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AWS introduces new Chaos Engineering as a Service offering
When large companies like Netflix or Amazon want to test the resilience of their systems, they use chaos engineering tools designed to help them simulate worst-case scenarios and find potential issues before they even happen. Today at AWS re:Invent, Amazon CTO Werner Vogels introduced the company’s Chaos Engineering as a Service offering called AWS Fault Injection Simulator.
The name may lack a certain marketing panache, but Vogels said that the service is designed to help bring this capability to all companies. “We believe that chaos engineering is for everyone, not just shops running at Amazon or Netflix scale. And that’s why today I’m excited to pre-announce a new service built to simplify the process of running chaos experiments in the cloud,” Vogels said.
As he explained, the goal of chaos engineering is to understand how your application responds to issues by injecting failures into your application, usually running these experiments against production systems. AWS Fault Injection Simulator offers a fully managed service to run these experiments on applications running on AWS hardware.
Image Credits: Amazon / Getty Images
“FIS makes it easy to run safe experiments. We built it to follow the typical chaos experimental workflow where you understand your steady state, set a hypothesis and inject faults into your application. When the experiment is over, FIS will tell you if your hypothesis was confirmed, and you can use the data collected by CloudWatch to decide where you need to make improvements,” he explained.
While the company was announcing the service today, Vogels indicated it won’t actually be available until some time next year.
It’s worth noting that there are other similar services out there by companies, like Gremlin, which are already providing a broad Chaos Engineering Service as a Service offering.
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Twitter taps AWS for its latest foray into the public cloud
Twitter has a lot going on, and it’s not always easy to manage that kind of scale on your own. Today, Amazon announced that Twitter has signed a multi-year agreement with AWS to run its real-time timelines. It’s a major win for Amazon’s cloud arm.
While the companies have worked together in some capacity for over a decade, this marks the first time that Twitter is tapping AWS to help run its core timelines.
“This expansion onto AWS marks the first time that Twitter is leveraging the public cloud to scale their real-time service. Twitter will rely on the breadth and depth of AWS, including capabilities in compute, containers, storage and security, to reliably deliver the real-time service with the lowest latency, while continuing to develop and deploy new features to improve how people use Twitter,” the company explained in the announcement.
Parag Agrawal, chief technology officer at Twitter, sees this as a way to expand and improve the company’s real-time offerings by taking advantage of AWS’s network of data centers to deliver content closer to the user. “The collaboration with AWS will improve performance for people who use Twitter by enabling us to serve Tweets from data centers closer to our customers at the same time as we leverage the Arm-based architecture of AWS Graviton2 instances. In addition to helping us scale our infrastructure, this work with AWS enables us to ship features faster as we apply AWS’s diverse and growing portfolio of services,” Agrawal said in a statement.
It’s worth noting that Twitter also has a relationship with Google Cloud. In 2018, it announced it was moving its Hadoop clusters to GCP.
This announcement could be considered a case of the rich getting richer as AWS is the leader in the cloud infrastructure market by far, with around 33% market share. Microsoft is in second with around 18% and Google is in third with 9%, according to Synergy Research. In its most recent earnings report, Amazon reported $11.6 billion in AWS revenue, putting it on a run rate of over $46 billion.
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AWS expands on SageMaker capabilities with end-to-end features for machine learning
Nearly three years after it was first launched, Amazon Web Services’ SageMaker platform has gotten a significant upgrade in the form of new features, making it easier for developers to automate and scale each step of the process to build new automation and machine learning capabilities, the company said.
As machine learning moves into the mainstream, business units across organizations will find applications for automation, and AWS is trying to make the development of those bespoke applications easier for its customers.
“One of the best parts of having such a widely adopted service like SageMaker is that we get lots of customer suggestions which fuel our next set of deliverables,” said AWS vice president of machine learning, Swami Sivasubramanian. “Today, we are announcing a set of tools for Amazon SageMaker that makes it much easier for developers to build end-to-end machine learning pipelines to prepare, build, train, explain, inspect, monitor, debug and run custom machine learning models with greater visibility, explainability and automation at scale.”
