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Syniverse Technologies, a company that helps mobile providers move communications across public and private networks, announced an extensive partnership with Twilio this morning. Under the agreement, Twilio is investing up to $750 million to become a minority owner in the company.
The idea behind the partnership is to combine Twilio’s API communications expertise with Syniverse’s mobile carrier contacts to create this end-to-end communications system. Twilio’s strength has always been its ability to deliver communications like texts without having a carrier relationship. This deal gives them access to that side of the equation.
James Attwood, executive chairman at Syniverse, certainly saw the value of the two companies working together. “The partnership will provide Syniverse access to Twilio’s extensive enterprise and API services expertise, creating opportunities to continue to build on Syniverse’s highly innovative product portfolio that helps mobile network operators and enterprises make communications better for their customers,” Attwood said in a statement.
Today’s deal comes on the heels of the company’s $3.2 billion acquisition of Segment at the end of last year as it continues to look for ways to expand its markets. Will Townsend, an analyst at Moor Insight & Strategy who covers the network and carrier markets, sees this deal giving Twilio access to a broader set of technologies.
“Twilio [gets] access to Syniverse’s significant capabilities in massive industrial IoT and private 4G LTE and 5G cellular networking. Both are poised to ramp significantly given newfound enterprise access to licensed spectrum via recent C-Band and CBRS auctions,” Townsend told me. He believes this will help Twilio reach parts of the enterprise not connected by Wi-FI or where the customers are dealing with “a mishmash of solutions that don’t scale or propagate well.”
As it turns out, it’s not a coincidence the two companies are coming together like this. In fact, Twilio has been a Syniverse customer for some time, according to Chee Chew, chief product officer at Twilio.
It’s a case of an old-school company like Syniverse, which was founded in 1987, combining forces with a more modern approach to communications like Twilio, which provides developers with APIs to deliver communications services inside applications with just a couple of lines of code.
The Wall Street Journal, which broke the news of this deal, is also reporting the company could go public via SPAC at a value of between $2 and $3 billion some time later this year. That would suggest that it has not gained much value since the 2010 deal.
Holger Mueller, an analyst at Constellation Research, says the SPAC provides an interesting additional component to the deal. “The high-flying stock market creates all kind of new chickens, one of them being a SPAC, and that’s the financial opportunity that Twilio is likely pursuing with the investment into Syniverse. The more immediate benefit is for Twilio to use the messaging vendor for its services. Call it a partnership with investment upside,” Mueller said.
According to Syniverse, “the company is one of the largest private IP Packet Exchange (IPX) providers in the world and offers a range of networking solutions, excelling in scenarios where seamless connections must cross over networks — either across multiple private networks or between public and private networks.”
The company is currently owned by the Carlyle Group private equity firm, which bought it in 2010 for $2.6 billion. Twilio launched in 2008 and raised over $236 million before going public in 2016 at $15 per share. The stock was up 3.82% in early trading, suggesting that Wall Street approves of the deal.
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This morning DigitalOcean, a provider of cloud computing services to SMBs, filed to go public. The company intends to list on the New York Stock Exchange (NYSE) under the ticker symbol “DOCN.”
DigitalOcean’s offering comes amidst a hot streak for tech IPOs, and valuations that are stretched by historical norms. The cloud hosting company was joined by Coinbase in filing its numbers publicly today.
DigitalOcean’s offering comes amidst a hot streak for tech IPOs.
However, unlike the cryptocurrency exchange, DigitalOcean intends to raise capital through its offering. Its S-1 filing lists a $100 million placeholder number, a figure that will update when the company announces an IPO price range target.
This morning let’s explore the company’s financials briefly, and then ask ourselves what its results can tell us about the cloud market as a whole.
TechCrunch has covered DigitalOcean with some frequency in recent years, including its early-2020 layoffs, its early-2020 $100 million debt raise and its $50 million investment from May of the same year that prior investors Access Industries and Andreessen Horowitz participated in.
From those pieces we knew that the company had reportedly reached $200 million in revenue during 2018, $250 million in 2019 and that DigitalOcean had expected to reach an annualized run rate of $300 million in 2020.
