Cloud Computing

Handing Bastion Hosts on AWS via SSH Agent Forwarding

What is a Bastion Host?

Bastion hosts are instances that sit within your public subnet and are typically accessed using SSH (for Linux) or RDP (for Windows). It acts as a ‘jump’ server, allowing you to use SSH or RDP to login to other instance in private subnet.

[Source: AWS Documentation]

High Availability (HA) can be ensured for Bastion hosts by having multiple bastion hosts in each availability zone, with each bastion host is mapped to an Auto scaling group

A NAT instance is, like a bastion host, lives in your public subnet. A NAT instance, however, allows your private instances outgoing connectivity to the Internet (to get updates), while at the same time blocking inbound traffic from the Internet.

It is required to use Elastic IP addresses for bastion hosts mainly if you are using high availability scenarios.

The following are the best practices while configuring a bastion host

1. Never place your SSH private keys within a bastion hosts/ server. As suggested, use SSH Agent Forwarding for this task to connect first to the bastion host then to other instances on the private subnets. This lets you keep the private keys only with your servers.

2. Make sure the security group on the bastion host to allow SSH (port 22) to connect only from your trusted hosts and never from 0.0.0.0/0 mask.

3. Always have more than one bastion. For example, having a bastion host for each Availability Zone (AZ).

4. Make sure to configure security groups on private subnets to accept SSH traffic only from the bastion hosts.

How to handle Bastion hosts via SSH Agent Forwarding?

SSH Agent:

The SSH agent handles signing of authentication data for you. When authenticating to a server, you are required to sign some data using your private key, to prove that you are. As a security measure most people sensibly protect their private keys with a pass phrase, so any authentication attempt would require you to enter this pass-phrase. This can be undesirable, so the ssh agent caches they key for you and you only need to enter the password once, when the agent wants to decrypt it.

The SSH agent never hands these keys to client programs, but merely presents a socket over which clients can send it data and over which it responds with signed data. A side benefit of this is that you can use your private key even with programs you don’t fully trust.

Another benefit of the SSH agent is that it can be forwarded over SSH. So when you ssh to host A, while forwarding your agent, you can then ssh from A to another host B without needing your key present (not even in encrypted form) on host A.

These SSH Agents can not only be used when the paraphrase is being used. This can be successfully used in Bastion hosts. Rather copying the PEM (rather the private key) to the Bastion host, it is more secure to hand this process to SSH Agents. That would be more secure and easy!. So here are the simple steps to follow if you are to do this task. However, if you are running this on heavily secured environment with well designed Security groups and NACLs, it is always good to have a complete idea before executing this. Otherwise you will end up having too many confusions. If all well, this works like a charm!

Step 1: Adding the private key (PEM file) to the key chain. This allows the user to access the private instances without copying to the bastion host. This adds an additional layer of security.

$ ssh-add -k <PEM_file_name>

Step 2: Check whether the private key is properly added to the key chain

$ ssh-add -L

The above will list all the keys added to the chain. Check whether the key you added is listed there.

Step 3: Access the Bastion Host (Public instance)

$ ssh -A ec2-user@<bastion-host-elastic-ip>
[Here ec2-user is the user for the Linux instance]

Step 4: Access the private instance

$ ssh ec2-user@<private-instance-ip>

References:

1. Securely connect to Linux instances running in a private Amazon VPC

2. An illustrated guide to SSH agent forwarding

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Towards a Cloud Enabled Data Intensive Digital Transformation

Today (08/07/2018) I had the privilege to do a 1 hour presentation on “Towards a Cloud Enabled Data Intensive Digital Transformation” for Jaffna University IT students. I hope they were able to learn something out of this presentation. You can reach the slide deck using the following link:

https://www.slideshare.net/crishantha/towards-cloud-enabled-data-intensive-digital-transformation

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SMACK Stack for building Data Intensive Enterprise Applications

With the advent of Big Data, the enterprise applications nowadays are following a Data Intensive microservices based enterprise application architecture deviating more monolithic architectures, which we have been used to decades.

These data intensive applications should meet a set of requirements.

1. Ingest Data at Scale without a loss

2. Analyze data in real-time

3. Trigger action based on the analyzed data

4. Store the data at cloud-scale.

5. Need to run in a distributed and highly resilient cloud platform

The SMACK is such a stack, which can be used for building modern enterprise applications because it can performs each of the above objectives with a loosely coupled tool chain of technologies that are are all open source, and production-proven at scale.