Already companies like 3M, ADP, AstraZeneca, Avis, Bayer, Capital One, Cerner, Domino’s Pizza, Fidelity Investments, Lenovo, Lyft, T-Mobile and Thomson Reuters are using SageMaker tools in their own operations, according to AWS.
The company’s new products include Amazon SageMaker Data Wrangler, which the company said was providing a way to normalize data from disparate sources so the data is consistently easy to use. Data Wrangler can also ease the process of grouping disparate data sources into features to highlight certain types of data. The Data Wrangler tool contains more than 300 built-in data transformers that can help customers normalize, transform and combine features without having to write any code.
Amazon also unveiled the Feature Store, which allows customers to create repositories that make it easier to store, update, retrieve and share machine learning features for training and inference.
Another new tool that Amazon Web Services touted was Pipelines, its workflow management and automation toolkit. The Pipelines tech is designed to provide orchestration and automation features not dissimilar from traditional programming. Using pipelines, developers can define each step of an end-to-end machine learning workflow, the company said in a statement. Developers can use the tools to re-run an end-to-end workflow from SageMaker Studio using the same settings to get the same model every time, or they can re-run the workflow with new data to update their models.
To address the longstanding issues with data bias in artificial intelligence and machine learning models, Amazon launched SageMaker Clarify. First announced today, this tool allegedly provides bias detection across the machine learning workflow, so developers can build with an eye toward better transparency on how models were set up. There are open-source tools that can do these tests, Amazon acknowledged, but the tools are manual and require a lot of lifting from developers, according to the company.
Other products designed to simplify the machine learning application development process include SageMaker Debugger, which enables developers to train models faster by monitoring system resource utilization and alerting developers to potential bottlenecks; Distributed Training, which makes it possible to train large, complex, deep learning models faster than current approaches by automatically splitting data across multiple GPUs to accelerate training times; and SageMaker Edge Manager, a machine learning model management tool for edge devices, which allows developers to optimize, secure, monitor and manage models deployed on fleets of edge devices.
Last but not least, Amazon unveiled SageMaker JumpStart, which provides developers with a searchable interface to find algorithms and sample notebooks so they can get started on their machine learning journey. The company said it would give developers new to machine learning the option to select several pre-built machine learning solutions and deploy them into SageMaker environments.
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AWS announces SageMaker Clarify to help reduce bias in machine learning models
As companies rely increasingly on machine learning models to run their businesses, it’s imperative to include anti-bias measures to ensure these models are not making false or misleading assumptions. Today at AWS re:Invent, AWS introduced Amazon SageMaker Clarify to help reduce bias in machine learning models.
“We are launching Amazon SageMaker Clarify. And what that does is it allows you to have insight into your data and models throughout your machine learning lifecycle,” Bratin Saha, Amazon VP and general manager of machine learning told TechCrunch.
He says that it is designed to analyze the data for bias before you start data prep, so you can find these kinds of problems before you even start building your model.
“Once I have my training data set, I can [look at things like if I have] an equal number of various classes, like do I have equal numbers of males and females or do I have equal numbers of other kinds of classes, and we have a set of several metrics that you can use for the statistical analysis so you get real insight into easier data set balance,” Saha explained.
After you build your model, you can run SageMaker Clarify again to look for similar factors that might have crept into your model as you built it. “So you start off by doing statistical bias analysis on your data, and then post training you can again do analysis on the model,” he said.
There are multiple types of bias that can enter a model due to the background of the data scientists building the model, the nature of the data and how they data scientists interpret that data through the model they built. While this can be problematic in general it can also lead to racial stereotypes being extended to algorithms. As an example, facial recognition systems have proven quite accurate at identifying white faces, but much less so when it comes to recognizing people of color.
It may be difficult to identify these kinds of biases with software as it often has to do with team makeup and other factors outside the purview of a software analysis tool, but Saha says they are trying to make that software approach as comprehensive as possible.
“If you look at SageMaker Clarify it gives you data bias analysis, it gives you model bias analysis, it gives you model explainability it gives you per inference explainability it gives you a global explainability,” Saha said.
