t surprising.  

“For a large company like Microsoft that serves consumers around the world, simplifying regulatory compliance by applying the same policies across an entire geography makes a lot of sense, because it removes the headaches of applying a hodgepodge of state-level data privacy laws,” he said in an email. “Moreover, by using the CCPA — the most robust U.S. data privacy law to date — as the standard, it demonstrates the company’s commitment to protecting consumers’ data privacy rights.”

Herold added that the CCPA will likely become the de facto data privacy law for the U.S. in the foreseeable future because Congress doesn’t appear to be motivated to pass any federal privacy laws.

Brill appeared to agree.

“CCPA marks an important step toward providing people with more robust control over their data in the United States,” she wrote in her blog post. “It also shows that we can make progress to strengthen privacy protections in this country at the state level even when Congress can’t or won’t act.”

Senior reporter Michael Heller contributed to this report.

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AWS gets behind Rust programming language

AWS has gotten behind the Rust programming language in a big way, to the point where the cloud infrastructure giant has become a sponsor of the language.

Since its first stable release four years ago, Rust has emerged as a viable alternative to C++. Known for enabling developers to build high-performing, reliable applications, as well as for boosting programmer productivity, Rust has been adopted as a system programming language by companies including Google, Microsoft, Mozilla, Yelp, Dropbox, Cloudflare and AWS.

“Rust is the first real alternative to C++ that we’ve seen in a long time,” said Cameron Purdy, CEO of Xqiz.it, a Lexington, Mass., startup developing its own programming language, known as Ecstasy. “Rust is built for systems-level work, and appears to be far better thought out than C++ was.”

Indeed, “Rust is making significant inroads as a language for systems programming,” said James Governor, an analyst at RedMonk.

The use of Rust at AWS has grown, as services such as Lambda, EC2 and S3 use Rust in performance-sensitive components. Also, AWS’s Firecracker virtualization technology is written using Rust.

The AWS sponsorship of Rust includes supporting the Rust project infrastructure. AWS provides promotional credits to the Rust project to be used to perform upstream and performance testing, CI/CD or storage of artifacts on AWS, the company said in a blog post. AWS also is offering similar promotional credits to other open source projects, including AdoptOpenJDK, Maven Central and the Julia programming language.

Jeffrey HammondJeffrey Hammond

“I think AWS is looking for opportunities to blunt the criticism — undeserved or not — that while it is a consumer and benefactor from its OSS consumption, it’s not a producer or community supporter of it,” said Jeffrey Hammond, an analyst at Forrester Research. “Projects like Coretto, Firecracker and sponsorship projects like this all go to counter that narrative.”

According to AWS, the Rust project uses AWS services to:

  • Store release artifacts such as compilers, libraries, tools and source code on S3.
  • Run ecosystem-wide regression tests with Crater on EC2.
  • Operate docs.rs, a website that hosts documentation for all packages published to the central crates.io package registry.

“It’s interesting that AWS recently made this approach explicit, but AWS is not alone,” Governor said. “I talk a lot about folks being ‘Rust curious,’ but it appears we’re now moving beyond curiosity. Microsoft is another major player making a strong call for more Rust-based development. Rust is no longer something for developers to play with on their weekends. It’s becoming a language of infrastructure.”

I talk a lot about folks being ‘Rust curious,’ but it appears we’re now moving beyond curiosity.
James GovernorAnalyst, RedMonk

Rust has been ranked as the “most loved” programming language in the annual Stack Overflow developer survey for four years in a row. With no runtime or garbage collector, Rust delivers faster performance. Rust also provides memory and thread safety, which helps to eliminate bugs.

In July, Microsoft said it was looking at Rust as an alternative to C and C++ based on its safety and performance. In other words, Rust enables developers to create secure, high-performant applications, said Ryan Levick, a principal cloud developer advocate at Microsoft, in a blog post.

“We believe Rust changes the game when it comes to writing safe systems software,” Levick said. “Rust provides the performance and control needed to write low-level systems, while empowering software developers to write robust, secure programs.”

However, Microsoft found some issues with Rust that will need to be addressed, including the lack of first-class interoperability with C++, and interoperability with existing Microsoft tooling, Levick said.

Holger Mueller, an analyst at Constellation Research in San Francisco, said the race for cloud market leadership is based on attracting developers to build next-generation applications on the leading cloud platforms.

“From time to time there is a new programming language that catches the attention of developers, usually for productivity and/or capability reasons,” he said. “That’s the case with Rust, which is gaining quickly in popularity and, hence, large IaaS providers need to support Rust.”

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Amazon Chime app adds dial-out, single sign-on features

Amazon Web Services has been gradually building out the features of Amazon Chime, as the tech giant struggles to attract corporate interest in the online messaging and meetings platform.

