Kubernetes
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Google Cloud puts its Kubernetes Engine on autopilot
Google Cloud today announced a new operating mode for its Kubernetes Engine (GKE) that turns over the management of much of the day-to-day operations of a container cluster to Google’s own engineers and automated tools. With Autopilot, as the new mode is called, Google manages all of the Day 2 operations of managing these clusters and their nodes, all while implementing best practices for operating and securing them.
This new mode augments the existing GKE experience, which already managed most of the infrastructure of standing up a cluster. This “standard” experience, as Google Cloud now calls it, is still available and allows users to customize their configurations to their heart’s content and manually provision and manage their node infrastructure.
Drew Bradstock, the group product manager for GKE, told me that the idea behind Autopilot was to bring together all of the tools that Google already had for GKE and bring them together with its SRE teams who know how to run these clusters in production — and have long done so inside of the company.
“Autopilot stitches together auto-scaling, auto-upgrades, maintenance, Day 2 operations and — just as importantly — does it in a hardened fashion,” Bradstock noted. “[ … ] What this has allowed our initial customers to do is very quickly offer a better environment for developers or dev and test, as well as production, because they can go from Day Zero and the end of that five-minute cluster creation time, and actually have Day 2 done as well.”
Image Credits: Google
From a developer’s perspective, nothing really changes here, but this new mode does free up teams to focus on the actual workloads and less on managing Kubernetes clusters. With Autopilot, businesses still get the benefits of Kubernetes, but without all of the routine management and maintenance work that comes with that. And that’s definitely a trend we’ve been seeing as the Kubernetes ecosystem has evolved. Few companies, after all, see their ability to effectively manage Kubernetes as their real competitive differentiator.
All of that comes at a price, of course, in addition to the standard GKE flat fee of $0.10 per hour and cluster (there’s also a free GKE tier that provides $74.40 in billing credits), plus additional fees for resources that your clusters and pods consume. Google offers a 99.95% SLA for the control plane of its Autopilot clusters and a 99.9% SLA for Autopilot pods in multiple zones.
Image Credits: Google
Autopilot for GKE joins a set of container-centric products in the Google Cloud portfolio that also include Anthos for running in multicloud environments and Cloud Run, Google’s serverless offering. “[Autopilot] is really [about] bringing the automation aspects in GKE we have for running on Google Cloud, and bringing it all together in an easy-to-use package, so that if you’re newer to Kubernetes, or you’ve got a very large fleet, it drastically reduces the amount of time, operations and even compute you need to use,” Bradstock explained.
And while GKE is a key part of Anthos, that service is more about brining Google’s config management, service mesh and other tools to an enterprise’s own data center. Autopilot of GKE is, at least for now, only available on Google Cloud.
“On the serverless side, Cloud Run is really, really great for an opinionated development experience,” Bradstock added. “So you can get going really fast if you want an app to be able to go from zero to 1,000 and back to zero — and not worry about anything at all and have it managed entirely by Google. That’s highly valuable and ideal for a lot of development. Autopilot is more about simplifying the entire platform people work on when they want to leverage the Kubernetes ecosystem, be a lot more in control and have a whole bunch of apps running within one environment.”
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Container security acquisitions increase as companies accelerate shift to cloud
Last week, another container security startup came off the board when Rapid7 bought Alcide for $50 million. The purchase is part of a broader trend in which larger companies are buying up cloud-native security startups at a rapid clip. But why is there so much M&A action in this space now?
Palo Alto Networks was first to the punch, grabbing Twistlock for $410 million in May 2019. VMware struck a year later, snaring Octarine. Cisco followed with PortShift in October and Red Hat snagged StackRox last month before the Rapid7 response last week.
This is partly because many companies chose to become cloud-native more quickly during the pandemic. This has created a sharper focus on security, but it would be a mistake to attribute the acquisition wave strictly to COVID-19, as companies were shifting in this direction pre-pandemic.
It’s also important to note that security startups that cover a niche like container security often reach market saturation faster than companies with broader coverage because customers often want to consolidate on a single platform, rather than dealing with a fragmented set of vendors and figuring out how to make them all work together.
Containers provide a way to deliver software by breaking down a large application into discrete pieces known as microservices. These are packaged and delivered in containers. Kubernetes provides the orchestration layer, determining when to deliver the container and when to shut it down.