(S – Spark, M – Mesos, A – Akka, C – Cassendra, K – Kafka)

  • Spark – A general engine for large-scale data processing, enabling analytics from SQL queries to machine learning, graph analytics, and stream processing
  • Mesos – Distributed systems kernel that provides resourcing and isolation across all the other SMACK stack components. Mesos is the foundation on which other SMACK stack components run.
  • Akka – A toolkit and runtime to easily create concurrent and distributed apps that are responsive to messages.
  • Cassandra – Distributed database management system that can handle large amounts of data across servers with high availability.
  • Kafka – A high throughput, low-latency platform for handling real-time data feeds with no data loss.
SMACK Stack

SMACK Stack

Source: www.mesosphere.com

SMACK Data Pipeline

Source: www.mesosphere.com

The following commercial options available for some of the components of SMACK.
1. Spark – Lightbend and Databricks
2, Cassendra – DataStax
3. Kafka – Confluent
4. Mesos – Mesosphere DC/OS
References:
1. Building Data-Rich apps with “SMAL” stack – https://www.youtube.com/watch?v=jV1WsUuQNck
2. The SMACK Stack is the new LAMP Stack – https://mesosphere.com/blog/smack-stack-new-lamp-stack/
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AWS Serverless Application Module (SAM)

Developer Tools for Serverless Applications on AWS

AWS and its ecosystem provide frameworks/ tools, which help you develop serverless applications on AWS Lambda and other AWS services. These will help you rapidly build, test, deploy, and monitor serverless applications.

Frameworks

There are multiple AWS / open source frameworks available in the market today to simplify serverless application development and deployment.

1. AWS Server Application Model (SAM)

2. Open Source third party frameworks (Apex, Chalice, Clauda.js, Serverless Express, Serverless Framework, Serverless Java Container, Sparta, Zappa)

1.) AWS SAM

For simple applications it is good to use normal Lambda console. However, for complex applications, it is recommended to use AWS SAM. AWS SAM is an “abstraction” of Cloudformation (Infrastructure As Code), which is optimized for serverless applications. It supports anything that Cloudformation supports and it is an Open Specification under Apache 2.0 License.

AWS SAM Local Client

AWS SAM Local is a complementary CLI tool that lets you locally test Lambda functions defined by AWS SAM templates.You can plug this client tool into any of your favorite IDE for higher fidelity testing and debugging.

AWS Cloud9

Now AWS introduced a new IDE for serverless development called AWS Cloud9. This has integrated all the required components for serverless development and testing without relying on any other tool/ IDE.

However, the deployment aspect was missing in AWS SAM and recently that was also added to the AWS SAM to automate the incremental deployments into AWS Lambda. This further allows to roll-out new versions to production in an incremental manner.

2). Open Source third party frameworks (Serverless Framework)

Please do have a look at my previous blog for an article on the Serverless Framework.

References:

1. Developer Tools for Serverless Applications – https://aws.amazon.com/serverless/developer-tools/

2, Comparing AWS SAM with the Serverless Framework – https://sanderknape.com/2018/02/comparing-aws-sam-with-serverless-framework/

3. AWS SAM – https://github.com/awslabs/serverless-application-model

4. AWS SAM Local – Build and Test Serverless Applications Locally – https://aws.amazon.com/blogs/aws/new-aws-sam-local-beta-build-and-test-serverless-applications-locally/

YouTube References:

1. Authoring and Deploying Serverless Applications with AWS SAM: – https://www.youtube.com/watch?v=pMyniSCOJdA

2. Serverless Architecture Patterns and Best Practices – https://www.youtube.com/watch?v=_mB1JVlhScs

3. Building CI/CD Pipelines for Serverless Applications – https://www.youtube.com/watch?v=9uOl3B88bcY

4. AWS Serverless Application Model (SAM) Implementation is Now Open-Source  – Apr 10, 2018 – AWS Launchpad San Francisco – https://www.youtube.com/watch?v=uxv1dOExq5U

5. Deep Dive SAM: Build on Serverless | Get Started with AWS SAM Open Source – May 3, 2018 -  https://www.youtube.com/watch?v=d7e1L4U7_Vc
6. Development with SAM Local: AWS re:Invent 2017: Local Serverless Development using SAM Local (DEM77) – Dec 6, 2017 -  https://www.youtube.com/watch?v=oGawhLx3Dxo
7. DevOps Orchestration for Serverless Solutions and SAM: AWS re:Invent 2017: Building CI/CD Pipelines for Serverless Applications (SRV302) – Dec 1, 2017 – https://www.youtube.com/watch?v=dCDZ7HR7dms

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Securing AWS Lambda Functions

The Default Security – (Permissions)

By default Lambda functions are “not” authorized to do access other AWS services. Hence, it is required to explicitly give access (permissions) to each and every AWS service.(i.e. accessing S3 to store images, accessing external databases such as DynamoDB, etc). These permissions are managed by AWS IAM roles.

