serverless computing
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AWS today quietly brought spot capacity to Fargate, its serverless compute engine for containers that supports both the company’s Elastic Container Service and, now, its Elastic Kubernetes service.
Like spot instances for the EC2 compute platform, Fargate Spot pricing is significantly cheaper, both for storage and compute, than regular Fargate pricing. In return, though, you have to be able to accept the fact that your instance may get terminated when AWS needs additional capacity. While that means Fargate Spot may not be perfect for every workload, there are plenty of applications that can easily handle an interruption.
“Fargate now has on-demand, savings plan, spot,” AWS VP of Compute Services Deepak Singh told me. “If you think about Fargate as a compute layer for, as we call it, serverless compute for containers, you now have the pricing worked out and you now have both orchestrators on top of it.”
He also noted that containers already drive a significant percentage of spot usage on AWS in general, so adding this functionality to Fargate makes a lot of sense (and may save users a few dollars here and there). Pricing, of course, is the major draw here and an hour of CPU time on Fargate Spot will only cost $0.01245364 (yes, AWS is pretty precise there) compared to $0.04048 for the on-demand price,
With this, AWS is also launching another important new feature: capacity providers. The idea here is to automate capacity provisioning for Fargate and EC2, both of which now offer on-demand and spot instances, after all. You simply write a config file that, for example, says you want to run 70 percent of your capacity on EC2 and the rest on spot instances. The scheduler will then keep that capacity on spot as instances come and go, and if there are no spot instances available, it will move it to on-demand instances and back to spot once instances are available again.
In the future, you will also be able to mix and match EC2 and Fargate. “You can say, I want some of my services running on EC2 on demand, some running on Fargate on demand, and the rest running on Fargate Spot,” Singh explained. “And the scheduler manages it for you. You squint hard, capacity is capacity. We can attach other capacity providers.” Outpost, AWS’ fully managed service for running AWS services in your data center, could be a capacity provider, for example.
These new features and prices will be officially announced in Thursday’s re:Invent keynote, but the documentation and pricing is already live today.
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As we move from a world dominated by virtual machines to one of serverless, it changes the nature of monitoring, and vendors like New Relic certainly recognize that. This morning the company announced it was acquiring IOpipe, a Seattle-based early-stage serverless monitoring startup, to help beef up its serverless monitoring chops. Terms of the deal weren’t disclosed.
New Relic gets what it calls “key members of the team,” which at least includes co-founders Erica Windisch and Adam Johnson, along with the IOpipe technology. The new employees will be moving from Seattle to New Relic’s Portland offices.
“This deal allows us to make immediate investments in onboarding that will make it faster and simpler for customers to integrate their [serverless] functions with New Relic and get the most out of our instrumentation and UIs that allow fast troubleshooting of complex issues across the entire application stack,” the company wrote in a blog post announcing the acquisition.
It adds that initially the IOpipe team will concentrate on moving AWS Lambda features like Lambda Layers into the New Relic platform. Over time, the team will work on increasing support for serverless function monitoring. New Relic is hoping by combining the IOpipe team and solution with its own, it can speed up its serverless monitoring chops.
Eliot Durbin, an investor at Bold Start, which led the company’s $2 million seed round in 2018, says both companies win with this deal. “New Relic has a huge commitment to serverless, so the opportunity to bring IOpipe’s product to their market-leading customer base was attractive to everyone involved,” he told TechCrunch.
The startup has been helping monitor serverless operations for companies running AWS Lambda. It’s important to understand that serverless doesn’t mean there are no servers, but the cloud vendor — in this case AWS — provides the exact resources to complete an operation, and nothing more.
Photo: New Relic
Once the operation ends, the resources can simply get redeployed elsewhere. That makes building monitoring tools for such ephemeral resources a huge challenge. New Relic has also been working on the problem and released New Relic Serverless for AWS Lambda earlier this year.
As TechCrunch’s Frederic Lardinois pointed out in his article about the company’s $2.5 million seed round in 2017, Windisch and Johnson bring impressive credentials:
IOpipe co-founders Adam Johnson (CEO) and Erica Windisch (CTO), too, are highly experienced in this space, having previously worked at companies like Docker and Midokura (Adam was the first hire at Midokura and Erica founded Docker’s security team). They recently graduated from the Techstars NY program.