This level of automation presents a security challenge, making sure the containers are configured correctly and not vulnerable to hackers. With myriad switches this isn’t easy, and it’s made even more challenging by the ephemeral nature of the containers themselves.
Yoav Leitersdorf, managing partner at YL Ventures, an Israeli investment firm specializing in security startups, says these challenges are driving interest in container startups from large companies. “The acquisitions we are seeing now are filling gaps in the portfolio of security capabilities offered by the larger companies,” he said.
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Rapid7 acquires Kubernetes security startup Alcide for $50M
Boston-based security operations company Rapid7 has been making moves into the cloud recently, and this morning it announced that it has acquired Kubernetes security startup Alcide for $50 million.
As the world shifts to cloud native using Kubernetes to manage containerized workloads, it’s tricky ensuring that the containers are configured correctly to keep them safe. What’s more, Kubernetes is designed to automate the management of containers, taking humans out of the loop and making it even more imperative that the security protocols are applied in an automated fashion as well.
Brian Johnson, SVP of Cloud Security at Rapid7 says that this requires a specialized kind of security product and that’s why his company is buying Alcide. “Companies operating in the cloud need to be able to identify and respond to risk in real time, and looking at cloud infrastructure or containers independently simply doesn’t provide enough context to truly understand where you are vulnerable,” he explained.
“With the addition of Alcide, we can help organizations obtain comprehensive, unified visibility across their entire cloud infrastructure and cloud-native applications so that they can continue to rapidly innovate while still remaining secure,” he added.
Today’s purchase builds on the company’s acquisition of DivvyCloud last April for $145 million. That’s almost $200 million for the two companies that allow Rapid7 to help protect cloud workloads in a fairly broad way.
It’s also part of an industry trend with a number of Kubernetes security startups coming off the board in the last year as bigger companies look to enhance their container security chops by buying talent and technology. This includes VMware nabbing Octarine last May, Cisco getting PortShift in October and Red Hat buying StackRox last month.
Alcide was founded in 2016 in Tel Aviv, part of the active Israeli security startup scene. It raised about $12 million along the way, according to Crunchbase data.
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Run:AI raises $30M Series B for its AI compute platform
Run:AI, a Tel Aviv-based company that helps businesses orchestrate and optimize their AI compute infrastructure, today announced that it has raised a $30 million Series B round. The new round was led by Insight Partners, with participation from existing investors TLV Partners and S Capital. This brings the company’s total funding to date to $43 million.
At the core of Run:AI’s platform is the ability to effectively virtualize and orchestrate AI workloads on top of its Kubernetes-based scheduler. Traditionally, it was always hard to virtualize GPUs, so even as demand for training AI models has increased, a lot of the physical GPUs often set idle for long periods because it was hard to dynamically allocate them between projects.
Image Credits: Run.AI
The promise behind Run:AI’s platform is that it allows its users to abstract away all of the AI infrastructure and pool all of their GPU resources — no matter whether in the cloud or on-premises. This also makes it easier for businesses to share these resources between users and teams. In the process, IT teams also get better insights into how their compute resources are being used.
“Every enterprise is either already rearchitecting themselves to be built around learning systems powered by AI, or they should be,” said Lonne Jaffe, managing director at Insight Partners and now a board member at Run:AI.” Just as virtualization and then container technology transformed CPU-based workloads over the last decades, Run:AI is bringing orchestration and virtualization technology to AI chipsets such as GPUs, dramatically accelerating both AI training and inference. The system also future-proofs deep learning workloads, allowing them to inherit the power of the latest hardware with less rework. In Run:AI, we’ve found disruptive technology, an experienced team and a SaaS-based market strategy that will help enterprises deploy the AI they’ll need to stay competitive.”
Run:AI says that it is currently working with customers in a wide variety of industries, including automotive, finance, defense, manufacturing and healthcare. These customers, the company says, are seeing their GPU utilization increase from 25 to 75% on average.
“The new funds enable Run:AI to grow the company in two important areas: first, to triple the size of our development team this year,” the company’s CEO Omri Geller told me. “We have an aggressive roadmap for building out the truly innovative parts of our product vision — particularly around virtualizing AI workloads — a bigger team will help speed up development in this area. Second, a round this size enables us to quickly expand sales and marketing to additional industries and markets.”
