Managing Multiple environments in a Hybrid Cloud

With the shift from traditional Client Server Application Software to Cloud Aware Application many Software Engineers have found themselves dusting off old System Administration Books from college. With multiple services running on multiple machine or containers software engineers have to be able to manage their applications across more and more complex environments. As I have been talking to some of my customers I have found common pain points in managing these complex applications: 

• Consistency between environments
• Single point of failure services
• Differing environment requirements  (Not all environments are created equal)
• Managing multiple environments across multiple clouds

All of these factors and many more can lead to time wasted, applications being released into production before their time, or worst of all unhappy software engineers.

DevOps to the rescue?

Wouldn't it be nice if the software engineer just worried about their application and its code, instead of all of the environments that it has to run on? In some places that is exactly what happens. Developers develop on their local laptops or in a development cloud and then check in their code and it moves to production. DevOps cleans up any problems with applications using single instance bottle-necked services, out of sync versions of centralized services, or adding load balancing services to the front end or back end of the application. The App developers have no clue what mess they have caused with their code changes, or a new version of service that they are using. Somehow we need to make sure that the application developer is still connected to the application architecture but disconnected  from the complexity of managing multiple environments.

Single Definition Multiple Environments

Working on my Local machine

One approach that I have been looking at is having the ability to define my application as a set of service templates. In this simple example I have a simple Node JS application that uses Redis and MongoDB. If I use a yaml format. It might look something like this.

MyApp:     
  Services:  
    web: NodeJS  
      ports: 80  
      links: mqueue, database  
    mqueue: Redis  
      ports: 6789  
    database: MongoDB  
      ports: 25678, 31502  

So with this definition I would like to deploy my application on my local box, using Virtual Box. I put this yaml file in my home directory of the application. This should be very familiar to those of you that have used docker-compose. Now I should be able to launch my application on my local machine using a command similar to docker-compose.

$ c3 up

After a couple of minutes my multi-service application is running on my local laptop.

I can change the application code and even make changes to the services that I need to work with.

Working in a Development Cloud

Now that I have it running on my laptop I want to make sure that I can run it in a cloud. Most organizations work with development clouds. Typically development clouds are not as big as production and test clouds but give the developer a good place to try out new code and debug problems found in production and test environments. Ideally the developer should use the same application definition and just point to another environment to launch the application.

$ c3 up --env=Dev

This launches the same application in the development environment. Which could be a OpenStack, VMWare or Kubernetes based SDI solution. The developer really does not care about how the infrastructure gets provisioned, just that it is done quickly and reliably. On quick inspection we see a slight difference in the services that are running in the development cloud. There is another instance of the NodeJS service running. This comes from the service definition of the NodeJS service. The NodeJS service is defined to have multiple instance in the development cloud and only one instance in the local environment.

NodeJS.yml - Service Definition

1. NodeJS:  
2.   Local:  
3.    web:  
4.       image: node-3.0.2  
5.       port: 1337  
6.   Dev:  
7.     web:  
8.      image: node-3.0.2  
9.      port: 1337  
10.     worker:  
11.      image: node-3.0.2  
12.      port:1338  
13.      cardinality: 3  
14.   Test: …  
15.   Prod: …  

This definition is produced by the service and stack developer not the application developer. So the service can be reused by several developers and can be defined for different environments (Local, Dev, Test, & Production). This ensures that services are defined for the different requirements of the environments. For example Production NodeJS might have a NGNX load balancer on the front end of it for serving up NodeJS web services for each user logged in. The key is that this is defined for the Service

that is reused. This increases re-usability and quality at the same time.

Working in the Test Cloud

Now that I have tried my application in the development cloud. It is time to run it through a series of tests before it gets pushed to production. This is just as easy for the developer as working in the development cloud.

$ c3 up --env=Test

$ c3 run --env=Test --exec runTestSuites

We launched the environment and then run the test suites in that environment. When the environment launches you can see additional instances of the same services we have seen before in the development cloud. Additionally, there is a new service running in the environment. The Perf Monitor Service is also running. It is monitoring the performance of the services while the tests are running. Where did the definition of this service come from? It came from the application stack definition. This definition just like the service definition can show that the application can have a different service landscape for each environment. But the software developer still sees them as the same. That is to say, code should not change based on the environment that is running the application. This decouples the application from the environment and frees up the software developer to focus on code and not environments.

What about Production 

The ultimate goal of course is to get the application into production. Some organizations, the smart ones, don't let developers publish directly into production without some gates to pass thru. So instead of just calling "c3 up --env=Prod" we have a publish mechanism that versions the application, its configurations and supporting services.

$ c3 publish --version=1.0.2

In this case the application is published and tagged with version 1.0.2. Once the application is published, it will then launch the environment if it is not currently running. If it is running then it will "upgrade the service" to the new version. The upgrade process will be covered in another blog. Needless to say it allows for rolling updates with minimum or no downtime. As you can see additional services have been added and some taken away from the test environment.