Saha says that Amazon is aware of the bias problem and that is why it created this tool to help, but he recognizes that this tool alone won’t eliminate all of the bias issues that can crop up in machine learning models, and they offer other ways to help too.
“We are also working with our customers in various ways. So we have documentation, best practices, and we point our customers to how to be able to architect their systems and work with the system so they get the desired results,” he said.
SageMaker Clarify is available starting to day in multiple regions.
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SingleStore, formerly MemSQL, raises $80M to integrate and leverage companies’ disparate data silos
While the enterprise world likes to talk about “big data”, that term belies the real state of how data exists for many organizations: the truth of the matter is that it’s often very fragmented, living in different places and on different systems, making the concept of analysing and using it in a single, effective way a huge challenge.
Today, one of the big up-and-coming startups that has built a platform to get around that predicament is announcing a significant round of funding, a sign of the demand for its services and its success so far in executing on that.
SingleStore, which provides a SQL-based platform to help enterprises manage, parse and use data that lives in silos across multiple cloud and on-premise environments — a key piece of work needed to run applications in risk, fraud prevention, customer user experience, real-time reporting and real-time insights, fast dashboards, data warehouse augmentation, modernization for data warehouses and data architectures and faster insights — has picked up $80 million in funding, a Series E round that brings in new strategic investors alongside its existing list of backers.
The round is being led by Insight Partners, with new backers Dell Technologies Capital, Hercules Capital; and previous backers Accel, Anchorage, Glynn Capital, GV (formerly Google Ventures) and Rev IV also participating.
Alongside the investment, SingleStore is formally announcing a new partnership with analytics powerhouse SAS. I say “formally” because they two have been working together already and it’s resulted in “tremendous uptake,” CEO Raj Verma said in an interview over email.
Verma added that the round came out of inbound interest, not its own fundraising efforts, and as such, it brings the total amount of cash it has on hand to $140 million. The gives the startup money to play with not only to invest in hiring, R&D and business development, but potentially also M&A, given that the market right now seems to be in a period of consolidation.
Verma said the valuation is a “significant upround” compared to its Series D in 2018 but didn’t disclose the figure. PitchBook notes that at the time it was valued at $270 million post-money.
When I last spoke with the startup in May of this year — when it announced a debt facility of $50 million — it was not called SingleStore; it was MemSQL. The company rebranded at the end of October to the new name, but Verma said that the change was a long time in the planning.
“The name change is one of the first conversations I had when I got here,” he said about when he joined the company in 2019 (he’s been there for about 16 months). “The [former] name didn’t exactly flow off the tongue and we found that it no longer suited us, we found ourselves in a tiny shoebox of an offering, in saying our name is MemSQL we were telling our prospects to think of us as in-memory and SQL. SQL we didn’t have a problem with but we had outgrown in-memory years ago. That was really only 5% of our current revenues.”
He also mentioned the hang up many have with in-memory database implementations: they tend to be expensive. “So this implied high TCO, which couldn’t have been further from the truth,” he said. “Typically we are ⅕-⅛ the cost of what a competitive product would be to implement. We were doing ourselves a disservice with prospects and buyers.”
The company liked the name SingleStore because it is based a conceptual idea of its proprietary technology. “We wanted a name that could be a verb. Down the road we hope that when someone asks large enterprises what they do with their data, they will say that they ‘SingleStore It!’ That is the vision. The north star is that we can do all types of data without workload segmentation,” he said.
That effort is being done at a time when there is more competition than ever before in the space. Others also providing tools to manage and run analytics and other work on big data sets include Amazon, Microsoft, Snowflake, PostgreSQL, MySQL and more.
SingleStore is not disclosing any metrics on its growth at the moment but says it has thousands of enterprise customers. Some of the more recent names it’s disclosed include GE, IEX Cloud, Go Guardian, Palo Alto Networks, EOG Resources, SiriusXM + Pandora, with partners including Infosys, HCL and NextGen.
