CloudBolt, a Bethesda, Maryland startup that helps companies manage hybrid cloud environments, announced a $35 million Series B investment today. It was split between $15 million in equity investment and $20 million in debt.

Insight Partners provided the equity side of the equation, while Hercules Capital and Bridge Bank supplied the venture debt. The company has now raised more than $61 million in equity and debt, according to Crunchbase data.

CEO Jeff Kukowski says that his company helps customers with cloud and DevOps management including cost control, compliance and security. “We help [our customers] take advantage of the fact that most organizations are already hybrid cloud, multi cloud and/or multi tool. So you have all of this innovation happening in the world, and we make it easier for them to take advantage of it,” he said.

As he sees it, the move to cloud and DevOps, which was supposed to simplify everything, has actually created new complexity, and the tools his company sells are designed to help companies reduce some of that added complexity. What they do is provide a way to automate, secure and optimize their workloads, regardless of the tools or approach to infrastructure they are using.

The company closed the funding round at the end of last quarter and put it to work with a couple of acquisitions — Kumolus and SovLabs — to help accelerate and fill in the road map. Kumolus, which was founded in 2011 and raised $1.7 million, according to Crunchbase, really helps CloudBolt extend its vision from managing on premises to the public cloud.

SovLabs was an early-stage startup working on a very specific problem creating a framework for extending VMware automation.

CloudBolt currently has 170 employees. While Kukowski didn’t want to get specific about the number of additional employees he might be adding to that in the next 12 months, he says that as he does, he thinks about diversity in three ways.

“One is just pure education. So we as a company regularly meet and educate on issues around inclusion, social justice and diversity. We also recruit with those ideas in mind. And then we also have a standing committee within the company that continues to look at issues not only for discussion, but quite frankly for investment in terms of time and fundraising,” he said.

Kukowski says that going remote because of COVID has allowed the company to hire from anywhere, but he still looks forward to a time when he can meet face-to-face with his employees and customers, and sees that as always being part of his company’s culture.

CloudBolt was founded in 2012 and has around 200 customers. Kukowski says that the company is growing between 40% and 50% year over year, although he wouldn’t share specific revenue numbers.

As IBM transitions from software and services to a company fully focussed on hybrid cloud management, it announced  its intention to buy Instana, an applications performance management startup with a cloud native approach that fits firmly within that strategy.

The companies did not reveal the purchase price.

With Instana, IBM can build on its internal management tools, giving it a way to monitor containerized environments running Kubernetes. It hopes by adding the startup to the fold it can give customers a way to manage complex hybrid and multi-cloud environments.

“Our clients today are faced with managing a complex technology landscape filled with mission-critical applications and data that are running across a variety of hybrid cloud environments – from public clouds, private clouds and on-premises,” Rob Thomas, senior vice president for cloud and data platform said in a statement. He believes Instana will help ease that load, while using machine learning to provide deeper insights.

At the time of the company’s $30 million Series C in 2018, TechCrunch’s Frederic Lardinois described the company this way. “What really makes Instana stand out is its ability to automatically discover and monitor the ever-changing infrastructure that makes up a modern application, especially when it comes to running containerized microservices.” That would seem to be precisely the type of solution that IBM would be looking for.

As for Instana, the founders see a good fit for the two companies, especially in light of the Red Hat acquisition in 2018 that is core to IBM’s hybrid approach. “The combination of Instana’s next generation APM and Observability platform with IBM’s Hybrid Cloud and AI technologies excited me from the day IBM approached us with the idea of joining forces and combining our technologies,” CEO Mirko Novakovic wrote in a blog post announcing the deal.

Indeed, in a recent interview IBM CEO Arvind Krishna told CNBC’s Jon Fortt, that they are betting the farm on hybrid cloud management with Red Hat at the center. When you combine that with the decision to spin out the company’s managed infrastructure services business, this purchase shows that they intend to pursue every angle

“The Red Hat acquisition gave us the technology base on which to build a hybrid cloud technology platform based on open-source, and based on giving choice to our clients as they embark on this journey. With the success of that acquisition now giving us the fuel, we can then take the next step, and the larger step, of taking the managed infrastructure services out. So the rest of the company can be absolutely focused on hybrid cloud and artificial intelligence,” Krishna told CNBC.

Instana, which is based in Chicago with offices in Munich, was founded in 2015 in the early days of Kubernetes and the startup’s APM solution has evolved to focus more on the needs of monitoring in a cloud native environment. The company raised $57 million along the way with the most recent round being that Series C in 2018.

The deal per usual is subject to regulatory approvals, but the company believes it should close in the next few months.

Data engineering is one of these new disciplines that has gone from buzzword to mission critical in just a few years. Data engineers design and build all the connections between sources of raw data (your payments information or ad-tracking data or what have you) and the ultimate analytics dashboards used by business executives and data scientists to make decisions. As data has exploded, so has their challenge of doing this key work, which is why a new set of tools has arrived to make data engineering easier, faster and better than ever.

One of those tools is Datafold, a YC-backed startup I covered just a few weeks ago as it was preparing for its end-of-summer Demo Day presentation.