Happy "Coder" Happy Company

The software engineer in this story focuses on writing software not on the environment. Services are being reused from application to application. Environment requirements are being met with service and application definitions. Stack and service developers are focusing on writing services for reuse instead of fixing application developers code. Now your company can run fast and deploy quality products into production,

Check out more detailed architecture and use cases on github at https://github.com/CAADE/C3/wiki.

You can see the video of this blog here

DWP

Building Microservices with SailsJS and NodeJS

I have been developing applications with uServices for sometime. Each time I wrote a new application I could not figure out where to put the uService Definitions. They tended to be spread all over my source tree. Since I was writing my application using sailsjs I wanted to follow the convention over configurability paradigm that they espouse in sails.

Here are some of the things that I tried.

• api/workers directory - Using the sails_hook_publisher & sails_hook_subscriber
• api/jobs directory - similar to the workers pattern but using grunt to run processes.
• deploy directory - Using the micro npm module.

Workers

This method uses the sails_hook_publisher & sails_hook_subscriber plugins to give each instance the ability to subscribe to jobs that are are requested from another service. It assumes that you are using redis as the message queue. And it does not handle the management of starting/stopping or replicating services. It is a good solution but it had the overhead of a full sails application with each worker. It also tied the logical to the deployment models too tightly for me.

Jobs

Very similar to the publish/subscribe worker paradigm but I wanted a light weight mechanism for spinning up small services without all of the overhead of the sails stack. So I basically just fired up small node js scripts that I stored in the jobs directory. Problems with this is lack of flexibility of the micro-service architecture and coupling with the application code.

Deploy

Using the micro npm package to create simple micro services that can handle a HTTP request. I created simple micro services that performed specific tasks for the application. Creating the micro services was actually very simple thanks to the micro package. But Deploying multiple micro services can be hard manage. So I looked to docker and containers to help with this.

I had to come up with a strategy to define/code my microservices, how they would be managed and deployed. I had to remember the key software engineering principles of Cohesion, Decoupling and Reuse in my architecture. So the first thing I worked on was decoupling the microservice deployment from the microservice source code itself.

This gave me the flexibility to change my deployment architecture from source code itself. To do this I looked at defining my deployment architecture using docker both DockerFile and docker compose file formations. To define a microservice I had to do the following.

• create a package.json file with all of the packages needed to run my microservice
• create a Dockerfile to build the image of my microservice
• add the microservice to a docker-compose file for the application.

package.json

The package.json file contains the npm packages that my microservice depends on as well as an scripts that are needed to manage my microservice including a build and deploy script. Note that when I build my microservice image I tag it with a local registry service using "localhost:5000/appName/userviceName" where appName is the name of the application and userviceName is the name of the microservice that I am creating. This is just an example of a naming convention that I like to use. If I was creating a microservice that I was going to use over and over again I would use a different name. The deploy target pushes the image into the local registry so I can use the image in the docker swarm that I am running.

 {
  "main": "index.js",
  "scripts": {
    "start": "micro",
    "build": "docker build . -t localhost:5000/appName/userviceName",
    "deploy": "docker push localhost:5000/appName/userviceName"
  },
  "dependencies": {
    "micro": "latest",
    "node-fetch": "latest"
  }
} 

Dockerfile

The dockerfile in this case is very simple. I am writing all of my micro-services in node so I start with the base image. Next I simply copy the package.json file to an application directory and I copy any of the source code into the application directory. Then I call "npm install" this will install all of the packaging that are required by my micro-service for the image. Then the last statement launchs the microservice by calling "npm start".

FROM  node:latest
RUN mkdir -p /usr/src/app
WORKDIR /usr/src/app
COPY package.json /usr/src/app/
RUN npm install
COPY . /usr/src/app
EXPOSE 3000
CMD npm start

docker-compose.yaml

The docker-compose.yaml file contains the services and their deployment configurations for the application. For my application I have a simple web server that is the main microservice for my application. It is a sailsjs application. I try to always name my web interface micro-service "web". It is easy for me to find them later. Again in the file below I have appName as the name of the application. Also you can see the micro-service definition is runing 5 replicas and the image is the same one as defined in the Dockerfile above.

version: '3'
services:
  mongo:
    image: mongo
    expose:
         - 27017
    ports:
         - "27017:27017"
  appName:
    image: localhost:5000/appName/web
    expose:
      - 1337
    ports:
      - "1337:1337"
  userviceName:
    image: localhost:5000/appName/userviceName
    deploy:
            mode: replicated
            replicas: 5

Bouquet Generator implementation

I have created a sails generator to generate the directory heiarchy as well as simple micro-services that you can use as a starting point for your own micro-service application check out the documernation at https://github.com/madajaju/bouquet/tree/master/sails-generate-bouquet-uservice. Or you can install it by installing the node.