Those numbers held up well. Per its S-1 filing, DigitalOcean generated $203.1 million in 2018 revenue, $254.8 million in 2019 and $318.4 million in 2020. The company closed 2020 out with a self-calculated $357 million in annual run rate.
During its recent years of growth, DigitalOcean has managed to lose modestly increasing amounts of money, calculated using generally accepted accounting principles (GAAP), and non-GAAP profit (adjusted EBITDA) in rising quantities. Observe the rising disconnect:
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Building a front-end for business applications is often a matter of reinventing the wheel, but because every business’ needs are slightly different, it’s also hard to automate. Kleeen is the latest startup to attempt this, with a focus on building the user interface and experience for today’s data-centric applications. The service, which was founded by a team that previously ran a UI/UX studio in the Bay Area, uses a wizard-like interface to build the routine elements of the app and frees a company’s designers and developers to focus on the more custom elements of an application.
The company today announced that it has raised a $3.8 million seed round led by First Ray Venture Partners. Leslie Ventures, Silicon Valley Data Capital, WestWave Capital, Neotribe Ventures, AI Fund and a group of angel investors also participated in the round. Neotribe also led Kleeen’s $1.6 million pre-seed round, bringing the company’s total funding to $5.3 million.
After the startup he worked at sold, Kleeen co-founder, CPO and President Joshua Hailpern told me, he started his own B2B design studio, which focused on front-end design and engineering.
“What we ended up seeing was the same pattern that would happen over and over again,” he said. “We would go into a client, and they would be like: ‘we have the greatest idea ever. We want to do this, this, this and this.’ And they would tell us all these really cool things and we were: ‘hey, we want to be part of that.’ But then what we would end up doing was not that. Because when building products — there’s the showcase of the product and there’s all these parts that support that product that are necessary but you’re not going to win a deal because someone loved that config screen.”
The idea behind Kleeen is that you can essentially tell the system what you are trying to do and what the users need to be able to accomplish — because at the end of the day, there are some variations in what companies need from these basic building blocks, but not a ton. Kleeen can then generate this user interface and workflow for you — and generate the sample data to make this mock-up come to life.
Once that work is done, likely after a few iterations, Kleeen can generate React code, which development teams can then take and work with directly.
As Kleeen co-founder and CEO Matt Fox noted, the platform explicitly doesn’t want to be everything to everybody.
“In the no-code space, to say that you can build any app probably means that you’re not building any app very well if you’re just going to cover every use case. If someone wants to build a Bumble-style phone app where they swipe right and swipe left and find their next mate, we’re not the application platform for you. We’re focused on really data-intensive workflows.” He noted that Kleeen is at its best when developers use it to build applications that help a company analyze and monitor information and, crucially, take action on that information within the app. It’s this last part that also clearly sets it apart from a standard business intelligence platform.
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Cloud monitoring platform Datadog has announced that it plans to acquire Sqreen, a software-as-a-service security platform. Originally founded in France, Sqreen participated in TechCrunch’s Startup Battlefield in 2016.
Sqreen is a cloud-based security product to protect your application directly. Once you install the sandboxed Sqreen agent, it analyzes your application in real time to find vulnerabilities in your code or your configuration. There’s a small CPU overhead with Sqreen enabled, but there are some upsides.
It can surface threats and you can set up your own threat detection rules. You can see the status of your application from the Sqreen dashboard, receive notifications when there’s an incident and get information about incidents.
For instance, you can see blocked SQL injections, see where the injection attempts came from and act to prevent further attempts. Sqreen also detects common attacks, such as credential stuffing attacks, cross-site scripting, etc. As your product evolves, you can enable different modules from the plugin marketplace.
Combining Datadog and Sqreen makes a lot of sense, as many companies already rely on Datadog to monitor their apps. Sqreen has a good product, Datadog has a good customer base. So you can expect some improvements on the security front for Datadog.
Sqreen raised a $2.3 million round from Alven Capital, Point Nine Capital, Kima Ventures, 50 Partners and business angels. It then participated in TechCrunch’s Startup Battlefield — it made it to the finals but didn’t win the competition. The startup attended Y Combinator a bit later.
