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Atlassian Smarts adds machine learning layer across the company’s platform of services
Atlassian has been offering collaboration tools, often favored by developers and IT for some time with such stalwarts as Jira for help desk tickets, Confluence to organize your work and BitBucket to organize your development deliverables, but what it lacked was a machine learning layer across the platform to help users work smarter within and across the applications in the Atlassian family.
That changed today, when Atlassian announced it has been building that machine learning layer, called Atlassian Smarts, and is releasing several tools that take advantage of it. It’s worth noting that unlike Salesforce, which calls its intelligence layer Einstein or Adobe, which calls its Sensei, Atlassian chose to forgo the cutesy marketing terms and just let the technology stand on its own.
Shihab Hamid, the founder of the Smarts and Machine Learning Team at Atlassian, who has been with the company 14 years, says they avoided a marketing name by design. “I think one of the things that we’re trying to focus on is actually the user experience and so rather than packaging or branding the technology, we’re really about optimizing teamwork,” Hamid told TechCrunch.
Hamid says that the goal of the machine learning layer is to remove the complexity involved with organizing people and information across the platform.
“Simple tasks like finding the right person or the right document becomes a challenge, or at least they slow down productivity and take time away from the creative high-value work that everyone wants to be doing, and teamwork itself is super messy and collaboration is complicated. These are human challenges that don’t really have one right solution,” he said.
He says that Atlassian has decided to solve these problems using machine learning with the goal of speeding up repetitive, time-intensive tasks. Much like Adobe or Salesforce, Atlassian has built this underlying layer of machine smarts, for lack of a better term, that can be distributed across their platform to deliver this kind of machine learning-based functionality wherever it makes sense for the particular product or service.
“We’ve invested in building this functionality directly into the Atlassian platform to bring together IT and development teams to unify work, so the Atlassian flagship products like JIRA and Confluence sit on top of this common platform and benefit from that common functionality across products. And so the idea is if we can build that common predictive capability at the platform layer we can actually proliferate smarts and benefit from the data that we gather across our products,” Hamid said.
The first pieces fit into this vision. For starters, Atlassian is offering a smart search tool that helps users find content across Atlassian tools faster by understanding who you are and how you work. “So by knowing where users work and what they work on, we’re able to proactively provide access to the right documents and accelerate work,” he said.
The second piece is more about collaboration and building teams with the best personnel for a given task. A new tool called predictive user mentions helps Jira and Confluence users find the right people for the job.
“What we’ve done with the Atlassian platform is actually baked in that intelligence, because we know what you work on and who you collaborate with, so we can predict who should be involved and brought into the conversation,” Hamid explained.
Finally, the company announced a tool specifically for Jira users, which bundles together similar sets of help requests and that should lead to faster resolution over doing them manually one at a time.
“We’re soon launching a feature in JIRA Service Desk that allows users to cluster similar tickets together, and operate on them to accelerate IT workflows, and this is done in the background using ML techniques to calculate the similarity of tickets, based on the summary and description, and so on.”
All of this was made possible by the company’s previous shift from mostly on-premises to the cloud and the flexibility that gave them to build new tooling that crosses the entire platform.
Today’s announcements are just the start of what Atlassian hopes will be a slew of new machine learning-fueled features being added to the platform in the coming months and years.
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Turbo Systems becomes Appify and launches app marketplace
When Jen Grant joined Turbo Systems, the no-code mobile application platform, as CEO in March, she came on board just as COVID was shutting down businesses. But she went straight to work, and over the last six months she has led two major initiatives that the company announced today: a name change and a new app marketplace.
For starters, the company is changing its name to Appify to more accurately reflect its mission around building mobile apps. She says that they found most people related the term “turbo” to cars. They began looking for a better name that was more closely aligned with what they do when her team stumbled across Appify .
“We had been playing around with different names and what we are about, and a lot of what we’re about is amplifying your business and your systems and your people with apps. And so when we kind of stumbled across Appify and the domain name was available, we moved quite quickly,” Grant explained.
