Containers and the Search for the “Killer App”

VisiCalc for early PCs. E-mail for the Internet. SMS for mobile. Every major tech platform we’ve seen has had the benefit of a “killer application” that transformed it from “toy” or “cool project” into an indispensable, mainstream product.

Now that that we’re in the midst of what looks to be another major platform shift in the datacenter – this time with the layer of abstraction moving from physical infrastructure via the hypervisor to the OS via containerization – talk has centered around Linux containers and whether they represent a paradigm shift in how we build and deploy applications or if they are simply another instrument in the DevOps toolkit.

The relevant analog for mapping out the fate of containerization seems to be virtualization. Charting VMware’s history provides a hint of how container adoption and ecosystem development may unfold, but it’s far from a perfect corollary.

In 1999, VMware released Workstation which let developers run multiple virtual machines with different operating systems locally. This solved an acute developer pain around building applications that would work across different OS’s and environments. A couple years later the company entered the server market with ESX and vMotion which enabled live migration; a fancy way of saying you could move running VMs between physical hosts without taking the whole application down. The VMware toolchain quickly spread through dev/test as developers could now build and test applications for different environments and then deploy them with a few clicks confident they wouldn’t break production (assuming proper config files were installed; hence the rise of config management tools like Chef, Puppet, etc.). In addition to this grass-roots, bottoms-up adoption, virtualization benefited from CIO-led, top-down initiatives to eliminate IT sprawl, improve server utilization and consolidate datacenters. The result, depending on who you ask today, is that anywhere from 75-90% of x86 workloads are virtualized.

Hardware virtualization, then, literally digitized the analog task of racking servers. It represented a step-function improvement over how IT could be provisioned and administered and how applications could be tested and deployed.

Now we’re seeing similar developer-led adoption of containerization, and sure enough there are myriad reasons why adopting Linux containers makes sense: from enabling application portability across compute and cloud infrastructures, to streamlining your deployment pipeline to liberating your organization from the VMware tax. But as we sit here today, many (including myself) contend that containers don’t represent as radical a step-function improvement over the tools used to solve similar problems as VMs did in the early 2000s. Nor is there a similar top-down, CTO-/CIO-led initiative to catalyze adoption. Consequently, what we’re looking for is the killer application that unlocks the value of containers for the mass-market.

What might those killer apps be? Here are three likely candidates:

• “Dropbox-ized” dev environments – One of the most nagging engineering pains is provisioning and replicating developer environments across the org and then maintaining parity between those environments with test and production. Containers offer a way to encapsulate code with all of its dependencies allowing it to run the same irrespective of underlying infrastructure. Because containers share the kernel user space, they offer a more lightweight alternative to VM-based solutions like Vagrant, thereby letting devs code/build/test every few minutes without the virtualization overhead. Consequently, orgs can create isolated and repeatable dev environments that are synced through the development lifecycle without resorting to cloud IDEs which have been the bane of many devs’ existences.

• Continuous deployment – As every company becomes a software company at its core, faster release cycles become a source of competitive advantage. This was highlighted in the recent Puppet Labs State of DevOps report, where it was revealed that “high performing IT organizations” deploy code 30x faster and have 200x shorter lead times leading to 60x fewer failures than their “low-performing” peers. It’s no surprise, then, that organizations are embracing continuous delivery practices in earnest. Containers, because of their inherent portability, are an enabler of this software deployment model. Instead of complex scripting to package and deploy application services and infrastructure, with containers scripts shrink to a couple lines to push or pull the relevant image to the right endpoint server and CI/CD becomes radically simplified.

• Microservices – Microservices architecture refers to a development practice of building an application as a suite of modular, self-contained services each running its own process with a minimal amount of centralized management. Microservices itself is a means not an end, enabling greater agility (entire applications don’t need be taken down during change cycles), speed-to-market and code manageability. Containers, offering lightweight isolation, are the key enabling technology for this development paradigm.

Ultimately, containerization allows companies of all sizes to write better software faster. But as with any platform shift, there is a learning curve and broad adoption is a function of ecosystem maturity. We’re just now beginning to see the emergence of best practices and standards via organizations like the Open Container Initiative and the Cloud Native Computing Foundation. The next step is for a hardened management toolchain to emerge which will allow devs and companies to begin building out powerful use cases. And it’s with those applications that we will start to unlock the power of container technology for the masses.

Lenny Pruss

Lenny Pruss

Lenny Pruss is a Principal at Redpoint Ventures and focuses on investments in cloud infrastructure, developer tools, SaaS and security. Prior to Redpoint, Lenny was a Principal at RRE Ventures, a leading early-stage venture fund in New York, where he worked on the firm's investments in Datadog, Flynn, Kryptnostic, WhipTail (acq. by Cisco) and several other companies. Lenny began his career as an Analyst with RRE, and prior to returning there after his MBA he worked as a Product Manager at Dataminr and an Analyst covering software, systems and semiconductor companies at JAT Capital, a multi-billion-dollar technology, media and telecom-focused ('TMT') hedge fund. Lenny holds an MBA from Harvard Business School and a BS from UC Berkeley where he graduated from with honors.

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