IOpipe was founded in 2015, which was just around the time that Amazon was announcing Lambda. At the time of the seed round the company had eight employees. According to PitchBook data, it currently has between 1 and 10 employees, and has raised $7.07 million since its inception.
New Relic was founded in 2008 and has raised more than $214 million, according to Crunchbase, before going public in 2014. Its stock price was $65.42 at the time of publication, up $1.40.
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Serverless development has largely been a lonely pursuit until recently, but Serverless, Inc. has been offering a free framework for intrepid programmers since 2015. At first, that involved development, deployment and testing, but today the company announced it is expanding into monitoring and security to make it an end-to-end tool — and it’s available for free.
Serverless computing isn’t actually server-free, but it’s a form of computing that provides a way to use only the computing resources you need to carry out a given function — and no more. When the process is complete, the resources effectively go away. That has the potential to be more cost-effective than having a server that’s always on, regardless of whether you’re using it or not. That requires a new way of thinking about how developers write code.
While serverless offers a compelling value proposition, up until Serverless, Inc. came along with some developer tooling, early adherents were pretty much stuck building their own tooling to develop, deploy and test their programs. Today’s announcement expands the earlier free Serverless, Inc. Framework to provide a more complete set of serverless developer tools.
Company founder and CEO Austen Collins says that he has been thinking a lot about what developers need to develop and deploy serverless programs, and talking to customers. He says that they really craved a more integrated approach to serverless development than has been available until now.
“What we’re trying to do is build this perfectly integrated solution for developers and developer teams because we want to enable them to innovate as much as possible and be as autonomous as possible,” Collins told TechCrunch. He says at the same time, he recognizes that operations need to connect to other tools, and the Serverless Framework provides hooks into other systems, as well.

The new tooling includes an integrated environment, so that once you deploy, you can simply click an error or security event and drill down to a dashboard for more information about the issue. You can click for further detail to see the exact spot in the code where the issue occurred, which should make it easier to resolve more quickly.
While no tool is 100% comprehensive, and most large organizations, and even individual developers, will have a set of tools they prefer to use, this is an attempt to build a one-stop solution for serverless developers for the first time. That in itself is significant, as serverless moves beyond early adopters and begins to become more of a mainstream kind of programming and deployment option. People starting now probably won’t want to cobble together their own toolkits, and the Serverless, Inc. Framerwork gives them a good starting point.
Serverless, Inc. was founded by Collins in 2015 out of a need for serverless computing tooling. He has raised more than $13.5 million since inception.
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When you think of old, giant mainframes that sit in the basement of a giant corporation, still doing the same work they did 30 years ago, chances are you’re thinking about a financial institution. It’s the financial enterprises, though, that are often leading the charge in bringing new technologies and software development practices to their employees and customers. That’s in part because they are in a period of disruption that forces them to become more nimble. Often, this means leaving behind legacy technology and embracing the cloud.
At TC Sessions: Enterprise, which is happening on September 5 in San Francisco, Capital One executive VP in charge of its technology operations, George Brady, will talk about the company’s journey from legacy hardware and software to embracing the cloud and open source, all while working in a highly regulated industry. Indeed, Capital One was among the first companies to embrace the Facebook-led Open Compute project and it’s a member of the Cloud Native Computing Foundation. It’s this transformation at Capital One that Brady is leading.
At our event, Brady will join a number of other distinguished panelists to specifically talk about his company’s journey to the cloud. There, Capital One is using serverless compute, for example, to power its Credit Offers API using AWS’s Lambda service, as well as a number of other cloud technologies.
Before joining Capital One as its CTO in 2014, Brady ran Fidelity Investment’s global enterprise infrastructure team from 2009 to 2014 and served as Goldman Sachs’ head of global business applications infrastructure before that.
Currently, he leads cloud application and platform productization for Capital One. Part of that portfolio is Critical Stack, a secure container orchestration platform for the enterprise. Capital One’s goal with this work is to help companies across industries become more compliant, secure and cost-effective operating in the public cloud.