While she was at it, Grant was talking to customers, and while the core company mission is to make it easy to build mobile apps, especially in the field service space, she felt that they could make it even easier. Rather than asking customers to build the apps themselves, they could provide a marketplace with some pre-built apps and simply let them customize them for their workflows.
“What we have done with the Appify Marketplace is instead of saying, here’s a box of parts, now fix your business problem, we’re saying, here’s an app that you can launch in minutes. It has all of the functionality that you will need […] and you can then very easily customize it using this no-code platform to make it specific to your business,” she said.
The marketplace is launching today with a couple of apps aimed at the company’s core field service market, including Field Sales, which allows salespeople in the field to send a bid or quote from a tablet directly from the field without having to return to the office. The other is a Field Service app for repair people, which provides all of the information about the repair, while allowing the service rep to update the customer record from the field using a mobile device.
Grant says this is just the start and there are many apps on the road map that they will be releasing in the coming months. Eventually, they may have systems integrators use the platform to build apps for specific industries as they move forward.
Appify was born as Turbo Systems in 2017 and has raised more than $11 million, according to PitchBook data.
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Armory nabs $40M Series C as commercial biz on top of open-source Spinnaker project takes off
As companies continue to shift more quickly to the cloud, pushed by the pandemic, startups like Armory that work in the cloud-native space are seeing an uptick in interest. Armory is a company built to be a commercial layer on top of the open-source continuous delivery project Spinnaker. Today, it announced a $40 million Series C.
B Capital led the round, with help from new investors Lead Edge Capital and Marc Benioff along with previous investors Insight Partners, Crosslink Capital, Bain Capital Ventures, Mango Capital, Y Combinator and Javelin Venture Partners. Today’s investment brings the total raised to more than $82 million.
“Spinnaker is an open-source project that came out of Netflix and Google, and it is a very sophisticated multi-cloud and software delivery platform,” company co-founder and CEO Daniel R. Odio told TechCrunch.
Odio points out that this project has the backing of industry leaders, including the three leading public cloud infrastructure vendors Amazon, Microsoft and Google, as well as other cloud players like CloudFoundry and HashiCorp. “The fact that there is a lot of open-source community support for this project means that it is becoming the new standard for cloud-native software delivery,” he said.
In the days before the notion of continuous delivery, companies moved forward slowly, releasing large updates over months or years. As software moved to the cloud, this approach no longer made sense and companies began delivering updates more incrementally, adding features when they were ready. Adding a continuous delivery layer helped facilitate this move.
As Odio describes it, Armory extends the Spinnaker project to help implement complex use cases at large organizations, including around compliance and governance and security. It is also in the early stages of implementing a SaaS version of the solution, which should be available next year.
While he didn’t want to discuss customer numbers, he mentioned JPMorgan Chase and Autodesk as customers, along with less specific allusions to “a Fortune Five technology company, a Fortune 20 Bank, a Fortune 50 retailer and a Fortune 100 technology company.”
The company currently has 75 employees, but Odio says business has been booming and he plans to double the team in the next year. As he does, he says that he is deeply committed to diversity and inclusion.
“There’s actually a really big difference between diversity and inclusion, and there’s a great Vernā Myers quote that diversity is being asked to the party and inclusion is being asked to dance, and so it’s actually important for us not only to focus on diversity, but also focus on inclusion because that’s how we win. By having a heterogeneous company, we will outperform a homogeneous company,” he said.
While the company has moved to remote work during COVID, Odio says they intend to remain that way, even after the current crisis is over. “Now obviously COVID been a real challenge for the world, including us. We’ve gone to a fully remote-first model, and we are going to stay remote-first even after COVID. And it’s really important for us to be taking care of our people, so there’s a lot of human empathy here,” he said.