In 2019, Sqreen raised a $14 million Series A round led by Greylock Partners with existing investors Y Combinator, Alven and Point Nine participating once again.
Datadog and Sqreen have signed a definitive acquisition agreement. Terms of the deal remain undisclosed and the acquisition should close in Q2 2021.
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One of the most difficult tasks in the increasingly high-fidelity world of gaming is making realistic-looking people — especially faces. Epic today showed off a new character creation tool in Unreal Engine that lets you make a near-infinite variety of near-photorealistic digital people with far less effort than it might have taken before.
MetaHuman Creator is an application for designing characters that lets people mix and match presets then dive into the tiniest details. It’s a cloud-hosted service, since the amount of computing power and storage needed to render these characters at this resolution and level of lighting and so on is more than most people will have on hand.
Anyone who’s used a high-quality character creator will recognize the pieces — a few dozen hairstyles, ear types, beards and lip shapes, which can be added, subtracted and adjusted like a digital Mr. Potato Head. Bet you didn’t see that reference coming!
The difference between MetaHuman and, say, a state of the art consumer-level creator like Cyberpunk 2077’s is fidelity and flexibility. As you can see in the videos, the quality of the hair, skin, eyes, teeth and so on is extremely high — the older fellow on the left has quite realistic wrinkles that shadow and deform properly when he moves his face, and the way the light interacts with the center lady’s light skin is very different from that of the dark-skinned man on the right.
The “center lady” also started as a middle-aged man and was sculpted piece by piece to her current look rather than just switching to a “feminine” preset, demonstrating that the faces don’t “break” if you manipulate them too much — a risk in other creators for sure. You can see the process in fast-forward in the video below:
Naturally it also integrates with the usual creator tools, allowing for animation by various means, fiddling with meshes and exporting for use in other tools.
This level of detail isn’t exactly unprecedented, but the amount of work that goes into rendering a main character good enough for extreme close-ups and microexpressions is huge. Epic’s approach is not just to increase the potential quality of the assets and lighting and so on but to make it easy and efficient to implement. If only AAA studios can muster the resources to make characters like this, it’s not healthy for gaming as a whole.
Epic was humble enough to give credit right off the bat to companies like 3Lateral and Cubic Motion, both specialists in the field it has acquired. The Unreal Engine is presented as a sort of monolithic advance in computer graphics and design, but really it’s a very cleverly assembled amalgamation of dozens of improvements and advances made by individual (now acquired) companies and divisions over the years — more like an operating system with a bunch of integrated applications at this point.
MetaHuman Creator isn’t quite ready for use by just anyone, but Epic is running an early-access program you can sign up for, and they’ve provided a pair of models for you to play with in your existing Unreal Engine environment in the meantime (check the “Learn” tab).
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SLAs, SLOs, SLIs. If there’s one thing everybody in the business of managing software development loves, it’s acronyms. And while everyone probably knows what a Service Level Agreement (SLA) is, Service Level Objectives (SLOs) and Service Level Indicators (SLIs) may not be quite as well known. The idea, though, is straightforward, with SLOs being the overall goals a team must hit to meet the promises of its SLA agreements, and SLIs being the actual measurements that back up those other two numbers. With the advent of DevOps, these ideas, which are typically part of a company’s overall Site Reliability Engineering (SRE) efforts, are becoming more mainstream, but putting them into practice isn’t always straightforward.
Nobl9 aims to provide enterprises with the tools they need to build SLO-centric operations and the right feedback loops inside an organization to help it hit its SLOs without making too many trade-offs between the cost of engineering, feature development and reliability.
The company today announced that it has raised a $21 million Series B round led by its Series A investors Battery Ventures and CRV. In addition, Series A investors Bonfire Ventures and Resolute Ventures also participated, together with new investors Harmony Partners and Sorenson Ventures.
