Container prehistory • Containers are not a new idea, having originated via filesystem containers with chroot in Seventh Edition Unix • chroot originated with Bill Joy, but specifics are blurry; according to Kirk McKusick, via Poul-Henning Kamp and Robert Watson:
Container limitations • The (prioritized) design constraints for OS-based virtualization as originally articulated by zones: Security, Isolation, Virtualization, Granularity, Transparency • Not among these: running foreign binaries or emulating other operating systems! • Despite its advantages in terms of tenancy and performance, OS- based virtualization didn’t fit the problem ca. early 2000s: needed the ability to consolidate entire stacks (i.e. Windows)
Hardware-level virtualization • Since the 1960s, the preferred approach for operating legacy stacks unmodified has been to virtualize the hardware • A virtual machine is presented upon which each tenant runs an operating system that they choose (but must also manage) • Effective for running legacy stacks, but with a clear inefficiency: there are as many operating systems on a machine as tenants: • Operating systems are heavy and don’t play well with others with respect to resources like DRAM, CPU, I/O devices, etc.! • Still, hardware-level virtualization became de facto in the cloud
Containers at Joyent • Joyent runs OS containers in the cloud via SmartOS — and we have run containers in multi-tenant production since ~2006 • Adding support for hardware-based virtualization circa 2011 strengthened our resolve with respect to OS-based virtualization • OS containers are lightweight and efficient — which is especially important as services become smaller and more numerous: overhead and latency become increasingly important! • We emphasized their operational characteristics — performance, elasticity, tenancy — and for many years, we were a lone voice...
Containers as PaaS foundation? • Some saw the power of OS containers to facilitate up-stack platform-as-a-service abstractions • For example, dotCloud — a platform-as-a-service provider — built their PaaS on OS containers • Struggling as a PaaS, dotCloud pivoted — and open sourced their container-based orchestration layer...
Docker revolution • Docker has used the rapid provisioning + shared underlying filesystem of containers to allow developers to think operationally • Developers can encode deployment procedures via an image • Images can be reliably and reproducibly deployed as a container • Images can be quickly deployed — and re-deployed • Docker complements the library ethos of microservices • Docker will do to apt what apt did to tar
Broader container revolution • The Docker model has pointed to the future of containers • Docker’s challenges today are largely operational: network virtualization, persistence, security, etc. • Security concerns are not due to Docker per se, but rather to the architectural limitations of the Linux “container” substrate • For multi-tenancy, state-of-the-art for Docker containers is to run in hardware virtual machines as Docker hosts (!!) • Deploying OS containers via Docker hosts in hardware virtual machines negates their economic advantage!
Container-native infrastructure? • SmartOS has been container-native since its inception — and running in multi-tenant, internet-facing production for many years • Can we achieve an ideal world that combines the development model of Docker with the container-native model of SmartOS? • This would be the best of all worlds: agility of Docker coupled with production-proven security and on-the-metal performance of SmartOS containers • But there were some obvious obstacles...
Docker + SmartOS: Linux binaries? • First (obvious) problem: while it has been designed to be cross- platform, Docker is Linux-centric — and the encyclopedia of Docker images will likely forever remain Linux binaries • SmartOS is Unix — but it isn’t Linux… • Fortunately, Linux itself is really “just” the kernel — which only has one interface: the system call table • We resurrected (and finished) a Sun technology for Linux system call emulation, LX-branded zones, the technical details of which are beyond the scope of this presentation...
Docker + SmartOS: Provisioning? • With the binary problem being tackled, focus turned to the mechanics of integrating Docker with SmartOS provisioning • Provisioning a SmartOS zone operates via the global zone that represents the control plane of the machine • docker is a single binary that functions as both client and server — and with too much surface area to run in the global zone, especially for a public cloud • docker has also embedded Go- and Linux-isms that we did not want in the global zone; we needed to find a different approach...
Docker Remote API • While docker is a single binary that can run on the client or the server, it does not run in both at once… • docker (the client) communicates with docker (the server) via the Docker Remote API • The Docker Remote API is expressive, modern and robust (i.e. versioned), allowing for docker to communicate with Docker backends that aren’t docker • The clear approach was therefore to implement a Docker Remote API endpoint for SmartDataCenter, our (open source!) orchestration software for SmartOS
Triton: Docker + SmartOS • In March, we launched Triton, which combines SmartOS and SmartDataCenter with our Docker Remote API endpoint • With Triton, the notion of a Docker host is virtualized: to the Docker client, the datacenter is a large Docker host • One never allocates VMs with Triton; all Triton containers are run directly on-the-metal • All of the components to Triton are open source: you can download and install SmartDataCenter and run it yourself • Triton is currently general available on the Joyent Public Cloud!
Container landscape • It is becoming broadly clear that containers are the future of application development and deployment • But the upstack ramifications are entirely unclear — there are many rival frameworks for service discovery, composition, etc. • The rival frameworks are all open source: • Unlikely to be winner-take-all • Productive mutation is not just possible but highly likely • Triton takes a deliberately modular approach: the container as general-purpose foundation, not prescriptive framework
Realizing the container revolution • The container revolution extends beyond traditional computing — it changes how we think of computing with respect to other elements of the stack • e.g. container-centric object storage allows us to encapsulate computation as containers that can process data in situ — viz. Joyent’s (open source!) Manta storage service • Realizing the full container revolution requires us to break the many-to-one relationship between containers and VMs!
Future of containers • For nearly a decade, we have believed that OS-virtualized containers represent the future of computing — and with the rise of Docker, this is no longer controversial • But to achieve the full promise of containers, they must run directly on-the-metal — multi-tenant security is a constraint! • The virtual machine is a vestigial abstraction; we must reject container-based infrastructure that implicitly assumes it • Triton represents our belief that containers needn’t compromise: multi-tenant security, operational elasticity and on-the-metal performance!
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