But at the same time, he sees COVID opening up businesses to move to the cloud and that represents an opportunity for his business, one that he will focus on with new capital at his disposal. “In terms of the business opportunity, we exist to help power the transformation that these enterprises are undergoing right now, and there’s a lot of urgency for us to execute on our vision and mission because there is a lot of demand for this right now,” he said.
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Twilio’s $3.2B Segment acquisition is about helping developers build data-fueled apps
The pandemic has forced businesses to change the way they interact with customers. Whether it’s how they deliver goods and services, or how they communicate, there is one common denominator, and that’s that everything is being forced to be digitally driven much faster.
To some extent, that’s what drove Twilio to acquire Segment for $3.2 billion today. (We wrote about the deal over the weekend. Forbes broke the story last Friday night.) When you get down to it, the two companies fit together well, and expand the platform by giving Twilio customers access to valuable customer data. Chee Chew, Twilio’s chief product officer, says while it may feel like the company is pivoting in the direction of customer experience, they don’t necessarily see it that way.
“A lot of people have thought about us as a communications company, but we think of ourselves as a customer engagement company. We really think about how we help businesses communicate more effectively with their customers,” Chew told TechCrunch.
Laurie McCabe, co-founder and partner at SMB Group, sees the move related to the pandemic and the need companies have to serve customers in a more fully digital way. “More customers are realizing that delivering a great customer experience is key to survive through the pandemic, and thriving as the economy recovers — and are willing to spend to do this even in uncertain times,” McCabe said.
Certainly Chew recognized that Segment gives them something they were lacking by providing developers with direct access to customer data, and that could lead to some interesting applications.
“The data capabilities that Segment has are providing a full view of the customer. It really layers across everything we do. I think of it as a horizontal add across the channels and extending beyond. So I think it really helps us advance in a different sort of way […] towards getting the holistic view of the customer and enabling our customers to build intelligence services on top,” he said.
Brent Leary, founder and principal analyst at CRM Essentials, sees Segment helping to provide a powerful data-fueled developer experience. “This move allows Twilio to impact the data-insight-interaction-experience transformation process by removing friction from developers using their platform,” Leary explained. In other words, it gives developers that ability that Chew alluded to, to use data to build more varied applications using Twilio APIs.
Paul Greenberg, author of CRM at the Speed of Light, and founder and principal analyst at 56 Group, agrees, saying, “Segment gives Twilio the ability to use customer data in what is already a powerful unified communications platform and hub. And since it is, in effect, APIs for both, the flexibility [for developers] is enormous,” he said.
That may be so, but Holger Mueller, an analyst at Constellation Research, says the company has to be seeing that the pure communication parts of the platform like SMS are becoming increasingly commoditized, and this deal, along with the SendGrid acquisition in 2018, gives Twilio a place to expand its platform into a much more lucrative data space.
“Twilio needs more growth path and it looks like its strategy is moving up the stack, at least with the acquisition of Segment. Data movement and data residence compliance is a huge headache for enterprises when they build their next generation applications,” Mueller said.
As Chew said, early on the problems were related to building SMS messages into applications and that was the problem that Twilio was trying to solve because that’s what developers needed at the time, but as it moves forward, it wants to provide a more unified customer communications experience, and Segment should help advance that capability in a big way for them.
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Twilio is buying customer data startup Segment for between $3B and $4B
Sources have told TechCrunch that Twilio intends to acquire customer data startup Segment for between $3 and $4 billion. Forbes broke the story on Friday night, reporting a price tag of $3.2 billion.
We have heard from a couple of industry sources that the deal is in the works and could be announced as early as Monday.
Twilio and Segment are both API companies. That means they create an easy way for developers to tap into a specific type of functionality without writing a lot of code. As I wrote in a 2017 article on Segment, it provides a set of APIs to pull together customer data from a variety of sources:
Segment has made a name for itself by providing a set of APIs that enable it to gather data about a customer from a variety of sources like your CRM tool, customer service application and website and pull that all together into a single view of the customer, something that is the goal of every company in the customer information business.