“As industry after industry reinvents itself using software, there will be accelerating market demand for predictive applications that can only be powered by fast, scalable, cloud-native database systems like SingleStore’s,” said Lonne Jaffe, managing director at Insight Partners, in a statement. “Insight Partners has spent the past 25 years helping transformational software companies rapidly scale-up, and we’re looking forward to working with Raj and his management team as they bring SingleStore’s highly differentiated technology to customers and partners across the world.”
“Across industries, SAS is running some of the most demanding and sophisticated machine learning workloads in the world to help organizations make the best decisions. SAS continues to innovate in AI and advanced analytics, and we partner with companies like SingleStore that share our curiosity about how data and analytics can help organizations reimagine their businesses and change the world,” said Oliver Schabenberger, COO and CTO at SAS, added. “Our engineering teams are integrating SingleStore’s scalable SQL-based database platform with the massively parallel analytics engine SAS Viya. We are excited to work with SingleStore to improve performance, reduce cost, and enable our customers to be at the forefront of analytics and decisioning.”
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Eco-conscious car subscription platform finn.auto raises $24.2M, with White Star and Zalando founders
Finn.auto — which allows people to subscribe to their car instead of owning it, and offsetting their CO₂ emissions — has raised a $24.2 million / €20 million Series A funding round. White Star Capital (which has also invested in Tier Mobility), and the Zalando co-CEOs Rubin Ritter, David Schneider and Robert Gentz, are new investors in this round. All previous investors participated.
The funding comes just under a year since the company launched, after selling just 1,000 car subscriptions. It’s also partnered with Deutsche Post AG and Deutsche Telekom AG.
A number of car manufacturers have launched similar subscription services powered by various providers, such as Drover, LeasePlan and Wagonex.
U.K.-based startup Drover has raised a total of $40 million in funding over five rounds. Their latest Series B funding round was with Shell Ventures and Cherry Ventures . Plus, there are branded services which include Audi on Demand, BMW, Citroën, DS, Jaguar Carpe, Land Rover Carpe, Mini, Volkswagen and Care by Volvo.
Digitally led subscription services have the potential to disrupt the traditional car sales model, and new startups are entering the market all the time.
The finn.auto model is proving to appeal to environment-conscious millennials. For each car subscription, the company is offsetting the CO₂ emissions of its vehicles, meaning subscribers can drive their cars in a climate-neutral manner. It’s now expanding its range of fully electric vehicles and, in cooperation with ClimatePartner, is supporting selected regional climate protection and development projects.
Key to the Munich-based startups’ play is the automation of fleet management processes and customer interactions, meaning it’s much easier and cheaper to run this kind of subscription operation.
Max-Josef Meier, CEO and founder of finn.auto, said: “We are delighted to have been able to bring such high-caliber investors on board and that our existing investors are cementing their confidence with the current round. Mobility with your own car becomes as easy as buying shoes on the internet. We already offer a large selection of different car brands, whose cars can be ordered online on our platform in just five minutes and at flexible runtimes. The delivery is then conveniently made to the front door.”
Nicholas Stocks, general partner at White Star Capital added: “There is a huge opportunity globally to streamline outdated customer experiences in the automotive retail space and become the Amazon of the automotive industry. This is something finn.auto is excellently placed to capitalize on with its offering of convenience, flexibility, value and sustainability.”
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Portugal’s Bizay — a customized products marketplace for SMBs — just raised a $38.6M C round
Bizay, a marketplace for small-to-medium-sized businesses allowing them to create highly customized products (such as merchandise), has raised a $38.6 million (€32 million) funding round. The Series C financing round was co-led by investors Indico Capital and the European Investment Bank, with “strong support” from Iberis Capital and existing investors including LeadX Capital Partners, Omnes Capital and Pathena.
This means Bizay has now raised a total of more than €54 million. The company previously raised a Series B financing round of €22 million. This new round will accelerate the development of further product expansion targeted at SMBs and reinforce Bizay´s operation supplying more than one million SMBs in 21 countries across Europe and America.
Bizay’s idea is to become the “Amazon” for SMBs in terms of merchandising, packaging, consumables, business essentials, decorations and uniforms, with good quality, at a fraction of the normal costs associated with these items.