Early-bird tickets are still on sale for $249; grab yours today before we sell out.
Student tickets are just $75 — grab them here.
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Cloud native models using containerized software in a continuous delivery approach could benefit from serverless computing where the cloud vendor generates the exact amount of resources required to run a workload on the fly. While the major cloud vendors have recognized this and are already creating products to abstract away the infrastructure, it may not work for every situation in spite of the benefits.
Cloud native, put simply, involves using containerized applications and Kubernetes to deliver software in small packages called microservices. This enables developers to build and deliver software faster and more efficiently in a continuous delivery model. In the cloud native world, you should be able to develop code once and run it anywhere, on prem or any public cloud, or at least that is the ideal.
Serverless is actually a bit of a misnomer. There are servers underlying the model, but instead of dedicated virtual machines, the cloud vendor delivers exactly the right number of resources to run a particular workload for the right amount of time and no more.
Such an arrangement would seem to be perfectly suited to a continuous delivery model, and while vendors have recognized the beauty of such an approach, as one engineer pointed out, there is never a free lunch in processes that are this complex, and it won’t be a perfect solution for every situation.
Arpana Sinha, director of product management at Google, says the Kubernetes community has really embraced the serverless idea, but she says that it is limited in its current implementation, delivered in the form of functions with products like AWS Lambda, Google Cloud Functions and Azure Functions.
“Actually, I think the functions concept is a limited concept. It is unfortunate that that is the only thing that people associate with serverless,” she said.
She says that Google has tried to be more expansive in its definition. “It’s basically a concept for developers where you are able to seamlessly go from writing code to deployment and the infrastructure takes care of all of the rest, making sure your code is deployed in the appropriate way across the appropriate, most resilient parts of the infrastructure, scaling it as your app needs additional resources, scaling it down as your traffic goes down, and charging you only for what you’re consuming,” she explained.
But Matt Whittington, senior engineer on the Kubernetes Team at Atlassian says, while it sounds good in theory, in practice, fully automated infrastructure could be unrealistic in some instances. “Serverless could be promising for certain workloads because it really allows developers to focus on the code, but it’s not a perfect solution. There is still some underlying tuning.”
He says you may not be able to leave it completely up to the vendor unless there is a way to specify the requirements for each container, such as instructing them you need a minimum container load time, a certain container kill time or perhaps you need to deliver it a specific location. He says in reality it won’t be fully automated, at least while developers fiddle with the settings to make sure they are getting the resources they need without over-provisioning and paying for more than they need.
The vendors are putting in their two cents trying to create tools that bring this ideal together. For instance, Google announced a service called Google Cloud Run at Google Cloud Next last month. It’s based on the open-source Knative project, and in essence combines the goodness of serverless for developers running containers. Other similar services include AWS Fargate and Azure Container Instances, both of which are attempting to bring together these two technologies in a similar package.
In fact, Gabe Monroy, partner program manager at Microsoft, says Azure Container Instances is designed to solve this problem without being dependent on a functions-driven programming approach. “What Azure Container Instances does is it allows you to run containers directly on the Azure compute fabric, no virtual machines, hypervisor isolated, pay-per-second billing. We call it serverless containers,” he said.
While serverless and containers might seem like a good fit, as Monroy points out, there isn’t a one-size-fits-all approach to cloud-native technologies, whatever the approach may be. Some people will continue to use a function-driven serverless approach like AWS Lambda or Azure Functions and others will shift to containers and look for other ways to bring these technologies together. Whatever happens, as developer needs change, it is clear the open-source community and vendors will respond with tools to help them. Bringing serverless and containers together is just one example of that.
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Last July, at its Cloud Next conference, Google announced the Cloud Services Platform, its first real foray into bringing its own cloud services into the enterprise data center as a managed service. Today, the Cloud Services Platform (CSP) is launching into beta.