While Twilio’s main focus since it launched in 2008 has been on making it easy to embed communications functionality into any app, it signaled a switch in direction when it released the Flex customer service API in March 2018. Later that same year, it bought SendGrid, an email marketing API company for $2 billion.
Twilio’s market cap as of Friday was an impressive $45 billion. You could see how it can afford to flex its financial muscles to combine Twilio’s core API mission, especially Flex, with the ability to pull customer data with Segment and create customized email or ads with SendGrid.
This could enable Twilio to expand beyond pure core communications capabilities and it could come at the cost of around $5 billion for the two companies, a good deal for what could turn out to be a substantial business as more and more companies look for ways to understand and communicate with their customers in more relevant ways across multiple channels.
As Semil Shah from early stage VC firm Haystack wrote in the company blog yesterday, Segment saw a different way to gather customer data, and Twilio was wise to swoop in and buy it.
Segment’s belief was that a traditional CRM wasn’t robust enough for the enterprise to properly manage its pipe. Segment entered to provide customer data infrastructure to offer a more unified experience. Now under the Twilio umbrella, Segment can continue to build key integrations (like they have for Twilio data), which is being used globally inside Fortune 500 companies already.
Segment was founded in 2011 and raised over $283 million, according to Crunchbase data. Its most recent raise was $175 million in April on a $1.5 billion valuation.
Twilio stock closed at $306.24 per share on Friday up $2.39%.
Segment declined to comment on this story. We also sent a request for comment to Twilio, but hadn’t heard back by the time we published. If that changes, we will update the story.
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How Roblox completely transformed its tech stack
Picture yourself in the role of CIO at Roblox in 2017.
At that point, the gaming platform and publishing system that launched in 2005 was growing fast, but its underlying technology was aging, consisting of a single data center in Chicago and a bunch of third-party partners, including AWS, all running bare metal (nonvirtualized) servers. At a time when users have precious little patience for outages, your uptime was just two nines, or less than 99% (five nines is considered optimal).
Unbelievably, Roblox was popular in spite of this, but the company’s leadership knew it couldn’t continue with performance like that, especially as it was rapidly gaining in popularity. The company needed to call in the technology cavalry, which is essentially what it did when it hired Dan Williams in 2017.
Williams has a history of solving these kinds of intractable infrastructure issues, with a background that includes a gig at Facebook between 2007 and 2011, where he worked on the technology to help the young social network scale to millions of users. Later, he worked at Dropbox, where he helped build a new internal network, leading the company’s move away from AWS, a major undertaking involving moving more than 500 petabytes of data.
When Roblox approached him in mid-2017, he jumped at the chance to take on another major infrastructure challenge. While they are still in the midst of the transition to a new modern tech stack today, we sat down with Williams to learn how he put the company on the road to a cloud-native, microservices-focused system with its own network of worldwide edge data centers.
Scoping the problem
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Grid AI raises $18.6M Series A to help AI researchers and engineers bring their models to production
Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers work more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute.
Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.
The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.
“Now the industry has an unhealthy aversion to deep learning because of this,” Falcon noted. “Lightning and Grid embed all those tricks into the workflow so you no longer need to be a PhD in AI nor [have] the resources of the major AI companies to get these things to work. This makes the opportunity cost of putting a simple model against a sophisticated neural network a few hours’ worth of effort instead of the months it used to take. When you use Lightning and Grid it’s hard to make mistakes. It’s like if you take a bad photo with your phone but we are the phone and make that photo look super professional AND teach you how to get there on your own.”
As Falcon noted, Grid is meant to help data scientists and other ML professionals “scale to match the workloads required for enterprise use cases.” Lightning itself can get them partially there, but Grid is meant to provide all of the services its users need to scale up their models to solve real-world problems.