Changing the Default Security – (Permissions)

If you are using the Serverless Framework you can customize the default settings by changing the serverless.yaml file (in the “iamRoleStatements:” block).

For example,

iamRoleStatements:
    - Effect: "Allow"
      Action:
        - "lambda:*"
      Resource:
        - "*"

The above will “Allow” all (“*”) to be invoked from the Lambda Function.

The Default Security – (Network)

By default, Lambda functions are not launched in a VPC. But you can change this by creating a Lambda function within a VPC. Furthermore, you can extend further by applying “Security Groups” as an additional layer of security within a VPC.

Changing the Default Security – (Network)

If you are using the Serverless Framework you can customize the default settings by changing the serverless.yaml file. Here is the code snippet that might use for this.

provider:
  name: aws
  runtime: python2.7
  profile: serverless-admin
  region: us-east-1

  vpc:
    securityGroupIds:
      - <security-group-id>
    subnetIds:
      - <subnet-1>
      - <subnet-2>
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The Serverless Framework with AWS

The Serverless Framework (https://serverless.com/framework/) is an open-source CLI for building serverless architectures to cloud providers (AWS, Microsoft Azure, IBM OpenWhisk, Google Cloud Platform, etc).

This article will brief you on the important steps you may require to get on with the AWS platform. This Framework works well with CI/CD tools and has the full support of AWS CloudFormation. With this it can provision your AWS Lambda functions,events, and infrastructure resources.

Step 1: Installing NodeJS

Serverless is a Node.js CLI tool so the first thing you need to do is to install Node.js on your machine. Refer the official NodeJS web site and download and follow the instructions to install NodeJS.

Serverless Framework runs on Node v6.5.0 or higher. You can verify that NodeJS is installed successfully by executing node -v in your terminal.

If all fine, we may proceed to the second step.

Step 2: Installing Serverless Framework

$ npm install -g serverless

Once installed, you may verify it.

$ serverless --version

Step 3: Setting up Cloud Provider (AWS) Credentials

The Serverless Framework needs access to your cloud provider’s account so that it can create and manage resources on your behalf. You may set it up with this Youtube link

Once above is completed, you may add the AWS credentials to your client machine to work as a CLI. You may use the following command to do that.

$ serverless config credentials --provider aws --key XXXXXXXXXXXXXXXXX --secret XXXXXXXXXXXXXXXXX --profile serverless-admin

This will basically add an entry to the credentials file, which is located in the $<home-folder>/.aws folder. (assumes the AWS user is serverless-admin)

[serverless-admin]
aws_access_key_id = XXXXXXXXXXXXXXXX
aws_secret_access_key = XXXXXXXXXXXXXXXXXXXXXXXXXXX

If all above is OK, you are ready to create your first Serverless function (Lambda Function) with AWS.

Step 3: Creating your Serverless Project

You may build your projects based on the templates/ archetypes given by the framework.

By default, there are multiple templates/ archetypes given. (i.e. “aws-nodejs”, “aws-python”, “aws-python3″, “aws-groovy-gradle”, “aws-java-maven”, “aws-java-gradle”, “aws-scala-sbt”, “aws-csharp”, etc)

So lets create a “aws-python” project for fun…

$ serverless create --template aws-python --path hello-world-python

The above will create a folder named “hello-world-python”.

Just browse the folder. You would see two files.

1. handler.py – (This is the Serverless Function. Your Business Logic goes here)

Here just edit the handler.py to have a simple output.

def hello(event, context):
        print "Hello Crishantha"
        return "Hello World!"

2. serverless.yml – (The Serverless Function Configuration.)

P.Note: You may check the following configuration especially before you executing the rest of the key commands

If you are new to YAML and know JSON well, you may use https://www.jason2yaml.com link to convert JSON to YAML and vice versa.

provider:
  name: aws
  runtime: python2.7
  profile: serverless-admin
  region: us-east-1

If all above is ok, you are good to go and deploy the function on AWS. So lets move to the next step. (Step 4)

Step 4: Deploy the Serverless Function

As explained, move to “hello-world-python” folder and execute the following command.