It’s important to note that the CSP isn’t — at least for the time being — Google’s way of bringing all of its cloud-based developer services to the on-premises data center. In other words, this is a very different project from something like Microsoft’s Azure Stack. Instead, the focus is on the Google Kubernetes Engine, which allows enterprises to then run their applications in both their own data centers and on virtually any cloud platform that supports containers.
As Google Cloud engineering director Chen Goldberg told me, the idea here it to help enterprises innovate and modernize. “Clearly, everybody is very excited about cloud computing, on-demand compute and managed services, but customers have recognized that the move is not that easy,” she said and noted that the vast majority of enterprises are adopting a hybrid approach. And while containers are obviously still a very new technology, she feels good about this bet on the technology because most enterprises are already adopting containers and Kubernetes — and they are doing so at exactly the same time as they are adopting cloud and especially hybrid clouds.
It’s important to note that CSP is a managed platform. Google handles all of the heavy lifting like upgrades and security patches. And for enterprises that need an easy way to install some of the most popular applications, the platform also supports Kubernetes applications from the GCP Marketplace.

As for the tech itself, Goldberg stressed that this isn’t just about Kubernetes. The service also uses Istio, for example, the increasingly popular service mesh that makes it easier for enterprises to secure and control the flow of traffic and API calls between its applications.
With today’s release, Google is also launching its new CSP Config Management tool to help users create multi-cluster policies and set up and enforce access controls, resource quotas and more. CSP also integrates with Google’s Stackdriver Monitoring service and continuous delivery platforms.
“On-prem is not easy,” Goldberg said, and given that this is the first time the company is really supporting software in a data center that is not its own, that’s probably an understatement. But Google also decided that it didn’t want to force users into a specific set of hardware specifications like Azure Stack does, for example. Instead, CSP sits on top of VMware’s vSphere server virtualization platform, which most enterprises already use in their data centers anyway. That surely simplifies things, given that this is a very well-understood platform.
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Lumigo, an Israeli startup, announced a healthy $8 million seed round today, as it emerged from stealth to help companies monitor serverless architecture. Investors include Pitango Venture Capital, Grove Ventures and Meron Capital.
The company was started by a couple of ex-Checkpoint execs, Erez Berkner and Aviad Mor. They decided to head out on their own to solve a problem they were seeing around monitoring as developers moved to serverless environments.
Serverless computing lets developers code applications without worrying about the underlying infrastructure. That’s because services like AWS Lambda, Azure Functions and Google Cloud Functions provide the exact amount of infrastructure resources required to run the application at any given moment. It is incredibly convenient for developers trying to move more quickly, but it poses challenges for the operations team trying to manage and monitor the application.
To help solve this, the company uses a visual map to show operations exactly what’s happening inside the application. The map enables operations teams to see and understand every request and get to the root cause of a problem. It can trace the path not only from the serverless infrastructure, but also to adjacent services like database and storage.
Lumigo serverless monitoring map
For starters, the company is working with AWS, but plans to add support for other cloud platforms down the road. Moving forward, the founders’ vision is more than just serverless. They plan to expand to monitor containers and API services like Twilio and Stripe.
For now, it’s still early days, but the company has eight employees and a dozen customers using the product. The money should allow them to hire more engineers and begin building out the product further.
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Solo.io, a Cambridge, Mass-based startup that helps enterprises adopt cloud-native technologies, is coming out of stealth mode today and announcing both its Series A funding round and the launch of its Gloo Enterprise API gateway.
Redpoint Ventures led the $11 million Series A round, with participation from seed investor True Ventures . Like most companies at the Series A state, Solo.io plans to use the money to invest in the product development of its enterprise and open-source tools, as well as to grow its sales and marketing teams.
Solo.io offers a number of open-source tools, like the Gloo function gateway, the Sqoop GraphQL server and the SuperGloo (see a theme here?) service mesh orchestration platform. In addition, the team has also, among others, open-sourced its Kubernetes debugger, a tool for building and running unikernels.

Its first commercial offering, though, is an enterprise version of the Gloo function gateway. Built on top of the Envoy proxy, Gloo can handle the routing necessary to connect incoming API requests to microservices, serverless applications (on the likes of AWS Lambda) and traditional monolithic applications behind the proxy. Gloo handles the load balancing and other functions necessary to aggregate the incoming API requests and route them to their destinations.