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RedHat is acquiring container security company StackRox
RedHat today announced that it’s acquiring container security startup StackRox . The companies did not share the purchase price.
RedHat, which is perhaps best known for its enterprise Linux products has been making the shift to the cloud in recent years. IBM purchased the company in 2018 for a hefty $34 billion and has been leveraging that acquisition as part of a shift to a hybrid cloud strategy under CEO Arvind Krishna.
The acquisition fits nicely with RedHat OpenShift, its container platform, but the company says it will continue to support StackRox usage on other platforms including AWS, Azure and Google Cloud Platform. This approach is consistent with IBM’s strategy of supporting multicloud, hybrid environments.
In fact, Red Hat president and CEO Paul Cormier sees the two companies working together well. “Red Hat adds StackRox’s Kubernetes-native capabilities to OpenShift’s layered security approach, furthering our mission to bring product-ready open innovation to every organization across the open hybrid cloud across IT footprints,” he said in a statement.
CEO Kamal Shah, writing in a company blog post announcing the acquisition, explained that the company made a bet a couple of years ago on Kubernetes and it has paid off. “Over two and half years ago, we made a strategic decision to focus exclusively on Kubernetes and pivoted our entire product to be Kubernetes-native. While this seems obvious today; it wasn’t so then. Fast forward to 2020 and Kubernetes has emerged as the de facto operating system for cloud-native applications and hybrid cloud environments,” Shah wrote.
Shah sees the purchase as a way to expand the company and the road map more quickly using the resources of Red Hat (and IBM), a typical argument from CEOs of smaller acquired companies. But the trick is always finding a way to stay relevant inside such a large organization.
StackRox’s acquisition is part of some consolidation we have been seeing in the Kubernetes space in general and the security space more specifically. That includes Palo Alto Networks acquiring competitor TwistLock for $410 million in 2019. Another competitor, Aqua Security, which has raised $130 million, remains independent.
StackRox was founded in 2014 and raised over $65 million, according to Crunchbase data. Investors included Menlo Ventures, Redpoint and Sequoia Capital. The deal is expected to close this quarter subject to normal regulatory scrutiny.
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New Relic acquires Kubernetes observability platform Pixie Labs
Two months ago, Kubernetes observability platform Pixie Labs launched into general availability and announced a $9.15 million Series A funding round led by Benchmark, with participation from GV. Today, the company is announcing its acquisition by New Relic, the publicly traded monitoring and observability platform.
The Pixie Labs brand and product will remain in place and allow New Relic to extend its platform to the edge. From the outset, the Pixie Labs team designed the service to focus on providing observability for cloud-native workloads running on Kubernetes clusters. And while most similar tools focus on operators and IT teams, Pixie set out to build a tool that developers would want to use. Using eBPF, a relatively new way to extend the Linux kernel, the Pixie platform can collect data right at the source and without the need for an agent.
At the core of the Pixie developer experience are what the company calls “Pixie scripts.” These allow developers to write their debugging workflows, though the company also provides its own set of these and anybody in the community can contribute and share them as well. The idea here is to capture a lot of the informal knowledge around how to best debug a given service.
“We’re super excited to bring these companies together because we share a mission to make observability ubiquitous through simplicity,” Bill Staples, New Relic’s chief product officer, told me. “[…] According to IDC, there are 28 million developers in the world. And yet only a fraction of them really practice observability today. We believe it should be easier for every developer to take a data-driven approach to building software and Kubernetes is really the heart of where developers are going to build software.”
It’s worth noting that New Relic already had a solution for monitoring Kubernetes clusters. Pixie, however, will allow it to go significantly deeper into this space. “Pixie goes much, much further in terms of offering on-the-edge, live debugging use cases, the ability to run those Pixie scripts. So it’s an extension on top of the cloud-based monitoring solution we offer today,” Staples said.
The plan is to build integrations into New Relic into Pixie’s platform and to integrate Pixie use cases with New Relic One as well.
Currently, about 300 teams use the Pixie platform. These range from small startups to large enterprises and, as Staples and Pixie co-founder Zain Asgar noted, there was already a substantial overlap between the two customer bases.
As for why he decided to sell, Asgar — a former Google engineer working on Google AI and adjunct professor at Stanford — told me that it was all about accelerating Pixie’s vision.