What exactly that looks like isn’t quite clear yet, though. “Imagine you can find any GitHub repository out there. You get a local copy on your laptop and without making any code changes you spin up 400 GPUs on AWS — all from your laptop using either a web app or command-line-interface. That’s the Lightning “magic” applied to training and building models at scale,” Falcon said. “It is what we are already known for and has proven to be such a successful paradigm shift that all the other frameworks like Keras or TensorFlow, and companies have taken notice and have started to modify what they do to try to match what we do.”
The service is now in private beta.
With this new funding, Grid, which currently has 25 employees, plans to expand its team and strengthen its corporate offering via both Grid AI and through the open-source project. Falcon tells me that he aims to build a diverse team, not in the least because he himself is an immigrant, born in Venezuela, and a U.S. military veteran.
“I have first-hand knowledge of the extent that unethical AI can have,” he said. “As a result, we have approached hiring our current 25 employees across many backgrounds and experiences. We might be the first AI company that is not all the same Silicon Valley prototype tech-bro.”
“Lightning’s open-source traction piqued my interest when I first learned about it a year ago,” Index Ventures’ Sarah Cannon told me. “So intrigued in fact I remember rushing into a closet in Helsinki while at a conference to have the privacy needed to hear exactly what Will and Luis had built. I promptly called my colleague Bryan Offutt who met Will and Luis in SF and was impressed by the ‘elegance’ of their code. We swiftly decided to participate in their seed round, days later. We feel very privileged to be part of Grid’s journey. After investing in seed, we spent a significant amount with the team, and the more time we spent with them the more conviction we developed. Less than a year later and pre-launch, we knew we wanted to lead their Series A.”
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Kong launches Kong Konnect, its cloud-native connectivity platform
At its (virtual) Kong Summit 2020, API platform Kong today announced the launch of Kong Konnect, its managed end-to-end cloud-native connectivity platform. The idea here is to give businesses a single service that allows them to manage the connectivity between their APIs and microservices and help developers and operators manage their workflows across Kong’s API Gateway, Kubernetes Ingress and Kong Service Mesh runtimes.
“It’s a universal control plane delivery cloud that’s consumption-based, where you can manage and orchestrate API gateway runtime, service mesh runtime, and Kubernetes Ingress controller runtime — and even Insomnia for design — all from one platform,” Kong CEO and co-founder Augusto “Aghi” Marietti told me.
The new service is now in private beta and will become generally available in early 2021.
Image Credits: Kong
At the core of the platform is Kong’s new so-called ServiceHub, which provides that single pane of glass for managing a company’s services across the organization (and make them accessible across teams, too).
As Marietti noted, organizations can choose which runtime they want to use and purchase only those capabilities of the service that they currently need. The platform also includes built-in monitoring tools and supports any cloud, Kubernetes provider or on-premises environment, as long as they are Kubernetes-based.
The idea here, too, is to make all these tools accessible to developers and not just architects and operators. “I think that’s a key advantage, too,” Marietti said. “We are lowering the barrier by making a connectivity technology easier to be used by the 50 million developers — not just by the architects that were doing big grand plans at a large company.”
To do this, Konnect will be available as a self-service platform, reducing the friction of adopting the service.
Image Credits: Kong
This is also part of the company’s grander plan to go beyond its core API management services. Those services aren’t going away, but they are now part of the larger Kong platform. With its open-source Kong API Gateway, the company built the pathway to get to this point, but that’s a stable product now and it’s now clearly expanding beyond that with this cloud connectivity play that takes the company’s existing runtimes and combines them to provide a more comprehensive service.
“We have upgraded the vision of really becoming an end-to-end cloud connectivity company,” Marietti said. “Whether that’s API management or Kubernetes Ingress, […] or Kuma Service Mesh. It’s about connectivity problems. And so the company uplifted that solution to the enterprise.”
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Adobe beefs up developer tools to make it easer to build apps on Experience Cloud
Adobe has had a developer program for years called Adobe.io, but today at the Adobe Developers Live virtual conference, the company announced some new tools with a fresh emphasis on helping developers build custom apps on the Adobe Experience Cloud.