Bizay’s Chief of Growth Officer José Salgado, said: “The current health crisis accelerated the shift to online ordering of customizable products at reduced prices. Our platform will be a key facilitator for businesses to recover at a faster pace. We are totally confident in achieving the goals that will allow us to enter a new level of global ambition”.
Speaking to TechCrunch Salgado added: “We are a software company, and our technology enables us to connect to industrial manufacturers that would usually work only for large corporations. We have no stock, we have no machines, no production. Using AI we aggregate multiple orders, and supply those orders using the network of industrial producers that we have in our marketplace. So we are able to offer these SMBs competitive prices for small individual orders. These industrial manufacturers would never normally supply SMBs because they are just too small.”
Stephan Morais, managing general partner at Indico Capital Partners, said: “Bizay is entering a new growth phase and this round will consolidate their presence across Europe and enable them to capture the opportunity that stems from the shift towards online ordering of personalized products for SMBs.”
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Google acquires Actifio to step into the area of data management and business continuity
In the same week that Amazon is holding its big AWS confab, Google is also announcing a move to raise its own enterprise game with Google Cloud. Today the company announced that it is acquiring Actifio, a data management company that helps companies with data continuity to be better prepared in the event of a security breach or other need for disaster recovery. The deal squares Google up as a competitor against the likes of Rubrik, another big player in data continuity.
The terms of the deal were not disclosed in the announcement; we’re looking and will update as we learn more. Notably, when the company was valued at over $1 billion in a funding round back in 2014, it had said it was preparing for an IPO (which never happened). PitchBook data estimated its value at $1.3 billion in 2018, but earlier this year it appeared to be raising money at about a 60% discount to its recent valuation, according to data provided to us by Prime Unicorn Index.
The company was also involved in a patent infringement suit against Rubrik, which it also filed earlier this year.
It had raised around $461 million, with investors including Andreessen Horowitz, TCV, Tiger, 83 North, and more.
With Actifio, Google is moving into what is one of the key investment areas for enterprises in recent years. The growth of increasingly sophisticated security breaches, coupled with stronger data protection regulation, has given a new priority to the task of holding and using business data more responsibly, and business continuity is a cornerstone of that.
Google describes the startup as as a “leader in backup and disaster recovery” providing virtual copies of data that can be managed and updated for storage, testing, and more. The fact that it covers data in a number of environments — including SAP HANA, Oracle, Microsoft SQL Server, PostgreSQL, and MySQL, virtual machines (VMs) in VMware, Hyper-V, physical servers, and of course Google Compute Engine — means that it also gives Google a strong play to work with companies in hybrid and multi-vendor environments rather than just all-Google shops.
“We know that customers have many options when it comes to cloud solutions, including backup and DR, and the acquisition of Actifio will help us to better serve enterprises as they deploy and manage business-critical workloads, including in hybrid scenarios,” writes Brad Calder, VP, engineering, in the blog post. :In addition, we are committed to supporting our backup and DR technology and channel partner ecosystem, providing customers with a variety of options so they can choose the solution that best fits their needs.”
The company will join Google Cloud.
“We’re excited to join Google Cloud and build on the success we’ve had as partners over the past four years,” said Ash Ashutosh, CEO at Actifio, in a statement. “Backup and recovery is essential to enterprise cloud adoption and, together with Google Cloud, we are well-positioned to serve the needs of data-driven customers across industries.”
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US shopping app downloads on Black Friday reached a record 2.8M installs
Many U.S. consumers spent this year’s Black Friday sales event shopping from home on mobile devices. That led to first-time installs of mobile shopping apps in the U.S. to break a new record for single-day installs on Black Friday 2020, according to a report from Sensor Tower. The firm estimates that U.S. consumers downloaded approximately 2.8 million shopping apps on November 27th — a figure that’s up by nearly 8% over last year.