$ serverless deploy -v

The above will run the automated script creating all the background scripts including CloudFormation scripts to deploy the respective application. It is pretty awesome!

Step 5: Invoke the Serverless Function

Use the following to see the output.

$ serverless invoke -f hello -l

The above will return a simple “hello” for you (The output that you have mentioned in the handler.py)

It is that simple!!!

Step 6: Verify

If you want to verify all this, you can log in to the AWS console and see what you have done is reflected in the AWS Lambda area. Sure you will.

Step 7: Remove All

OK. We just did some testing. So probably you want to remove the serverless function and all its dependencies (IAM roles, Cloudwatch Log groups, etc)

- Move to the folder that the function that you want to delete.

- Execute the following

$ serverless remove

The above will clean the whole thing up!…

So, if you are a AWS Developer, you may find it very useful as much as I do at the moment. Happy Coding!

[References]

1. Serverless Framework Page – https://serverless.com/framework/docs/providers/aws/guide/services/

2. AWS Provider Documentation – https://serverless.com/framework/docs/providers/aws/

3. Serverless AWS Lambda Guide – https://serverless.com/framework/docs/providers/aws/guide/

4. Serverless Framework GitHub – https://github.com/serverless/serverless

5. YAML to JSON tool – https://www.jason2yaml.com

6. The Serverless Framework: A deep overview of the best AWS Lambda + API Gateway Automation Solution – https://cloudacademy.com/blog/serverless-framework-aws-lambda-api-gateway-python/

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Connecting to a remote MYSQL instance on a AWS EC2 instance

If you are having a “self-managed” MySQL EC2 instance, which can be connected to other EC2 instances in the same VPC or even other remote machines. In order to do this, there are a few configuration changes you need to carry out.

Here are the steps:

1. Connect to the remote MySQL remote EC2 instance. – On default you can access the MySQL using “root” user. However it is not advisable to access a MySQL instance remotely using the “root” user for security reasons.

[P.Note: Please make sure the Port 3306 is added to the inbound rules in the EC2 Security Group prior attempting this.]

2. Change the <bind-address> parameter to 0.0.0.0, allowing the access to all remote addresses. This needs to be changed in the /etc/mysql/mysql.conf.d/my.cnf file.

3. Restart the MySQL instance

mysql-ec2-instance>> sudo /etc/init.d/mysqld restart

4. Therefore, create a new MySQL user. – For this, you are required to sign in to the MySQL and execute the following command(s).

mysql-ec2-instance>> mysql -u root -p<root-password>

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql> CREATE USER 'user'@'localhost' IDENTIFIED BY 'user123';

mysql> CREATE USER 'user'@'%' IDENTIFIED BY 'user123';

mysql> GRANT ALL PRIVILEGES ON *.* to user@localhost IDENTIFIED BY 'user123' WITH GRANT OPTION;

mysql> GRANT ALL PRIVILEGES ON *.* to user@'%' IDENTIFIED BY 'user123' WITH GRANT OPTION;

mysql> FLUSH PRIVILEGES;

mysql> EXIT;

5. Now exit from the EC2 MySQL instance and try to log into the MySQL EC2 instance from your local machine.

your-local-machine>> mysql -h <ec2-public-dns-name> -u user -puser123

If all fine, you should be able to sign in to the remote EC2 instance without any issue!!

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Docker on Ubuntu 16.04 LTS – [Part 04] Docker Compose

Currently, Docker is the most popular and widely used container management system. In most of our enterprise applications nowadays, we do tend to have components running in separate containers. In such an architecture, the “container orchestration” (starting/ shutting down containers and setting up intra-container linkages) is an important factor and the Docker community came up with a solution called Fig, which basically handled this requirement. This uses a single YAML file to orchestrate all your Docker containers and configurations. The popularity of Fig allowed Docker community to plug into its own Docker code base as separate component called “Docker Compose“.

1. Installing Docker Compose

You are required to follow the steps below:

$ sudo curl -o /usr/local/bin/docker-compose -L "https://github.com/docker/compose/releases/download/1.11.2/docker-compose-$(uname -s)-$(uname -m)"

Set the permissions:

$ sudo chmod +x /usr/local/bin/docker-compose

Now check whether it is installed properly:

$ docker-compose -v

2. Running a Container with Docker Compose

Create a directory called “ubuntu” to download an image from GitHub. This will basically download the latest ubuntu distribution as an image to the local.