Before starting Nobl9, co-founders Marcin Kurc (CEO) and Brian Singer (CPO) spent time together at Orbitera, where Singer was the co-founder and COO and Kurc the CEO, and then at Google Cloud, after it acquired Orbitera in 2016. In the process, the team got to work with and appreciate Google’s site reliability engineering frameworks.
As they started looking into what to do next, that experience led them to look into productizing these ideas. “We came to this conclusion that if you’re going into Kubernetes, into service-based applications and modern architectures, there’s really no better way to run that than SRE,” Kurc told me. “And when we started looking at this, naturally SRE is a complete framework, there are processes. We started looking at elements of SRE and we agreed that SLO — service level objectives — is really the foundational part. You can’t do SRE without SLOs.”
As Singer noted, in order to adopt SLOs, businesses have to know how to turn the data they have about the reliability of their services, which could be measured in uptime or latency, for example, into the right objectives. That’s complicated by the fact that this data could live in a variety of databases and logs, but the real question is how to define the right SLOs for any given organization based on this data.
“When you go into the conversation with an organization about what their goals are with respect to reliability and how they start to think about understanding if there’s risks to that, they very quickly get bogged down in how are we going to get this data or that data and instrument this or instrument that,” Singer said. “What we’ve done is we’ve built a platform that essentially takes that as the problem that we’re solving. So no matter where the data lives and in what format it lives, we want to be able to reduce it to very simply an error budget and an objective that can be tracked and measured and reported on.”
The company’s platform launched into general availability last week, after a beta that started last year. Early customers include Brex and Adobe.
As Kurc told me, the team actually thinks of this new funding round as a Series A round, but because its $7.5 million Series A was pretty sizable, they decided to call it a Series A instead of a seed round. “It’s hard to define it. If you define it based on a revenue milestone, we’re pre-revenue, we just launched the GA product,” Singer told me. “But I think just in terms of the maturity of the product and the company, I would put us at the [Series] B.”
The team told me that it closed the round at the end of last November, and while it considered pitching new VCs, its existing investors were already interested in putting more money into the company and since its previous round had been oversubscribed, they decided to add to this new round some of the investors that didn’t make the cut for the Series A.
The company plans to use the new funding to advance its roadmap and expand its team, especially across sales, marketing and customer success.
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Google today announced the launch of Apigee X, the next major release of the Apgiee API management platform it acquired back in 2016.
“If you look at what’s happening — especially after the pandemic started in March last year — the volume of digital activities has gone up in every kind of industry, all kinds of use cases are coming up. And one of the things we see is the need for a really high-performance, reliable, global digital transformation platform,” Amit Zavery, Google Cloud’s head of platform, told me.
He noted that the number of API calls has gone up 47% from last year and that the platform now handles about 2.2 trillion API calls per year.
At the core of the updates are deeper integrations with Google Cloud’s AI, security and networking tools. In practice, this means Apigee users can now deploy their APIs across 24 Google Cloud regions, for example, and use Google’s caching services in more than 100 edge locations.
In addition, Apigee X now integrates with Google’s Cloud Armor firewall and its Cloud Identity Access Management platform. This also means that Apigee users won’t have to use third-party tools for their firewall and identity management needs.
“We do a lot of AI/ML-based anomaly detection and operations management,” Zavery explained. “We can predict any kind of malicious intent or any other things which might happen to those API calls or your traffic by embedding a lot of those insights into our API platform. I think [that] is a big improvement, as well as new features, especially in operations management, security management, vulnerability management and making those a core capability so that as a business, you don’t have to worry about all these things. It comes with the core capabilities and that is really where the front doors of digital front-ends can shine and customers can focus on that.”
The platform now also makes better use of Google’s AI capabilities to help users identify anomalies or predict traffic for peak seasons. The idea here is to help customers automate a lot of the standards automation tasks and, of course, improve security at the same time.
As Zavery stressed, API management is now about more than just managing traffic between applications. But more than just helping customers manage their digital transformation projects, the Apigee team is now thinking about what it calls “digital excellence.” “That’s how we’re thinking of the journey for customers moving from not just ‘hey, I can have a front end,’ but what about all the excellent things you want to do and how we can do that,” Zavery said.