“We started Pixie to create this magical developer experience that really allows us to redefine how application developers monitor, secure and manage their applications,” Asgar said. “One of the cool things is when we actually met the team at New Relic and we got together with Bill and [New Relic founder and CEO] Lew [Cirne], we realized that there was almost a complete alignment around this vision […], and by joining forces with New Relic, we can actually accelerate this entire process.”
New Relic has recently done a lot of work on open-sourcing various parts of its platform, including its agents, data exporters and some of its tooling. Pixie, too, will now open-source its core tools. Open-sourcing the service was always on the company’s road map, but the acquisition now allows it to push this timeline forward.
“We’ll be taking Pixie and making it available to the community through open source, as well as continuing to build out the commercial enterprise-grade offering for it that extends the New Relic One platform,” Staples explained. Asgar added that it’ll take the company a little while to release the code, though.
“The same fundamental quality that got us so excited about Lew as an EIR in 2007, got us excited about Zain and Ishan in 2017 — absolutely brilliant engineers, who know how to build products developers love,” Benchmark Ventures General Partner Eric Vishria told me. “New Relic has always captured developer delight. For all its power, Kubernetes completely upends the monitoring paradigm we’ve lived with for decades. Pixie brings the same easy to use, quick time to value, no-nonsense approach to the Kubernetes world as New Relic brought to APM. It is a match made in heaven.”
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Cast.ai nabs $7.7M seed to remove barriers between public clouds
When you launch an application in the public cloud, you usually put everything on one provider, but what if you could choose the components based on cost and technology and have your database one place and your storage another?
That’s what Cast.ai says that it can provide, and today it announced a healthy $7.7 million seed round from TA Ventures, DNX, Florida Funders and other unnamed angels to keep building on that idea. The round closed in June.
Company CEO and co-founder Yuri Frayman says that they started the company with the idea that developers should be able to get the best of each of the public clouds without being locked in. They do this by creating Kubernetes clusters that are able to span multiple clouds.
“Cast does not require you to do anything except for launching your application. You don’t need to know […] what cloud you are using [at any given time]. You don’t need to know anything except to identify the application, identify which [public] cloud providers you would like to use, the percentage of each [cloud provider’s] use and launch the application,” Frayman explained.
This means that you could use Amazon’s RDS database and Google’s ML engine, and the solution decides how to make that work based on your requirements and price. You set the policies when you are ready to launch and Cast will take care of distributing it for you in the location and providers that you desire, or that makes most sense for your application.
The company takes advantage of cloud-native technologies, containerization and Kubernetes to break the proprietary barriers that exist between clouds, says company co-founder Laurent Gil. “We break these barriers of cloud providers so that an application does not need to sit in one place anymore. It can sit in several [providers] at the same time. And this is great for the Kubernetes application because they’re kind of designed with this [flexibility] in mind,” Gil said.
Developers use the policy engine to decide how much they want to control this process. They can simply set location and let Cast optimize the application across clouds automatically, or they can select at a granular level exactly the resources they want to use on which cloud. Regardless of how they do it, Cast will continually monitor the installation and optimize based on cost to give them the cheapest options available for their configuration.
The company currently has 25 employees with four new hires in the pipeline, and plans to double to 50 by the end of 2021. As they grow, the company is trying keep diversity and inclusion front and center in its hiring approach; they currently have women in charge of HR, marketing and sales at the company.
“We have very robust processes on the continuous education inside of our organization on diversity training. And a lot of us came from organizations where this was very visible and we took a lot of those processes [and lessons] and brought them here,” Frayman said.
Frayman has been involved with multiple startups, including Cujo.ai, a consumer firewall startup that participated in TechCrunch Disrupt Battlefield in New York in 2016.
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Arrikto raises $10M for its MLOps platform
Arrikto, a startup that wants to speed up the machine learning development lifecycle by allowing engineers and data scientists to treat data like code, is coming out of stealth today and announcing a $10 million Series A round. The round was led by Unusual Ventures, with Unusual’s John Vrionis joining the board.
“Our technology at Arrikto helps companies overcome the complexities of implementing and managing machine learning applications,” Arrikto CEO and co-founder Constantinos Venetsanopoulos explained. “We make it super easy to set up end-to-end machine learning pipelines. More specifically, we make it easy to build, train, deploy ML models into production using Kubernetes and intelligent intelligently manage all the data around it.”