$ mkdir ubuntu
$ cd ubuntu

Once you do above, create a configuration file (docker-compose.yml) as an guideline to create an image.

docker-compose-test:
  image: ubuntu

Now execute the following:

$ docker-compose up // As an interactive job
$ docker-compose up -d // As a daemon job

The above will read the docker-compose.yml and pull the relevant images and up the respective container.

Pulling docker-compose-test (ubuntu:latest)...
latest: Pulling from library/ubuntu
e0a742c2abfd: Pull complete
486cb8339a27: Pull complete
dc6f0d824617: Pull complete
4f7a5649a30e: Pull complete
672363445ad2: Pull complete
Digest: sha256:84c334414e2bfdcae99509a6add166bbb4fa4041dc3fa6af08046a66fed3005f
Status: Downloaded newer image for ubuntu:latest
Creating ubuntu_docker-compose-test_1
Attaching to ubuntu_docker-compose-test_1
ubuntu_docker-compose-test_1 exited with code 0

Now execute the following to see whether an ubuntu:latest image is downloaded and container is created.

$ docker images
REPOSITORY                    TAG                 IMAGE ID            CREATED             SIZE
ubuntu                        latest              14f60031763d        4 days ago          120 MB
$ docker ps -a
CONTAINER ID        IMAGE                         COMMAND                  CREATED             STATUS                     PORTS                    NAMES
5705871fe7ed        ubuntu                        "/bin/bash"              2 minutes ago       Exited (0) 2 minutes ago                            ubuntu_docker-compose-test_1

References

1. How to install Docker Compose on Ubuntu 16.04 LTS

2. How to install and use Docker Compose on Ubuntu 14.04 LTS

3. How To Configure a Continuous Integration Testing Environment with Docker and Docker Compose on Ubuntu 16.04

4. How To Install WordPress and PhpMyAdmin with Docker Compose on Ubuntu 14.04

4. Docker Compose (Official Web URL)

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Docker on Ubuntu 16.04 LTS – [Part 03] Docker Networking

In my previous post on Docker images, we were able to run certain containers in the foreground. To recall it, here it is:

$ docker run -d -p 80 --name static_web crishantha/static_web  /usr/sbin/apache2ctl -D FOREGROUND

However, this container is not visible to outside since it runs in a private network. If you are to run this allowing to public means, you are required to bind the 80 port to some other port, which runs the container itself. For example, if we map the same port of 80 to the container, we should execute the above command as follows:

$ docker run -d -p 80:80 --name static-web crishantha/static-web  /usr/sbin/apache2ctl -D FOREGROUND

Once you do above, you are able to run the container from the outside IP. Hope this is clear now!

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Docker on Ubuntu 16.04 LTS – [Part 02] – Images

In my previous article, I stopped at the Docker Container management. In this article basically I will be touching the Docker Images.

A typical traditional Linux system to run, it basically needs two file systems:

  1. boot file system (bootfs)
  2. root file system (rootfs)

The bootfs contains the boot loader and the kernel. The user never makes any changes to the boot file system. In fact, soon after the boot process is complete, the entire kernel is in memory, and the boot file system is unmounted to free up the RAM associated with the initrd disk image.

The rootfs includes the typical directory structure we associate with Unix-like operating systems: /dev, /proc, /bin, /etc, /lib, /usr, and /tmp plus all the configuration files, binaries and libraries required to run user applications.

Here the root file system is mounted read-only and then switched to read-write after boot. In Docker, the root file system stays in read-only mode, and Docker takes advantage of a union mount to add more read-only filesystems onto the root file system and appear as only one file system. This gives the complete control of the all the file systems, which are added to the Docker container. Finally when a container is created/ launched, Docker will mount a read-write file system on top of all the other file system image layers. All the changes made to underneath images are basically stored in this read-write layer. However, the original copy is retained in underneath layers without and changes written to them. This read-write layer + other layers underneath  + base layer basically form a Docker container. (See the image below)

In Part 01 of this article, we created a container with an ubuntu image. You can see all the available images by,

$ sudo docker images

REPOSITORY TAG    IMAGE ID     CREATED     VIRTUAL SIZE
ubuntu     latest 07f8e8c5e660 4 weeks ago 188.3 MB

Seems now you have the “latest” ubuntu image with you. If you want a specific version image then you need to specify it as a TAG. i.e. ubuntu:12.04. So lets try that now.

