Choosing PaaS: Cisco and Open Source Options: an overview
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This document discusses container platforms and PaaS. It provides context on containers and supporting technologies like Docker. It describes how containers are limited when confined to a single host, and how schedulers can distribute containers across multiple hosts. It outlines common production tools used with containers like configuration management, monitoring, and logging. It compares PaaS and containers, noting how PaaS consumed containers before they were widely known, and how the lines between the two are blurring as container platforms provide more services. It introduces Mantl as Cisco's container stack designed to run container workloads and big data applications across clouds.
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Choosing PaaS: Cisco and Open Source Options: an overview
- 1. Container Platforms and PaaS Overview • Ann Wallace @randombug Matt Johnson @mattdashj • February, 2016 • Cisco Cloud Innovation Team
- 3. • A wonderful packaging & portability layer for applications. Containers.. Container Your code Your startup scripts Code Dependencies Should deploy with exactly the same behavior on any Host/VM that can run containers. NB: Containers != Microservices
- 4. • Supporting technologies. Containers.. Container Docker Engine Alternatives to docker engine here: Rkt (rocket) Linux Kernel Technologies: LXC / CGroups / ‘Namespaces’ Single Host / VM LXC/CGroups existed before anyone cared. Docker just made using these tools easier for the masses and adoption followed. UX important in this ecosystem. They use CGroups (Linux kernel feature) to do this. You’ll also hear ‘LXC’ used to refer to this tech. Containers ‘WORK’ by hiding themselves from other processes / containers on the same VM/Host without the need for VM’s.
- 5. • Moving beyond single host. • Containers aren't too great if they never leave the developer’s mac.. • Or if you have to manage them like this... Containers .. Container Docker Engine Linux Kernel Host / VM 1 Host / VM 2 Host / VM 3 Linux KernelLinux Kernel Docker Engine Docker Engine ContainerContainer $ssh host1 host1# docker run container $ssh host2 host2# docker run container $ssh host3 host3# docker run container
- 6. • Create a pool of resource for throwing containers at Containers + Schedulers .. Container Linux Kernel Host / VM 1 Host / VM 2 Host / VM 3 Linux KernelLinux Kernel Docker Engine ContainerContainer Scheduler API (HTTP POST): Run three instances of my container. Docker Engine Docker Engine Container Scheduler (Distributed, Clustered) API for Developers Linux Kernel Host / VM 4 Scheduler State DB Docker Engine
- 7. • Getting to production • We need supporting players Containers + Schedulers .. Container Linux Kernel Host / VM 1 Host / VM 2 Host / VM 3 Linux KernelLinux Kernel Docker Engine ContainerContainer Docker Engine Docker Engine Container Scheduler (Distributed, Clustered) API Linux Kernel Host / VM 4 DB Docker Engine Deployment / Provisioning. IaaS/VM’s Deployment / Provisioning. Install & configure components Monitoring & Statistics Gathering Log & Metrics collection & Visibility - Automation - Deployment - Configuration - Health - Assurance - Logs - Audit
- 8. • Commonly implemented tools.. Containers + Schedulers + Production Tooling Container Linux Kernel Host / VM 1 Host / VM 2 Host / VM 3 Linux KernelLinux Kernel Docker Engine ContainerContainer Docker Engine Docker Engine Container Scheduler (Distributed, Clustered) API Linux Kernel Host / VM 4 DB Docker Engine Terraform – Provision & Configure VM’s in IaaS Ansible, puppet, chef, configuration management for you VM’s Sensu, Nagios, collectd, syslog, cadvisor (collect container stats) ELK Stack ELK: Elasticsearch, logstash and Kibana. Three open source tools that form a scalable pipeline for taking, processing, storing and visualizing system / app log data
- 9. Containers + Schedulers + Production Tooling + Operators + Documentation = Container Stack Container Linux Kernel Host / VM 1 Host / VM 2 Host / VM 3 Linux KernelLinux Kernel Docker Engine ContainerContainer Docker Engine Docker Engine Container Scheduler (Distributed, Clustered) API Linux Kernel Host / VM 4 DB Docker Engine Terraform – Provision & Configure VM’s in IaaS Ansible, puppet, chef, configuration management for you VM’s Sensu, Nagios, collectd, syslog, cadvisor (collect container stats) ELK Stack People (Ops) Documentation A lot of the ‘DevOPS’ tooling/movement assumes this stack is consumed ‘as a Service’ from the cloud. If you need containers on prem and/or cross-cloud (with zero lock in); you’ll likely need an open container stack. People (Ops) Container Stack DevOps (development teams)
- 10. Context PaaS Aka. Containers != Microservices
- 11. • PaaS consumed containers; before Containers were a ‘thing’* PaaS Container Stack Throwing containers at a pool of resource via an API. Built-in Infrastrucure services. Conversation lines blurring. Some “PaaS vs Container” conversations will get harder without context. * Statement refers to “common understanding” and excludes veterans familiar with mainframe, Solaris zones and other container tech 10+ years ago Developer UI’s + ‘Templates’ CI/CD Integration - Pipelines Service Integration Providing a “developer experience”. Saving time, building pipelines, providing integrations. Still ends up deploying the developers apps, in containers, down onto a container stack. Service Discovery Integration
- 13. PaaS vs Containers All custom components. uses Warden/Garden containers instead of docker containers for the container stack. - ‘Microservices all the way’. - Code changes for goodies! - Service Integration API’s. - ”Mature” - HTTP / HTTPS Apps only. ‘PaaS’ becomes the ‘consumption’ interface on an orchestrated pool of resource. That interface may perfectly solve your problems, or may prevent you carving your own path at the container layer (opinionated Platform) Container stack gives you access to ‘Warden/Garden’ if you want it. Can do more, less opinionated. Easier to shoot yourself in the foot without a ‘PaaS-Like’ frontend or process.
- 14. Ecosystems moving closer PaaS Not a magic Bullet Containers Not a magic Bullet More use cases. Shared Resources Rapid consumption of the strengths and services from each ecosystem. No ‘copy and paste’ re-work needed to support something in the other ecosystem.
- 15. Vision. More use cases. Shared Resources An open, transparent ‘Container Stack’. - Forms a foundation for a range of developer experience interfaces. - Supports integration with new and legacy services. - Doesn’t ignore Enterprise issues.
- 16. Cisco’s answer to needing a container stack. An end to end, cloud agnostic, highly extensible, integrated stack for running container workloads and big data. Including Deployment automation, security, and monitoring. Designed to grow into a platform for application and data services. Introducing Mantl
- 18. • At its core, Mesos is a focused, scalable, two phased meta-scheduler that provides primitives to express a wide variety of scheduling patterns and use cases. • Solutions are written atop of Mesos as frameworks. • The technology allows you to utilize the same machines for both long running (Docker) and batch (Hadoop) workloads • Mature at Scale, successfully powering Twitter, Airbnb and Apple’s Siri voice interpreter application among others • Functioning Big Data Toolset including Logstash, Cassandra, Spark and Hadoop frameworks available with one-click deployments What is Mesos?
- 20. Questions?
- 21. More info? See us at the cloud booth in DevNet More Presentation? Brian Hicks talking Mantl; tomorrow at 9am.