However, this number doesn’t necessarily represent faster growth than in 2019, which also saw about an 8% year-over-year increase in Black Friday shopping app installs, the report noted. This could be because mobile shopping and the related app installs are now taking place throughout the month of November, though, as retailers adjusted to the pandemic and other online shopping trends by hosting earlier sales or even month-long sales events.
Image Credits: Sensor Tower
The data seems to indicate this is true. Between November 1 and November 29, U.S. consumers downloaded approximately 59.2 million shopping apps from across the App Store and Google Play — an increase of roughly 15% from the 51.7 million they downloaded in Novenber 2019. That’s a much higher figure than the 2% year-over-year growth seen during this same period in 2019.
Another shift taking place in mobile shopping is the growing adoption of apps from brick-and-mortar retailers. During the first three quarters of 2020, apps from brick-and-mortar retailers grew installs 27%. This trend continued on Black Friday, when five out of the top 10 mobile shopping apps were those from brick-and-mortar retailers, led by Walmart.
Image Credits: Sensor Tower
Walmart saw the highest adoption this year, with around 131,000 Black Friday installs, followed by Amazon at 106,000, then Shopify’s Shop at 81,000. Combined, the top 10 apps saw 763,000 total new installs, or 27% of the first-time downloads in the Shopping category.
Because the firms are only looking at new app installs, they aren’t giving a full picture of the U.S. mobile shopping market, as many consumers already have these apps installed on their devices. And many more simply shop online via a desktop or laptop computer.
To give these figures some context, Shopify reported on Saturday it had seen record Black Friday sales of $2.4 billion, with 68% on mobile. And today, Amazon announced its small business sales alone topped $4.8 billion from Black Friday to Cyber Monday, a 60% year-over-year increase, but it didn’t break out the percentage that came from mobile.
Sensor Tower and rival app store analytics firm App Annie largely agreed on the top five shopping apps downloaded this Black Friday. They both saw Walmart again beating Amazon to become the most-downloaded U.S. shopping app on Black Friday — as it did in 2019. The two firms reported that Amazon remained No. 2 by downloads, followed by Shopify’s Shop app, then Target. However, Sensor Tower put Best Buy in fifth place, followed by Nike, while App Annie saw those positions swapped.
Image Credits: App Annie
The rest of Sensor Tower’s top 10 included SHEIN, Sam’s Club, Klarna, then Offer Up, while App Annie’s list was rounded out by SHEIN, Sam’s Club, Wish, then Offer Up.
The pandemic’s impact may not have been obvious given the growth in online shopping this year, but the recession it triggered has played a role in how U.S. consumers are paying for their purchases. “Buy Now, Pay Later” apps like Klarna were up this year, even breaking into the top 10 per Sensor Tower’s data. The firm also noted that many new shopping apps launched this year focused on discounts and deals, and retailers ran longer sales this year, as well.
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Amazon S3 Storage Lens gives IT visibility into complex S3 usage
As your S3 storage requirements grow, it gets harder to understand exactly what you have, and this is especially true when it crosses multiple regions. This could have broad implications for administrators, who are forced to build their own solutions to get that missing visibility. AWS changed that this week when it announced a new product called Amazon S3 Storage Lens, a way to understand highly complex S3 storage environments.
The tool provides analytics that help you understand what’s happening across your S3 object storage installations, and to take action when needed. As the company describes the new service in a blog post, “This is the first cloud storage analytics solution to give you organization-wide visibility into object storage, with point-in-time metrics and trend lines as well as actionable recommendations,” the company wrote in the post.
Image Credits: Amazon
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The idea is to present a set of 29 metrics in a dashboard that help you “discover anomalies, identify cost efficiencies and apply data protection best practices,” according to the company. IT administrators can get a view of their storage landscape and can drill down into specific instances when necessary, such as if there is a problem that requires attention. The product comes out of the box with a default dashboard, but admins can also create their own customized dashboards, and even export S3 Lens data to other Amazon tools.
For companies with complex storage requirements, as in thousands or even tens of thousands of S3 storage instances, who have had to kludge together ways to understand what’s happening across the systems, this gives them a single view across it all.
S3 Storage Lens is now available in all AWS regions, according to the company.
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