Like so many developer-centric platforms today, Arrikto is all about “shift left.” Currently, the team argues, machine learning teams and developer teams don’t speak the same language and use different tools to build models and to put them into production.
Image Credits: Arrikto
“Much like DevOps shifted deployment left, to developers in the software development life cycle, Arrikto shifts deployment left to data scientists in the machine learning life cycle,” Venetsanopoulos explained.
Arrikto also aims to reduce the technical barriers that still make implementing machine learning so difficult for most enterprises. Venetsanopoulos noted that just like Kubernetes showed businesses what a simple and scalable infrastructure could look like, Arrikto can show them what a simpler ML production pipeline can look like — and do so in a Kubernetes-native way.
Arrikto CEO Constantinos Venetsanopoulos. Image Credits: Arrikto
At the core of Arrikto is Kubeflow, the Google -incubated open-source machine learning toolkit for Kubernetes — and in many ways, you can think of Arrikto as offering an enterprise-ready version of Kubeflow. Among other projects, the team also built MiniKF to run Kubeflow on a laptop and uses Kale, which lets engineers build Kubeflow pipelines from their JupyterLab notebooks.
As Venetsanopoulos noted, Arrikto’s technology does three things: it simplifies deploying and managing Kubeflow, allows data scientists to manage it using the tools they already know, and it creates a portable environment for data science that enables data versioning and data sharing across teams and clouds.
While Arrikto has stayed off the radar since it launched out of Athens, Greece in 2015, the founding team of Venetsanopoulos and CTO Vangelis Koukis already managed to get a number of large enterprises to adopt its platform. Arrikto currently has more than 100 customers and, while the company isn’t allowed to name any of them just yet, Venetsanopoulos said they include one of the largest oil and gas companies, for example.
And while you may not think of Athens as a startup hub, Venetsanopoulos argues that this is changing and there is a lot of talent there (though the company is also using the funding to build out its sales and marketing team in Silicon Valley). “There’s top-notch talent from top-notch universities that’s still untapped. It’s like we have an unfair advantage,” he said.
“We see a strong market opportunity as enterprises seek to leverage cloud-native solutions to unlock the benefits of machine learning,” Unusual’s Vrionis said. “Arrikto has taken an innovative and holistic approach to MLOps across the entire data, model and code lifecycle. Data scientists will be empowered to accelerate time to market through increased automation and collaboration without requiring engineering teams.”
Image Credits: Arrikto
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Mirantis brings extensions to its Lens Kubernetes IDE, launches a new Kubernetes distro
Earlier this year, Mirantis, the company that now owns Docker’s enterprise business, acquired Lens, a desktop application that provides developers with something akin to an IDE for managing their Kubernetes clusters. At the time, Mirantis CEO Adrian Ionel told me that the company wants to offer enterprises the tools to quickly build modern applications. Today, it’s taking another step in that direction with the launch of an extensions API for Lens that will take the tool far beyond its original capabilities.
In addition to this update to Lens, Mirantis also today announced a new open-source project: k0s. The company describes it as “a modern, 100% upstream vanilla Kubernetes distro that is designed and packaged without compromise.”
It’s a single optimized binary without any OS dependencies (besides the kernel). Based on upstream Kubernetes, k0s supports Intel and Arm architectures and can run on any Linux host or Windows Server 2019 worker nodes. Given these requirements, the team argues that k0s should work for virtually any use case, ranging from local development clusters to private data centers, telco clusters and hybrid cloud solutions.
“We wanted to create a modern, robust and versatile base layer for various use cases where Kubernetes is in play. Something that leverages vanilla upstream Kubernetes and is versatile enough to cover use cases ranging from typical cloud based deployments to various edge/IoT type of cases,” said Jussi Nummelin, senior principal engineer at Mirantis and founder of k0s. “Leveraging our previous experiences, we really did not want to start maintaining the setup and packaging for various OS distros. Hence the packaging model of a single binary to allow us to focus more on the core problem rather than different flavors of packaging such as debs, rpms and what-nots.”
Mirantis, of course, has a bit of experience in the distro game. In its earliest iteration, back in 2013, the company offered one of the first major OpenStack distributions, after all.