# npm install sails-generate-bouquet-uservice --save.

I hope this helps you with your journey to building your own sails application using micro-services.
For more information on the Bouquet sails generators check out my previous blog post at https://darrenpulsipher.blogspot.com/2017/05/resurrecting-bouquet_3.html.

DWP

Argument for Hybrid Cloud with Common Cloud Core

Current Cloud environment

Over the last five years there has been a fundamental shift in the IT environment. The continual growth of Public Cloud and the emergence of Private cloud options has left many CIOs and IT departments playing catchup. In the competitive digital economy of today, many development teams need to move faster than their IT departments can deliver, which has led many enterprise developers to turn to public clouds like AWS, GCE, and Azure to spin up new infrastructure resources on demand - no more waiting around for several levels of technical and business approvals, physical space in the data center, and vendor supply problems. Now, in a matter of minutes, a development team can have all of the infrastructure they need for their new project. While the consumerization of IT through the public cloud has helped developers move fast rather than wait for their IT departments to give them the resources they need, this “bring your own” server trend has resulted in the emergence of shadow IT – infrastructure not supported or known to the IT department. Shadow IT then raises its own concerns for the organization – namely security, cost management, data silos, and compliance concerns.

Before the Public Cloud, IT managers could easily walk around the cubes and count the number of local servers running under employees desks. With physical machines no longer visible to the IT departments, identifying teams and their project’s infrastructures is challenging. Many public cloud have given organizations the ability to consolidate accounting from all of the accounts for specific domains, but visibility into what is running and who is working on the infrastructure is still somewhat of a “snipe hunt”. Many times these rogue projects become visible when projects are productized and need to be put into a company’s on premises infrastructure. Security, privacy and regulatory policies can make productization of projects near impossible. Especially if developers have tightly coupled their applications to Cloud infrastructure.

Forward thinking IT departments are doing their best to capture shadow IT by working with Public Clouds and ISVs to create   company portals to the Cloud. Putting a pass-thru portal in place is a good start to capturing projects using infrastructure, but many organizations find that just a portal is leaving development teams wanting more. Over the last couple of years, I have been working with many of these organizations to identify use cases, architectures, and technologies to help develop these augmented portals which we called “Common Cloud Core (C3). Typically, three major technologies are integrated together to build these C3s. Cloud Management Platforms (CMP), Automation Frameworks, and Platform as a Service frameworks (PaaS).

Cloud Management Platform (CMP) 

Cloud Management Platforms primary responsibility is managing multiple heterogeneous cloud both
public and private. Giving end users the ability to manage multiple clouds and their infrastructure from one common pane of glass.  CMPs are typically opinionated with Cloud Administrators in mind. Although the Cloud Management Platform tools primary focus is managing multiple cloud, many tools have added features from the PAAS and Automation Frameworks or at minimum have a plugin architecture to support it.

Use Cases covered

• Managing Public Clouds
• Managing Private Clouds
• Managing Cloud identities
• Managing Infrastructure across multiple clouds.

Automation Frameworks 

Automation Frameworks primary responsibility is to
automate the deployment, management and upgrading software stacks on infrastructure. Automation Frameworks came out of the DevOps community and are typically focused on repeatable processes. Many of these tools include scripting languages that allow DevOps engineers to repeatability manage and configure software and services. Many DevOps teams are well versed in these tools.

Use Cases Covered

• Deploy Software on Infrastructure
• Manage Software on Infrastructure
• Upgrade Software and Services

Platform as a Service (PAAS)

Platform as a Service is primarily responsible for giving a single

portal to re-use platforms and deploy them onto Infrastructure. PaaS tools are typically highly opinionated with the Developer in mind. Which can lead to inflexible infrastructure configurations. Many of these tools have a web portal that give developers the ability to select services and deploy them in the infrastructure.

Use Cases Covered

• Deploy/Manage Services/Applications
• Manage Service Catalog
• Develop new Services/Applications

Convergence creates true Hybrid Clouds on C3)

Because not one tool set has all of the use cases they need to manage clouds, applications,
infrastructure and services, teams spend several “man years” installing, configuring, and integrating these three tool sets together. This has led to an emergence in technologies that integrate these tools including new product offerings, and new features in currently available products.
Many CMP products are including PaaS and Automation Frameworks into their solutions. PaaS tools are now managing multiple clouds. Automation Frameworks are beginning to offer web portals and connectivity to multiple clouds. Many of the tools are moving to the Unified Hybrid Cloud vision. When looking at which tool(s) to use it is important to remember the roots of the tool.

Deploying a solution

The Common Cloud Core ecosystem is still fairly new and still requires some heavy integrations between the tools. There are some tools that are starting to deliver complete out of the box solutions, but still with their particular vision of the world. Because the ecosystem is nascent there are many players and choices. Time will tell who will win this space. For now it will interesting to watch the tools converge and consolidate while the features mature.

DWP