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For developers, worrying about infrastructure is a chore they can do without. Serverless computing relieves that burden.
It’s always unfortunate to start the definition of a phrase by calling it a misnomer, but that’s where you have to begin with serverless computing: Of course there will always be servers. Serverless computing merely adds another layer of abstraction atop cloud infrastructure, so developers no longer need to worry about servers, including virtual ones in the cloud.
To explore this idea, I spoke with one of serverless computing’s most vocal proponents: Chad Arimura, CEO of the startup Iron.io, which develops software for microservices workload management. Arimura says serverless computing is all about the modern developer’s evolving frame of reference:
What we’ve seen is that the atomic unit of scale has been changing from the virtual machine to the container, and if you take this one step further, we’re starting to see something called a function … a single-purpose block of code. It’s something you can conceptualize very easily: Process an image. Transform a piece of data. Encode a piece of video.
To me this sounded a lot like microservices architecture, where instead of a building a monolithic application, you assemble an application from single-purpose services. What then is the difference between a microservice and a function?
A service has a common API that people can access. You don’t know what’s going on under the hood. That service may be powered by functions. So functions are the building block code aspect of it; the service itself is like the interface developers can talk to.
Just as developers use microservices to assemble applications and call services from functions, they can grab functions from a library to build the services themselves — without having to consider server infrastructure as they create an application.
AWS Lambda is the best-known example of serverless computing. As an Amazon instructional video explains, “once you upload your code to Lambda, the service handles all the capacity, scaling, patching, and administration of the infrastructure to run your code.” Both AWS Lambda and Iron.io offer function libraries to further accelerate development. Provisioning and autoscaling are on demand.
Keep in mind all of this is above the level of service orchestration — of the type offered by Mesos, Kubernetes, or Docker Swarm. Although Iron.io offers its own orchestration layer, which predated those solutions being generally available, it also plugs into them, “but we really play at the developer/API later,” says Arimura.
In fact, it’s fair to view the core of Iron.io’s functionality roughly equivalent to that of AWS Lambda, only deployable on all major public and private cloud platforms. Arimura sees the ability to deploy on premises as a particular Iron.io advantage because the hybrid cloud is becoming more and more essential to the enterprise approach to cloud computing. Think of the consistency and application portability enabled by the same serverless computing environment across public and private clouds.
Arimura even goes as far as to use the controversial “no-ops,” coined by former Netflix cloud architect Adrain Cockcroft. Again, just as there will always be servers, there will always be ops to run them. Again, no-ops and serverless computing take the developer’s point of view: Someone else has to worry about that stuff, but not me while I create software.
Serverless computing, then, represents yet another leap in developer efficiency, where even virtual infrastructure concerns melt away and libraries of services and functions reduce once again the amount of code developers need to write from scratch.
Enterprise dev shops have been slow to adopt agile, CICD, devops, and the like. But as we move up the stack to serverless computing levels of abstraction, the palpable benefits of modern development practices become more and more enticing.
Original article here.
Operator and vendor revenues across the main cloud services and infrastructure market segments hit $148 billion (£120.5bn) in 2016 growing at 25% annually, according to the latest note from analyst firm Synergy Research.
Infrastructure as a service (IaaS) and platform as a service (PaaS) experienced the highest growth rates at 53%, followed by hosted private cloud infrastructure services, at 35%, and enterprise SaaS, at 34%. Amazon Web Services (AWS) and Microsoft lead the way in IaaS and PaaS, with IBM and Rackspace on top for hosted private cloud.
In the four quarters ending September (Q3) 2016, total spend on hardware and software to build cloud infrastructure exceeded $65bn, according to the researchers. Spend on private cloud accounts for more than half of the overall total, but public cloud spend is growing much more rapidly. The note also argues unified comms as a service (UCaaS) is growing ‘steadily’.
“We tagged 2015 as the year when cloud became mainstream and I’d say that 2016 is the year that cloud started to dominate many IT market segments,” said Jeremy Duke, Synergy Research Group founder and chief analyst in a statement. “Major barriers to cloud adoption are now almost a thing of the past, especially on the public cloud side.
“Cloud technologies are now generating massive revenues for technology vendors and cloud service providers and yet there are still many years of strong growth ahead,” Duke added.
The most recent examination of the cloud infrastructure market by Synergy back in August argued AWS, Microsoft, IBM and Google continue to grow more quickly than their smaller competitors and, between them, own more than half of the global cloud infrastructure service market.
Original article here.
Like everything in enterprise technology, pricing can be a bit complicated. Here’s an analysis from RightScale looking at how discounts alter the cloud pricing equation. Google comes out cheapest in most scenarios.
With Amazon Web Services hosting its annual conference this week, talk about the price for performance and agility equation will be everywhere.
Knowing AWS’ re:Invent is kicking off this week, the largest cloud service provider has been busy cutting prices for various instances. Rest assured that Google and Microsoft are likely to toss in their own price cuts, as AWS speaks to its base.
But the cloud pricing equation is getting complicated for compute instances. Not so shockingly, these price discussions have to include discounts. Like everything in enterprise technology, there’s the street price and your price. Comparing the cloud providers on pricing is tricky given Microsoft, Google, and AWS all have different approaches to discounts.
Fortunately, RightScale on Monday will outline a study on cloud compute prices. Generally speaking, AWS won’t be your cheapest option for compute. AWS typically lands in the middle between Microsoft Azure and Google Cloud.
The bottom line is that AWS uses reserved instances in one-year and three-year terms to offer discounts. Microsoft requires an enterprise agreement for its Azure discounts. Google has sustained usage discounts that are relatively easy to follow.
Overall, RightScale found that Google will be cheapest in most scenarios because sustained usage discounts are automatically applied. Among the key takeaways:
- If you need solid state drive performance instead of attached storage, Google will charge you a premium.
- Azure matches or beats AWS for on-demand pricing consistently.
- AWS won’t be the cheapest alternative in many scenarios. Then again — AWS has a bigger menu, more advanced cloud services, and the customer base where it doesn’t have to go crazy on pricing. AWS just has to be fair.
- Your results will vary based on the level of your Microsoft enterprise agreement and what reserved instances were purchased on AWS.
Here are three slides to ponder from RightScale.
Add it up and you’d be advised to make your own comparisons; check out RightScale’s SlideShare, and then crunch some numbers. In the end, enterprises may have to have all three cloud providers in their company — if only to play them off each other.
Original article here.