AWS added a dial-out function to the Amazon Chime app this week so that users can program the app to call a phone number at the start of a meeting. The feature will simplify the process of connecting to meeting audio for attendees who are away from their desks. 

AWS also recently announced it would integrate the Amazon Chime app with the software of Okta, a leading single sign-on vendor. Okta’s platform consolidates the username and password information of an organization’s apps so that users only have to remember one set of sign-on credentials.

Last month, AWS made it possible to conduct a Chime video meeting in Google Chrome. While all major browsers support messaging and most non-video meeting features, Chrome is the only internet client that supports Chime video conferencing. (Users can also install a desktop app.)

“I see these largely as incremental improvements that allow Amazon to better compete with the likes of Zoom, BlueJeans, GoToMeeting, Cisco Webex, etc.,” said Irwin Lazar, analyst at Nemertes Research, based in Mokena, Ill.

Businesses expect all online meetings platforms to support in-browser video conferencing at this point, while single sign-on is a must-have feature for many large organizations, Lazar said.

Amazon Chime app trails rivals as AWS seeks greater share of collaboration market

Launched in February 2017, Amazon Chime is still playing catch-up with more established online meetings platforms. Amazon has stepped up efforts to penetrate the enterprise market in recent years, including with the release of the contact center platform Amazon Connect.

Alexa for Business, an enterprise version of the vendor’s popular AI voice assistant, has the potential to gain traction in the enterprise market, said Wayne Kurtzman, analyst at IDC. The Amazon Chime app, however, is not yet on the radar of many companies, he said.

“While Alexa for Business will gain traction over time, mostly integrated with other products, Amazon has to prove that Chime will be here for the long haul, be better than competitors and be a trusted part of a custom, cloud-based IT stack,” Kurtzman said.

Amazon is not the only consumer tech giant making a play at the enterprise collaboration market. Google also recently released a team collaboration app, Hangouts Chat, and an online meetings platform, Hangouts Meet.

AWS, a $17.5 billion division of Amazon, has sought to use low and flexible pricing to attract businesses to Amazon Chime.

When Chime first launched, AWS gave customers the ability to prorate the subscription fees of individual users by activating and deactivating their licenses on demand. Later, the vendor implemented a usage-based pricing system that costs $3 every time a user hosts a meeting, for a maximum of $15 per user, per month.

In announcing usage-based pricing in March, AWS said it expected the new scheme would reduce the bills of virtually all premium customers of Amazon Chime. Nevertheless, aggressive pricing hasn’t been enough to draw attention from tech buyers.

“I rarely hear about Chime,” said Alan Lepofsky, analyst at Constellation Research, based in Cupertino, Calif. “I think Chime could have an interesting differentiation if Amazon made it very easy for developers to add voice and video features to custom applications. That would make Chime more of a competitor to Twilio than to Webex.”

At OpenText Enterprise World, security and AI take center stage

OpenText continues to invest in AI and security, as the content services giant showcased where features from recent acquisitions fit into its existing product line at its OpenText Enterprise World user conference.

The latest Pipeline podcast recaps the news and developments from Toronto, including OpenText OT2, the company’s new hybrid cloud/on-premises enterprise information management platform. The new platform brings wanted flexibility while also addressing regulatory concerns with document storage.

“OT2 simplifies for our customers how they invest and make decisions in taking some of their on-premises workflows and [porting] them into a hybrid model or SaaS model into the cloud,” said Muhi Majzoub, OpenText executive vice president of engineering and IT.

Majzoub spoke at OpenText Enterprise World 2018, which also included further updates to how OpenText plans to integrate Guidance Software’s features into its endpoint security offerings following the Guidance’s September 2017 acquisition.

Will the native AI functionality from OpenText compare and keep up? What will be the draw for new customers?
Alan Lepofskyprincipal analyst, Constellation Research

OpenText has a rich history of acquiring companies and using the inherited customer base as an additional revenue or maintenance stream, as content management workflows are often built over decades of complex legacy systems.

But it was clear at OpenText Enterprise World 2018 that the Guidance Software acquisition filled a security gap in OpenText’s offering. One of Guidance’s premier products, EnCase, seems to have useful applications for OpenText users, according to Lalith Subramanian, vice president of engineering for analytics, security and discovery at OpenText.

In addition, OpenText is expanding its reach to Amazon AWS, Microsoft Azure and Google Cloud, but it’s unclear if customers will prefer OpenText offerings to others on the market or if current customers will migrate to public clouds.

“It comes down to: Will customers want to use a general AI platform like Azure, Google, IBM or AWS?” said Alan Lepofsky, principal analyst for Constellation Research. “Will the native AI functionality from OpenText compare and keep up? What will be the draw for new customers?”