“Costumers who use Gloo to connect between microservices and serverless found that invocation of [AWS] Lambda is 350ms faster than the AWS API Gateway,” Idit Levine, the founder and CEO of Solo.io, told me. “Gloo also offers them direct money saving, since AWS bills per invocation. In general, Gloo offers money saving because it allows our clients to use the less expensive technologies — like their legacy apps, and sometimes containers — whenever they can, and limit the use of more expensive stuff to whenever it’s necessary.”
The enterprise version adds features like audit controls, single sign-on and more advanced security tools to the platform.
In addition to broadening its customer base, the company plans to invest heavily into its customer success and support teams, as well as its evangelism and education efforts, Levine tells me.
“Helping enterprises easily adopt innovative technologies like microservices, serverless and service mesh is our goal at Solo.io,” Levine in today’s announcement. “Melding different technologies into one coherent environment, by supplying a suite of tools to route, debug, manage, monitor and secure applications, lets organizations focus on their software without worrying about the complexity of the underlying environment.”
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AWS launched Lambda in 2015 and with it helped popularize serverless computing. You simply write code (event triggers) and AWS deals with whatever compute, memory and storage you need to make that work. Today at AWS re:Invent in Las Vegas, the company announced several new features to make it more developer friendly, while acknowledging that even while serverless reduced complexity, it still requires more sophisticated tools as it matures.
It’s called serverless because you don’t have to worry about the underlying servers. The cloud vendors take care of all that for you, serving whatever resources you need to run your event and no more. It means you no longer have to worry about coding for all your infrastructure and you only pay for the computing you need at any given moment to make the application work.
The way AWS works is that it tends to release something, then builds more functionality on top of a base service as it sees increasing requirements as customers use it. As Amazon CTO Werner Vogels pointed out in his keynote on Thursday, developers debate about tools and everyone has their own idea of what tools they bring to the task every day.
For starters, they decided to please the language folks introducing support for new languages. Those developers who use Ruby can now use Ruby Support for AWS Lambda. “Now it’s possible to write Lambda functions as idiomatic Ruby code, and run them on AWS. The AWS SDK for Ruby is included in the Lambda execution environment by default,” Chris Munns from AWS wrote in a blog post introducing the new language support.
If C++ is your thing, AWS announced C++ Lambda Runtime. If neither of those match your programming language tastes, AWS opened it up for just about any language with the new Lambda Runtime API, which Danilo Poccia from AWS described in a blog post as “a simple interface to use any programming language, or a specific language version, for developing your functions.”
AWS didn’t want to stop with languages though. They also recognize that even though Lambda (and serverless in general) is designed to remove a level of complexity for developers, that doesn’t mean that all serverless applications consist of simple event triggers. As developers build more sophisticated serverless apps, they have to bring in system components and compose multiple pieces together, as Vogels explained in his keynote today.
To address this requirement, the company introduced Lambda Layers, which they describe as “a way to centrally manage code and data that is shared across multiple functions.” This could be custom code used by multiple functions or a way to share code used to simplify business logic.
As Lambda matures, developer requirements growl; these announcements and others are part of trying to meet those needs.
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Serverless has become a big buzzword of late, and with good reason. It has the potential to completely alter how developers write code. They can simply write a series of event triggers, while letting the cloud vendor worry about providing whatever amount of compute resources are required to complete the job. It represents a huge shift in how programs are developed, but it’s been difficult to find companies who were built from the ground up using this methodology because it’s fairly new.
Blissfully, a startup that helps customers manage their Software-as-a-Service usage inside their companies, is one company that decided to do just that. Aaron White, co-founder and CTO, says that when he was building early versions of Blissfully, he found he needed quick bursts of compute power to deliver a list of all the SaaS products an organization is using.
He figured he could set aside a bunch of servers to provide that burst of power as needed, but that would have required a ton of overhead on his part to manage. At this point, he was a lone programmer trying to prove his SaaS management idea was even possible. As he looked at the pros and cons of serverless versus traditional virtual machines, he began to see serverless as a viable approach.