$ sudo docker run -t -i --name new_container ubuntu:12.04 /bin/bash

Now, check the image status

$ sudo docker images

REPOSITORY TAG    IMAGE ID     CREATED     VIRTUAL SIZE
ubuntu     latest 07f8e8c5e660 4 weeks ago 188.3 MB
ubuntu     12.04  ac6b0eaa3203 4 weeks ago 132.5 MB

Further, if you want to delete one of the created images you can use,

$ sudo docker rmi <image-id>

While interacting with multiple images, there can be many unnamed and unwanted (dangling) images are being created. These can take a lot of space in the disk. Hence periodically it is required to purge  them from the system. Use the following to do the trick:

$ docker rmi $(docker images -q -f dangling=true)

Up to now, we used Docker run command to create containers. While creating it downloads the given image from the Docker Hub. This downloading to the local basically takes some time. If you want to save this time when you are creating the container, you can have the alternate route by first pulling the required template from the Docker Hub and then creating the container using the downloaded image. So here are the steps

// Pulling the image from Docker Hub
$ sudo docker pull fedora

// Creating a Docker Container using the pulled image
$ sudo docker run -i -t fedora /bin/bash

Now if you see, you will have 3 containers.

$ sudo docker ps -a

86476cec9907 fedora:latest ---
4d8b96d1f8b1 ubuntu:12.04  ---
c607547adce2 ubuntu:latest ---
Building your own Docker Images

There are two ways to do this.

Method (1). Via docker commit command

Method (2). Via docker build command with a Dockerfile (This is the recommended method)

To test method (1), first create a container using an already pulled image and then do some alteration to the image and then execute docker commit.

// Creating a Docker Container using an image
$ sudo docker run -i -t ubuntu:14.04 /bin/bash

// Alter the image
$ apt-get -yqq update
$ apt-get -y install apache2

// Committing the changes to the image
// Here, crishantha is the account created
// in the Docker Hub repository
// you may use Docker Hub or any other Docker repo
// 9b48a2b8850f is the Container ID of the contatiner

$ sudo docker commit 9b48a2b8850f crishantha/apache2

// List the Docker images
// Here the Docker altered image ID is shown
$ sudo docker images crishantha/apache2
crishantha/apache2 latest 0a33454e78e4 ....

To test method (2), you may create a Dockerfile at a given directory and specify the required changes needed for the image. For example, the Dockerfile can have the following lines, for an Ubuntu 14.04 image. FROM basically pulls the ubuntu 14.04 image and then RUN commands basically executes and add more layers to the image. EXPOSE will basically expose port 80 from the container.

Before executing the Dockerfile, it is good to create a new directory and create the DockerFile within that directory. Here the directory is called static_web.

FROM ubuntu:14.04
RUN apt-get update
RUN apt-get install -y apache2
EXPOSE 80

Once this is done, you can execute the Dockerfile by,

$ sudo docker build -t="crishantha/static_web" .

If all successful, it will return a image ID and further you can see it using docker images crishantha/static_web

Checking the Docker Image History

You can further check the history of the image by executing docker history <image Name/ image ID>

$ sudo docker history crishantha/static_web

Now you can execute the container by,

$ sudo docker run -d -p 80 --name static_web crishantha/static_web  /usr/sbin/apache2ctl -D FOREGROUND

The above will run as a detached process and you would see this by executing docker ps and you would see it running in the background as a Docker process.

If you use Nginx instead of Apache2 as the web server, you may add nginx -g “daemon off;” to the command. The daemon off; directive tells Nginx to stay in the foreground. For containers this is useful as best practice is for one container = one process. One server (container) has only one service.

Pushing Docker Images

Once an image is created we can always push it a Docker repository. If you are registered with Docker Hub, it is quite easy to push your image to it. Since it is a public repository, then if anyone interested can just pull it to his/her own Docker repository.

// If you have not already not logged in,
// Here the username is the one you registered
// with Docker Hub
$ sudo docker login
Username: crishantha
Password: xxxxxxxxxx

// If login is successful
$ sudo docker push crishantha/static_web

If all successful, you may see it is available in the Docker Hub.

Pulling Docker Images

Once it is push to Docker Hub, you may pull to to any other instance which runs Docker.

$ sudo docker pull crishantha/static_web
Automated Builds in Docker Hub Repositories

In addition to push our images from our set ups to Docker Hub, it allow us to automate Docker image builds within Docker Hub by connecting to external repositories. (private or public)

You can test this out by connecting your GitHub repository or Bitbucket repositories to Docker Hub. (Use the Add Repository –> Automated Build option in the Docker Hub to follow this process)

However, the Docker Hub automated builds should have a Dockerfile attached to it in the specific build folder. The build will go through based on the Dockerfile build that you specify here. Once the build is completed you can see the build log as well.

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