Tag Archives: aws

Comparing Docker deployment options in public cloud

Cloud Platforms, Containers & Kubernetes, , , , ,

Few weeks back, I gave a presentation in Container conference, Bangalore comparing different solutions available to deploy Docker in the public cloud.

Slides are available here. I have also put the steps necessary along with short video for each of the options in the github page here.

Abstract of the talk:

Containers provide portability for applications across private and public clouds. Since there are many options to deploy Docker Containers in public cloud, customers get confused in the decision making process. I will compare Docker machine, Docker Cloud, Docker datacenter, Docker for AWS, Azure and Google cloud, AWS ECS, Google Container engine, Azure Container service. A sample multi-container application will be deployed using the different options. The deployment differences including technical internals for each option will be covered. At the end of the session, the user will be able to choose the right Docker deployment option for their use-case.

Note:

  • I have focused mainly on Docker centric options in the comparison.
  • There are few CaaS platforms like Tectonic, Rancher that I have not included since I did not get a chance to try them.
  • Since all the solutions are under active development, some of the gaps will get covered by the solutions in the future.

Hybrid cloud recent solutions from Microsoft and VMWare – 2 different ends of the hybrid cloud spectrum

Cloud Platforms, Containers & Kubernetes, DevOps & Automation, Networking & SDN, Storage & Virtualization, , , , , , , , ,

Public clouds have grown tremendously over the last few years and there are very few companies who do not use public cloud at this point. Even traditional enterprises with in-house data centers have some presence in the public cloud. I was looking at Amazon’s re:Invent conference details and I was amazed by the number of new services and enhancements that were announced this year.  It is very difficult for private clouds to keep up in pace with the new features of public cloud. There is no doubt that public clouds will overtake private clouds in the long term. Private clouds still have a wide deployment and there will be enough use cases for quite some time to deploy private cloud. The use cases includes regulated industries, compute needed in remote locations not having access to public cloud and some specialized requirements that public clouds cannot meet. For some enterprises, private cloud would make more sense from a costing perspective. Having hybrid cloud option is a safe bet for most companies as it provides the best of both worlds. I saw 2 recent announcements in hybrid cloud that captured my attention. One is Azure stack that allows running Azure stack in private cloud. Another is VMWare cloud on AWS that allows running entire VMware stack in AWS public cloud. I see these two services as 2 ends of the hybrid cloud spectrum. In 1 case, public cloud infrastructure software is made to run on private cloud(Azure stack) and in another case, private cloud infrastructure software is made to run on public cloud(Vmware cloud on AWS). In this blog, I have tried to capture more details on these 2 services.

Hybrid cloud

There are predominantly 2 options currently to run Private cloud. 1 option is to use vendor based cloud management software along with hardware from same vendor.

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Vault – Use cases

Cloud Platforms, Containers & Kubernetes, DevOps & Automation, Distributed Systems, Security, , , ,

This blog is a continuation of my previous blog on Vault. In the first blog, I have covered overview of Vault. In this blog, I will cover some Vault use cases that I tried out.

Pre-requisites:

Install and start Vault

I have used Vault 0.6 version for the examples here. Vault can be used either in development or production mode. In development mode, Vault is unsealed by default and secrets are stored only in memory. Vault in production mode needs manual unsealing and supports backends like Consul, S3.

Start Vault server:

Following command starts Vault server in development mode. We need to note down the root key that will be used later.

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Docker for AWS – Deployment options

Cloud Platforms, Containers & Kubernetes,

In this blog, I will cover 5 different options to deploy Docker Containers in AWS infrastructure. There are pros and cons of each option and the goal in this blog is not to suggest that some options are better than others, but to highlight the suitable option for a particular use case. I have taken a sample multi-container application and deployed in all the 5 different models to illustrate this. Following are the 5 options/models discussed in this blog:

  1. Docker Machine for AWS
  2. Docker for AWS
  3. Docker Cloud for AWS
  4. Docker Datacenter for AWS
  5. AWS ECS

I have separate blog for each of the above deployment options which are linked to this blog.

Sample application

Following is the sample application used in this blog:

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AWS ECS – Docker Container service

Cloud Platforms, Containers & Kubernetes,

In this blog, I will cover AWS ECS Docker Container service. ECS is an AWS product. This blog is part of my Docker for AWS series and uses the sample voting application for illustration.

AWS has EC2 Container service(ECS) for folks who want to deploy Docker containers in AWS infrastructure. For basics of AWS ECS, you can refer to my previous blog here. With ECS, Amazon provides its own scheduler to manage Docker containers. ECS integrates very well with other AWS services including load balancer, logging service, cloudformation templates etc. AWS recently introduced Application load balancer(ALB) that does L7 load balancing and this integrates well with ECS. Using ALB, we can load balance services directly across Containers. With ECS, users get charged for the EC2 instances and not for the Containers.