What he learned along the way was that serverless offers many advantages to a company with a bursty approach like Blissfully, scaling up and down as needed. But it isn’t perfect and there are issues around management and tooling and handling the pros and cons of that scaling ability that he had to learn about on the fly, especially coming in as early as he did with this approach.
Blissfully is a service where serverless made a lot of sense. It wouldn’t have to manage or pay for servers it wasn’t using. Nor would it have to worry about the underlying infrastructure at all. That would be up to the cloud provider, and it would only pay for the bursts as they happened.
Serverless is actually a misnomer, in that it doesn’t mean there are no servers. It actually means you don’t have to set up servers in order to run your program, which is a pretty mind-blowing transformation. In traditional programming you have to write your code and set up all the underlying hardware ahead of time, whether it’s in your data center or in the cloud. With serverless, you just write the code and the cloud provider handles all of that for you.
The way it works in practice is that programmers set up a series of event triggers, so when a certain thing happens, the cloud provider sees this and provides the necessary resources on demand. Most of the cloud vendors are offering this type of service, whether AWS Lambda, Azure Functions or Google Functions.
At this point, White began to think about serverless as a way of freeing him from thinking about managing and maintaining infrastructure and all that entailed. “I started thinking, let’s see how far we can take this. Can we really do absolutely everything serverless, and if so that reduces a ton of traditional DevOps-style work you have to do in practice. There’s still plenty, but that was the thinking at the beginning,” he said.
But there were issues, especially getting into serverless as early as he did. For starters, White needed to find developers who could work in this fashion, and in 2016 when it launched there weren’t a large number of people out there with serverless skills. White said he wasn’t looking for direct experience so much as people who were curious to learn and were flexible enough to deal with new technology, regardless of how Blissfully implemented that.
Once he figured out the basics, he needed to think about how this would work structurally. “Part of the challenge is figuring out where do you draw the boundaries between different serverless functions? How do you think about how much you want to overload the capability of one function versus another? How do you want to split it up? You could go way too specific, and you can of course, go way too broad. So there’s a lot of judgement calls to be made in terms of how you want to split your code base to work in this way,” he said.
The other challenge he faced going with a serverless approach so early was a dearth of tooling around it. White found Serverless, Inc. right way, which helped him with a basic framework for developing, but he lacked good logging tools and says that the company still struggles with this even now. “DevOps doesn’t go away. This is still running on a server somewhere (even if you don’t control that) and you will run into issues.” One such issue he calls a “cold start issue.”
Blissfully uses AWS Lambda, and as their customers require resources, it isn’t as though Amazon has a set of dedicated resources set aside waiting for such an event. If it needs to start servers cold, that could result in latency. To compensate for that, Blissfully runs a job that pings Lambda continually, so that it’s always ready to run the actual application, and there isn’t a lag time related to starting from scratch.
The other issue could be the opposite problem. You can scale much faster than you’re ready to deal with and that can be a problem for a small team. He says in that case, you want to put a limiter on the speed of the calls so you don’t end up spending more than you can afford, and it doesn’t scale beyond your team’s ability to manage it, “I think, in some ways, this actually accelerates you running into problems where you would normally be larger scale before you really had to think about them,” White said.
The other piece is that once Lambda gets everything going, it can move data faster than your external APIs can handle, and that could require limiters to actually slow things down. “I never had that problem in the past where I was provisioning so many computational resources that Google was yelling at me for being too fast. Being too fast for Google takes a lot of effort, but it doesn’t take a lot of effort with Lambda. When it does decide to spool up whatever resources, you can do some serious outbound damage to other APIs.” That meant he and his team actually had to think very early on about building sophisticated rate-limiting schemes.
As for costs, White estimates that his costs are much lower now that he has the service built and in place. “Our costs are so low right now, and far lower than if we had server-based infrastructure. Our computational pattern is very bursty.” That’s because it re-parses the SaaS database once a day or when the customer first signs up, and in between, usage is fairly low beyond interacting with the data.
“So for us that was perfect for serverless because I don’t really need to keep capacity around that would be pure waste.”
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