“During these uncertain times, organizations worldwide are doubling-down on their API strategies to operate anywhere, automate processes, and deliver new digital experiences quickly and securely,” said James Fairweather, chief innovation officer at Pitney Bowes. “By powering APIs with new capabilities like reCAPTCHA Enterprise, Cloud Armor (WAF), and Cloud CDN, Apigee X makes it easy for enterprises like us to scale digital initiatives, and deliver innovative experiences to our customers, employees and partners.”
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Atlassian has made it clear for some time that it’s all in on the cloud, but now it’s official. The company stopped selling new on-prem server licenses as of yesterday. Perhaps to take away the sting of that move for large organizations, today it announced a new all-inclusive enterprise pricing tier.
Atlassian chief revenue officer Cameron Deatsch says that previously the company had offered a free tier and then standard and premium-level paid tiers. “And now this cloud Enterprise Edition will be our highest tier, and what this will allow is for the most complex deployments, the largest customers who need unlimited scale, the customers that have all the security and regulatory requirements, data residency, you name it, — that is what we’re launching starting [today],” Deatsch told me.
What the enterprise tier delivers is unlimited instances across the Atlassian product line for each enterprise customer. That means a big company with multiple divisions could, for instance, have 20 instances of Jira and Confluence deployed with one for each division and a central management console.
While the company is supporting existing on-prem server customers until 2024, the idea is to now move them to the cloud and this offering should help. One thing we have clearly seen is that the pandemic has accelerated the move to the cloud by companies of every size, and this should encourage the company’s largest customers to make the move.
“The reality is, the demand was there, which was great to see, but we actually had this huge pipeline of our largest customers, basically trying to build their plan over the next couple of years to get to our cloud. The general availability of our Enterprise Edition is going to accelerate that even more,” he said.
It’s a move the company has been working toward for some time, but it really began to take shape when they shifted their operations to AWS and rebuilt the entire stack as a set of microservices beginning in 2016. This was the first step toward being able to handle the increased kinds of workloads an enterprise tier would require.
The company reported earnings at the end of last month with revenue of $501.4 million up 23% YoY with over 11,000 net new subscribers, a record for the company. The new enterprise tier won’t help with new customer volume, but it should help with overall revenue as more customers look for cloud solutions and pricing that meets their needs.
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Pinecone, a new startup from the folks who helped launch Amazon SageMaker, has built a vector database that generates data in a specialized format to help build machine learning applications faster, something that was previously only accessible to the largest organizations. Today the company came out of stealth with a new product and announced a $10 million seed investment led by Wing Venture Capital.
Company co-founder Edo Liberty says that he started the company because of this fundamental belief that the industry was being held back by the lack of wider access to this type of database. “The data that a machine learning model expects isn’t a JSON record, it’s a high dimensional vector that is either a list of features or what’s called an embedding that’s a numerical representation of the items or the objects in the world. This [format] is much more semantically rich and actionable for machine learning,” he explained.
He says that this is a concept that is widely understood by data scientists, and supported by research, but up until now only the biggest and technically superior companies like Google or Pinterest could take advantage of this difference. Liberty and his team created Pinecone to put that kind of technology in reach of any company.
The startup spent the last couple of years building the solution, which consists of three main components. The main piece is a vector engine to convert the data into this machine-learning ingestible format. Liberty says that this is the piece of technology that contains all the data structures and algorithms that allow them to index very large amounts of high dimensional vector data, and search through it in an efficient and accurate way.
The second is a cloud hosted system to apply all of that converted data to the machine learning model, while handling things like index lookups along with the pre- and post-processing — everything a data science team needs to run a machine learning project at scale with very large workloads and throughputs. Finally, there is a management layer to track all of this and manage data transfer between source locations.
One classic example Liberty uses is an eCommerce recommendation engine. While this has been a standard part of online selling for years, he believes using a vectorized data approach will result in much more accurate recommendations and he says the data science research data bears him out.
“It used to be that deploying [something like a recommendation engine] was actually incredibly complex, and […] if you have access to a production grade database, 90% of the difficulty and heavy lifting in creating those solutions goes away, and that’s why we’re building this. We believe it’s the new standard,” he said.