Jason Woosley, VP of developer experience and commerce at Adobe, says that the pandemic has forced companies to build enhanced digital experiences much more quickly than they might have, and the new tools being announced today are at least partly related to helping speed up the development of better online experiences.
“Our focus is very specifically on making the experience-generation business something that’s very attractive to developers and very accessible to developers so we’re announcing a number of tools,” Woosley told TechCrunch.
The idea is to build a more complete framework over time to make it easier to build applications and connect to data sources that take advantage of the Experience Cloud tooling. For starters, Project Firefly is designed to help developers build applications more quickly by providing a higher level of automation than was previously available.
“Project Firefly creates an extensibility framework that reduces the boilerplate that a developer would need to get started working with the Experience Cloud, and extends that into the customizations that we know every implementation eventually needs to differentiate the storefront experience, the website experience or whatever customer touch point as these things become increasingly digital,” he said.
In order to make those new experiences open to all, the company is also announcing React Spectrum, an open source set of libraries and tools designed to help members of the Adobe developer community build more accessible applications and websites.
“It comes with all of the accessibility features that often get forgotten when you’re in a race to market, so it’s nice to make sure that you will be very inclusive with your design, making sure that you’re bringing on all aspects of your audiences,” Woosley said.
Finally, a big part of interacting with Experience Cloud is taking advantage of all of the data that’s available to help build those more customized interactions with customers that having that data enables. To that end, the company is announcing some new web and mobile software development kits (SDKs) designed to help make it simpler to link to Experience Cloud data sources as you build your applications.
Project Firefly is available in developer preview starting today. Several React Spectrum components and some data connection SDKs are also available today. The company intends to keep adding to these various pieces in the coming months.
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Five years after creating Traefik application proxy, open-source project hits 2B downloads
Five years ago, Traefik Labs founder and CEO Emile Vauge was working on a project deploying thousands of microservices and he was lacking a cloud-native application proxy that could handle this kind of scale. So like any good developer, he created one himself, and Traefik was born.
If you go back five years, the notion of cloud native was still in its infancy. Docker has been doing containers for just a couple of years, and Kubernetes would only be released that year. There wasn’t much cloud-native tooling around, so Vauge decided to build a cloud-native reverse proxy out of pure necessity.
“At that time, five years ago, there was no reverse proxy that was good at managing the complexity of microservices at cloud scale. So that was really the origin of Traefik. And one of the big innovations was its automation and its simplicity,” he said.
As he explained it, a reverse proxy needs to have several features, like traffic management, load balancing, observability and security, but much of this had to be done manually with the tools available at the time. As it turns out, Vauge had stumbled onto a major pain point.
“Initially I created Traefik for myself. It was a side project but it turned out that there was a huge interest and very quickly a community gathered around the project,” he said. After a few months, he realized he could build a company around this and left his job to start a company called Containous.
Today, he changed the name of that company to Traefik Labs and the open-source project he developed has become wildly popular. “Five years later we are at 2 billion downloads. It’s in the top 10 most downloaded projects on Docker. We have 30,000 stars on GitHub. So basically it’s one of the largest open-source projects in the world,” he said. In addition, he said there are more than 550 individuals contributing to the project today.
When he formed Containous, he developed an open core-based commercial project designed for enterprise needs around scaling, high availability and more security features. Today, that includes the Traefik Proxy and an open-source service mesh called Traefik Mesh.
Among the companies using the open-source project today are Conde Nast, eBay Classifieds and Mailchimp.
Vauge certainly was in the right place at the right time five years ago, which he modestly attributes to luck because he was working at one of the few companies at the time that was dealing with microservices at scale. “We had to build a lot of things, and Traefik was one of those things. So I was basically lucky because I created Traefik at the right time,” he said.
Not surprisingly, a company with that kind of open-source traction has attracted the interest of venture capitalists, and Vauge has raised $16 million since he launched his company in 2015, including $10 million led by Balderton Capital in January.
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