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Couchbase Containers with Bare Metal Performance

Presentation given at CouchbaseConnect '15, held at Levi's Stadium in Santa Clara, California. Video is at

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Couchbase Containers with Bare Metal Performance

  1. 1. Couchbase Containers with Bare Metal Performance CTO Bryan Cantrill @bcantrill
  2. 2. Elastic infrastructure, circa Dot Com Boom • In the late 1990s, the only way to meaningfully scale a database was up — and the physical infrastructure had to scale with it • This was excruciatingly expensive — and became a non-starter in the post-apocalyptic nuclear winter of the early 2000s...
  3. 3. Elastic infrastructure, circa Dot Com Bust • The rise of rack-and-stack commodity servers brought with it new distributed software architectures like memcached that were designed to scale across many machines • The rise of these architectures afforded new operational possibilities: if the computer itself is a commodity, why buy it at all? Why not rent from someone who runs it cheaper and better? • From the perspective of compute providers, economies of scale could only be realized if hardware is shared across tenants... • Multi-tenancy demands virtualization, but where in the stack to virtualize?
  4. 4. Hardware-level virtualization? • The historical answer to virtualization — since the 1960s — has been to virtualize the hardware: • A virtual machine is presented upon which each tenant runs an operating system that they choose (and must manage) • There are as many operating systems on a machine as tenants! • Can run entire legacy stacks unmodified... • ...but operating systems are heavy and don’t play well with others with respect to resources like DRAM, CPU, I/O devices, etc. • Hardware-level virtualization limits tenancy and performance!
  5. 5. Platform-level virtualization? • Virtualizing at the application platform layer addresses the tenancy challenges of hardware virtualization, and presents a much more nimble (& developer friendly!) abstraction... • ...but at the cost of dictating abstraction to the developer • This is the “Google App Engine” problem: developers are in a straightjacket where toy programs are easy — but sophisticated applications are impossible • Virtualizing at the application platform layer poses many other challenges with respect to security, containment, etc.
  6. 6. OS-level virtualization! • Virtualizing at the operating system hits a sweet spot: • A single operating system (i.e. a single kernel) allows for efficient use of hardware resources, maximizing tenancy and performance • Disjoint instances are securely compartmentalized by the operating system • Gives tenants what appears to be a virtual machine (albeit a very fast one) on which to run higher-level software: PaaS ease with IaaS generality • Applications run directly on the hardware! • Model was pioneered by FreeBSD jails and taken to their logical extreme by Solaris zones — and then aped by Linux containers
  7. 7. OS-level virtualization 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 • We emphasized their operational characteristics — performance, elasticity, tenancy — and for many years, we were a lone voice...
  8. 8. 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...
  9. 9. ...and Docker was born
  10. 10. 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 will do to apt what apt did to tar
  11. 11. 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 (!!) • Deploying OS containers in hardware virtual machines negates their economic advantage!
  12. 12. 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 are some obvious obstacles...
  13. 13. 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...
  14. 14. LX-branded zones: tl;dr
  15. 15. LX-branded zones: tl;dr, cont.
  16. 16. 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...
  17. 17. 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
  18. 18. 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 • All of the components to Triton are open source: you can download and install SmartDataCenter and run it yourself • Triton is currently in early access at Joyent — and moving into general availability in Q2CY2015
  19. 19. Container landscape • It is becoming broadly clear that containers are the future of application development and (especially) deployment • But the upstack ramifications are entirely unclear — there are many rival frameworks for service discovery, deployment, 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
  20. 20. Containers and Couchbase • Couchbase is particularly appropriate for containers: its scale-out architecture demands elastic infrastructure — and its use cases demand on-the-metal performance • But hardware-virtualized Docker hosts undermine the efficacy of containers — and force an allocation-oriented disposition instead of allowing a consumption-oriented one • The Triton model represents Couchbase containers without compromise: like Couchbase itself, the infrastructure can grow as needed — while still delivering bare-metal performance!
  21. 21. Future of containers • For nearly a decade, we have believed that OS-virtualized containers represent the future of computing — and with the rise of microservices + 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!
  22. 22. Thank you! • @joshwilsdon, @trentmick, @cachafla, @orlandov, @fredfkuo and @notmatt and Todd Whiteman for their work on sdc-docker • Jerry Jelinek, @pfmooney, @jmclulow, @rmustacc and @jperkin for their work on LX branded zones • The countless engineers who have worked on or with SmartOS because they believed in OS-based virtualization before the rest of the world figured it out