Why Serverless Computing Will Be Bigger Than Containers

One of the more popular trends in public cloud adoption is the use of serverless computing in AWS, Microsoft Azure, and Google Cloud. All of the major public cloud vendors offer serverless computing options, including databases, functions/scripts, load balancers, and more. When designing new or updated applications, many developers are looking at serverless components as an option. This new craze is coming at a time when the last big thing, containers, is still around and a topic of conversation. So, when users are starting up new projects or streamlining applications, will they stick with traditional virtual machines or go with a new paradigm? And out of all these buzzy trends, will anything come out on top and endure?

Virtual Machines: The Status Quo

The “traditional” approach to deployment of an application is to use a fleet of virtual machines running software on your favorite operating system. This approach is what most deployments have been like for 20 years, which means that there are countless resources available for installation, management, and upkeep. However, that also means you and your team have to spend the time and energy to install, manage, and keep that fleet going. You also have to plan for things like high availability, load balancing, and upgrades, as well as decide if these VMs are going to be on-prem or in the cloud. I don’t see the use of virtual machines declining anytime soon, but there are better options for some use cases.

Containers: The New Hotness, But Too Complex to be Useful

Containerization involves isolating an application by making it think it’s the only application on a server, with only the hardware available that you allow. Containers can divide up a virtual machine in a similar way that virtual machines can divide up a physical server. This idea has been around since the early 1980s, but has really started to pick up steam due to the release of Docker in 2013. The main benefits of containerization are the ability to maximize the utilization of physical hardware while deploying pieces of a microservices architecture that can easily run on any OS.

This sounds great in theory, but there are a couple of downsides to this approach. The primary problem is the additional operational complexity, as you still have to manage the physical hardware and the virtual machines, along with the container orchestration without much of a performance boost. The added complexity without removing any current orchestration means that you now have to think about more, not less, You also need to build in redundancy, train your users and developers, and ensure communication between pieces on top of your existing physical and virtual infrastructure.

Speaking of container orchestration, the other main downside is the multitude of options surrounding containers and their management, as there’s no one clear choice of what to use (and it’s hard to tell if any of the existing ones will just go away one day and leave you with a mess). Kubernetes seems to be the front runner in this area, but Apache Mesos and Docker Swarm are big players as well. Which do you choose, and do you force all users and teams to use the same one? What if the company who manages those applications makes a change that you didn’t plan for? There’s a lot of questions and unknowns, along with just having to make the choice that could have ramifications for years to come.

Serverless Computing: Less Setup, More Functionality

When users or developers are working on a project that involves a database and some python scripts, they just want the database and the scripts, not a server that is running database software and a server that runs scripts. That’s because the main idea behind serverless architecture is the goal of trying to eliminate all the overhead that comes along with these requests for specific software. This is a big benefit to those who just want to get something up and running without installing operating systems, tweaking configuration files, and worrying about redundancy and uptime.

This isn’t all sunshine and rainbows, however. One of the big downsides to serverless comes hand-in-hand with that reduced complexity, in that you also typically have reduced customization. Running an older database version or having a long-running python function might not be possible using serverless services. Another possible downside is that you are typically locked in to a vendor once you start developing your applications around serverless architecture, as the APIs are often going to be vendor-specific.

That being said, it appears that the reduced complexity is a big deal for the users who want things to “just work”. Dealing with less headaches and less management so they can get creative and deploy some cool applications is one of the main goals of folks who are trying to push the boundaries of what’s possible. If Amazon, Microsoft, or Google want to handle database patching and python versioning so you don’t have to, then let them deal with it and move on to the fun stuff!

Here at ParkMyCloud, we’re doing a mix of serverless and traditional virtual machines to maximize the benefits and minimize the overhead for what we do.  By using serverless where it makes sense without forcing a square peg into a round hole, we can run virtual machines to handle the code we’ve already written while using serverless architecture for things like databases, load balancing, and email messages.  We’re starting to see more customers going with this approach as well, who then use ParkMyCloud to keep the costs of virtual machines low when they aren’t in use. (If you’d like to do the same, check out a trial of ParkMyCloud to get your hybrid infrastructure optimized.)

When it comes to development and operations, there are numerous decisions to make that all have pros and cons. Serverless architecture is the latest deployment option available, and it clearly helps reduce complexity and accounts for things that may give you headaches. The reduced mobility is something that containers can handle really well, but involves more complexity in deployment and ongoing management. Software installed on virtual machines is a tried-and-true method, but does mean you are doing a lot of the work yourself. It’s the fact that serverless computing is so simple to implement that makes it more than a trend: this is a paradigm that will endure, where containers won’t.


About Chris Parlette

Chris Parlette is the Director of Cloud Solutions at ParkMyCloud. Chris helps customers reduce their cloud waste and manage their hybrid infrastructures by drawing on his years of experience working at various software startups. From SaaS to on-prem, virtualization to cloud, monitoring tools to cloud management platforms, and small businesses to large enterprises, Chris has seen it all and loves helping drive improvements to IT management. Chris earned a BS in Computer Science from the University of Maryland. He and his wife, Megan, reside in Silver Spring, MD.

One response to “Why Serverless Computing Will Be Bigger Than Containers”

  1. […] Containers also add more operational complexity than you might at first assume, adding more to orchestrate and requiring additional management. […]

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