The company currently has 10 people including the founders, but the plan is to double or even triple that number, depending on how the year goes. As he builds his company as an immigrant founder — Liberty is from Israel — he says that diversity is top of mind. He adds that it’s something he worked hard on at his previous positions at Yahoo and Amazon as he was building his teams at those two organizations. One way he is doing that is in the recruitment process. “We have instructed our recruiters to be proactive [in finding more diverse applicants], making sure they don’t miss out on great candidates, and that they bring us a diverse set of candidates,” he said.
Looking ahead to post-pandemic, Liberty says he is a bit more traditional in terms of office versus home, and that he hopes to have more in-person interactions. “Maybe I’m old fashioned but I like offices and I like people and I like to see who I work with and hang out with them and laugh and enjoy each other’s company, and so I’m not jumping on the bandwagon of ‘let’s all be remote and work from home’.”
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Datastax, the company best known for commercializing the open-source Apache Cassandra database, is moving beyond databases. As the company announced today, it has acquired Kesque, a cloud messaging service.
The Kesque team built its service on top of the Apache Pulsar messaging and streaming project. Datastax has now taken that team’s knowledge in this area and, combined with its own expertise, is launching its own Pulsar-based streaming platform by the name of Datastax Luna Streaming, which is now generally available.
This move comes right as Datastax is also now, for the first time, announcing that it is cash-flow positive and profitable, as the company’s chief product officer, Ed Anuff, told me. “We are at over $150 million in [annual recurring revenue]. We are cash-flow positive and we are profitable,” he told me. This marks the first time the company is publically announcing this data. In addition, the company also today revealed that about 20 percent of its annual contract value is now for DataStax Astra, its managed multi-cloud Cassandra service and that the number of self-service Asta subscribers has more than doubled from Q3 to Q4.
The launch of Luna Streaming now gives the 10-year-old company a new area to expand into — and one that has some obvious adjacencies with its existing product portfolio.
“We looked at how a lot of developers are building on top of Cassandra,” Anuff, who joined Datastax after leaving Google Cloud last year, said. “What they’re doing is, they’re addressing what people call ‘data-in-motion’ use cases. They have huge amounts of data that are coming in, huge amounts of data that are going out — and they’re typically looking at doing something with streaming in conjunction with that. As we’ve gone in and asked, “What’s next for Datastax?,’ streaming is going to be a big part of that.”
Given Datastax’s open-source roots, it’s no surprise the team decided to build its service on another open-source project and acquire an open-source company to help it do so. Anuff noted that while there has been a lot of hype around streaming and Apache Kafka, a cloud-native solution like Pulsar seemed like the better solution for the company. Pulsar was originally developed at Yahoo! (which, full disclosure, belongs to the same Verizon Media Group family as TechCrunch) and even before acquiring Kesque, Datastax already used Pulsar to build its Astra platform. Other Pulsar users include Yahoo, Tencent, Nutanix and Splunk.
“What we saw was that when you go and look at doing streaming in a scale-out way, that Kafka isn’t the only approach. We looked at it, and we liked the Pulsar architecture, we like what’s going on, we like the community — and remember, we’re a company that grew up in the Apache open-source community — we said, ‘okay, we think that it’s got all the right underpinnings, let’s go and get involved in that,” Anuff said. And in the process of doing so, the team came across Kesque founder Chris Bartholomew and eventually decided to acquire his company.
The new Luna Streaming offering will be what Datastax calls a “subscription to success with Apache Pulsar.’ It will include a free, production-ready distribution of Pulsar and an optional, SLA-backed subscription tier with enterprise support.
Unsurprisingly, Datastax also plans to remain active in the Pulsar community. The team is already making code contributions, but Anuff also stressed that Datastax is helping out with scalability testing. “This is one of the things that we learned in our participation in the Apache Cassandra project,” Anuff said. “A lot of what these projects need is folks coming in doing testing, helping with deployments, supporting users. Our goal is to be a great participant in the community.”
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