To demonstrate ECS usage, we will deploy voting service application in ECS cluster.

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Docker Datacenter for AWS

Cloud Platforms, Containers & Kubernetes,

In this blog, I will cover Docker datacenter usage with AWS. This blog is part of my Docker for AWS series and uses the sample voting application for illustration.

Docker Datacenter is Docker’s enterprise grade CaaS(Container as a service) solution where they have integrated their open source software with some proprietary software and support to make it into a commercial product. Docker Datacenter can be deployed on-premise or in cloud providers like AWS. Docker Datacenter is available free for 30 day trial period.

Docker Datacenter Architecture

Following picture shows the core components of Docker Datacenter:

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Docker Cloud for AWS

Cloud Platforms, Containers & Kubernetes, ,

In this blog, I will cover Docker cloud usage with AWS. This blog is part of my Docker for AWS series and uses the sample voting application for illustration.

Docker cloud is a hosted service from Docker to manage Containers. Docker cloud is free to try for 1 private repository and node and is chargeable after that. Docker cloud was originally an acquisition from Tutum. Docker cloud can be used to manage infrastructure nodes in the cloud or nodes in the local data center. For basics on Docker cloud/Tutum, please refer to my earlier blog here. Since Docker cloud was an acquisition, it does not use some of the Docker ecosystem software. Following are some important differences:

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Docker for AWS beta

Cloud Platforms, Containers & Kubernetes,

In this blog, I will cover “Docker for AWS” beta service launched by Docker. This blog is part of my Docker for AWS series and uses the sample voting application for illustration.

As part of Docker 1.12 announcement, Docker released AWS Docker integration as beta software. With this software, Docker is trying to  simplify AWS integration by better integrating Docker with AWS services like load balancer, security groups, logs etc. Docker launched similar integration service with Microsoft Azure as well. Docker 1.12 RC4 is available as part of this integration, so Swarm mode feature can be used.
Following are some features that Docker has added as part of this integration with AWS:

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Microservices Infrastructure using Mantl

Cloud Platforms, Containers & Kubernetes, DevOps & Automation, Distributed Systems, Networking & SDN, , , , , , , , , , ,

Mantl is an Open source project from Cisco and it provides an integrated solution to deploy distributed Microservices. Any company deploying Microservices has to integrate different components before the solution becomes production ready. Mantl makes it easier by integrating the different components and providing the glue software that integrates the components. In this blog, I will cover the following:

  • Distributed Microservice infrastructure components and the need for Mantl.
  • Mantl Architecture.
  • Mantl installation using Vagrant
  • Mantl installation using AWS public cloud

Microservices infrastructure

Following are typical components in Container based Microservices infrastructure:

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Baremetal cloud using Packet

Cloud Platforms, Containers & Kubernetes, Networking & SDN, Storage & Virtualization, , , , ,

Typical Opensource demo applications comes packaged as a Vagrant application which starts a bunch of VMs and does automatic provisioning. I have a Windows machine with Virtualbox and VMWare player installed. Since Virtualbox does not support nested virtualization with 64 bit VMs(More details can be found in my previous blogs on Virtualbox and VMWare player), I use VMWare player to try out demo applications that needs 64 bit VMs. The demo applications typically run on Linux, so running them on Windows with Virtualbox is ruled out. I was recently trying this Mantl project for deploying distributed microservices and I found that it was very slow to run in VMWare player with nested virtualization. I tried to run the application in AWS and I found that AWS does not support nested virtualization(More details can be found here). Then I tried out Google cloud. Even though Google cloud supports nested virtualization, hardware virtualization is disabled on the guest VMs and this prevents running 64 bit VMs inside Google cloud VMs. After I ran out of these options, I stumbled upon the possibility of using baremetal cloud. I used baremetal cloud from Packet and it worked great for my usecase mentioned above. Though this is not a typical use case, I was very happy with the performance and the possibilities that this provides. In this blog, I will share the use cases for baremetal cloud and my experiences with using Packet service.

Bare metal cloud Use case

Typical cloud providers like Amazon, Google, Digitalocean, Microsoft rent out VMs as part of their compute offering. These VMs run on top of a hypervisor. Though the user is guaranteed a specific performance, these VMs share the same resources with other VMs running on the same host machine. With bare metal cloud, the cloud provider hosts machines that the user can rent which is not shared with anyone. Cloud providers provide different configurations for bare metal and the user can choose based on their performance needs and the costing is based on the performance provided by the bare metal server. Following are some advantages that bare metal cloud provides:

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