Image Credits: Mirantis
As for Lens, the new API, which will go live next week to coincide with KubeCon, will enable developers to extend the service with support for other Kubernetes-integrated components and services.
“Extensions API will unlock collaboration with technology vendors and transform Lens into a fully featured cloud native development IDE that we can extend and enhance without limits,” said Miska Kaipiainen, the co-founder of the Lens open-source project and senior director of engineering at Mirantis. “If you are a vendor, Lens will provide the best channel to reach tens of thousands of active Kubernetes developers and gain distribution to your technology in a way that did not exist before. At the same time, the users of Lens enjoy quality features, technologies and integrations easier than ever.”
The company has already lined up a number of popular CNCF projects and vendors in the cloud-native ecosystem to build integrations. These include Kubernetes security vendors Aqua and Carbonetes, API gateway maker Ambassador Labs and AIOps company Carbon Relay. Venafi, nCipher, Tigera, Kong and StackRox are also currently working on their extensions.
“Introducing an extensions API to Lens is a game-changer for Kubernetes operators and developers, because it will foster an ecosystem of cloud-native tools that can be used in context with the full power of Kubernetes controls, at the user’s fingertips,” said Viswajith Venugopal, StackRox software engineer and developer of KubeLinter. “We look forward to integrating KubeLinter with Lens for a more seamless user experience.”
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With $29M in funding, Isovalent launches its cloud-native networking and security platform
Isovalent, a startup that aims to bring networking into the cloud-native era, today announced that it has raised a $29 million Series A round led by Andreessen Horowitz and Google. In addition, the company today officially launched its Cilium Enterprise platform (which was in stealth until now) to help enterprises connect, observe and secure their applications.
The open-source Cilium project is already seeing growing adoption, with Google choosing it for its new GKE data plane, for example. Other users include Adobe, Capital One, Datadog and GitLab. Isovalent is following what is now the standard model for commercializing open-source projects by launching an enterprise version.
Image Credits: Cilium
The founding team of CEO Dan Wendlandt and CTO Thomas Graf has deep experience in working on the Linux kernel and building networking products. Graf spent 15 years working on the Linux kernel and created the Cilium open-source project, while Wendlandt worked on Open vSwitch at Nicira (and then VMware).
Image Credits: Isovalent
“We saw that first wave of network intelligence be moved into software, but I think we both shared the view that the first wave was about replicating the traditional network devices in software,” Wendlandt told me. “You had IPs, you still had ports, you created virtual routers, and this and that. We both had that shared vision that the next step was to go beyond what the hardware did in software — and now, in software, you can do so much more. Thomas, with his deep insight in the Linux kernel, really saw this eBPF technology as something that was just obviously going to be groundbreaking technology, in terms of where we could take Linux networking and security.”
As Graf told me, when Docker, Kubernetes and containers, in general, become popular, what he saw was that networking companies at first were simply trying to reapply what they had already done for virtualization. “Let’s just treat containers as many as miniature VMs. That was incredibly wrong,” he said. “So we looked around, and we saw eBPF and said: this is just out there and it is perfect, how can we shape it forward?”
And while Isovalent’s focus is on cloud-native networking, the added benefit of how it uses the eBPF Linux kernel technology is that it also gains deep insights into how data flows between services and hence allows it to add advanced security features as well.
As the team noted, though, users definitely don’t need to understand or program eBPF, which is essentially the next generation of Linux kernel modules, themselves.
Image Credits: Isovalent
“I have spent my entire career in this space, and the North Star has always been to go beyond IPs + ports and build networking visibility and security at a layer that is aligned with how developers, operations and security think about their applications and data,” said Martin Casado, partner at Andreesen Horowitz (and the founder of Nicira). “Until just recently, the technology did not exist. All of that changed with Kubernetes and eBPF. Dan and Thomas have put together the best team in the industry and given the traction around Cilium, they are well on their way to upending the world of networking yet again.”
As more companies adopt Kubernetes, they are now reaching a stage where they have the basics down but are now facing the next set of problems that come with this transition. Those, almost by default, include figuring out how to isolate workloads and get visibility into their networks — all areas where Isovalent/Cilium can help.
The team tells me its focus, now that the product is out of stealth, is about building out its go-to-market efforts and, of course, continuing to build out its platform.
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