Well, that Demo Day presentation and the company’s trajectory clearly caught the eyes of investors, since the startup locked in $2.1 million in seed funding from NEA, the company announced this morning.

As I wrote back in August:

With Datafold, changes made by data engineers in their extractions and transformations can be compared for unintentional changes. For instance, maybe a function that formerly returned an integer now returns a text string, an accidental mistake introduced by the engineer. Rather than wait until BI tools flop and a bunch of alerts come in from managers, Datafold will indicate that there is likely some sort of problem, and identify what happened.

Definitely read our profile if you want to learn more about the product and origin story.

Not a whole heck of a lot has changed over the past few weeks (some new features, some new customers), but with more money in its billfold, Datafold is going to keep on growing, hiring and taking on the world of data engineering.

AI startup RealityEngines.AI changed its name to Abacus.AI in July. At the same time, it announced a $13 million Series A round. Today, only a few months later, it is not changing its name again, but it is announcing a $22 million Series B round, led by Coatue, with Decibel Ventures and Index Partners participating as well. With this, the company, which was co-founded by former AWS and Google exec Bindu Reddy, has now raised a total of $40.3 million.

In addition to the new funding, Abacus.AI is also launching a new product today, which it calls Abacus.AI Deconstructed. Originally, the idea behind RealityEngines/Abacus.AI was to provide its users with a platform that would simplify building AI models by using AI to automatically train and optimize them. That hasn’t changed, but as it turns out, a lot of (potential) customers had already invested into their own workflows for building and training deep learning models but were looking for help in putting them into production and managing them throughout their lifecycle.

“One of the big pain points [businesses] had was, ‘look, I have data scientists and I have my models that I’ve built in-house. My data scientists have built them on laptops, but I don’t know how to push them to production. I don’t know how to maintain and keep models in production.’ I think pretty much every startup now is thinking of that problem,” Reddy said.

Since Abacus.AI had already built those tools anyway, the company decided to now also break its service down into three parts that users can adapt without relying on the full platform. That means you can now bring your model to the service and have the company host and monitor the model for you, for example. The service will manage the model in production and, for example, monitor for model drift.

Another area Abacus.AI has long focused on is model explainability and de-biasing, so it’s making that available as a module as well, as well as its real-time machine learning feature store that helps organizations create, store and share their machine learning features and deploy them into production.

As for the funding, Reddy tells me the company didn’t really have to raise a new round at this point. After the company announced its first round earlier this year, there was quite a lot of interest from others to also invest. “So we decided that we may as well raise the next round because we were seeing adoption, we felt we were ready product-wise. But we didn’t have a large enough sales team. And raising a little early made sense to build up the sales team,” she said.

Reddy also stressed that unlike some of the company’s competitors, Abacus.AI is trying to build a full-stack self-service solution that can essentially compete with the offerings of the big cloud vendors. That — and the engineering talent to build it — doesn’t come cheap.

It’s no surprise then that Abacus.AI plans to use the new funding to increase its R&D team, but it will also increase its go-to-market team from two to ten in the coming months. While the company is betting on a self-service model — and is seeing good traction with small- and medium-sized companies — you still need a sales team to work with large enterprises.

Come January, the company also plans to launch support for more languages and more machine vision use cases.

“We are proud to be leading the Series B investment in Abacus.AI, because we think that Abacus.AI’s unique cloud service now makes state-of-the-art AI easily accessible for organizations of all sizes, including start-ups,” Yanda Erlich, a p artner at Coatue Ventures  told me. “Abacus.AI’s end-to-end autonomous AI service powered by their Neural Architecture Search invention helps organizations with no ML expertise easily deploy deep learning systems in production.”

 

PingCAP, the open-source software developer best known for NewSQL database TiDB, has raised a $270 million Series D. TiDB handles hybrid transactional and analytical processing (HTAP), and is aimed at high-growth companies, including payment and e-commerce services, that need to handle increasingly large amounts of data.

The round’s lead investors were GGV Capital, Access Technology Ventures, Anatole Investment, Jeneration Capital and 5Y Capital (formerly known as Morningside Venture Capital). It also included participation from Coatue, Bertelsmann Asia Investment Fund, FutureX Capital, Kunlun Capital, Trustbridge Partners, and returning investors Matrix Partners China and Yunqi Partners.

The funding brings PingCAP’s total raised so far to $341.6 million. Its last round, a Series C of $50 million, was announced back in September 2018.

PingCAP says TiDB has been adopted by about 1,500 companies across the world. Some examples include Square; Japanese mobile payments company PayPay; e-commerce app Shopee; video-sharing platform Dailymotion; and ticketing platfrom BookMyShow. TiDB handles online transactional processing (OLTP) and online analytical processing (OLAP) in the same database, which PingCAP says results in faster real-time analytics than other distributed databases.

In June, PingCAP launched TiDB Cloud, which it describes as fully-managed “TiDB as a Service,” on Amazon Web Services and Google Cloud. The company plans to add more platforms, and part of the funding will be used to increase TiDB Cloud’s global user base.