Teaching Alexa to deploy applications in any cloud

Alexa, deploy a webserver in AWS and a database in Azure!

Recently I presented a session at Codemotion Milan, with my colleague Stefano Gioia.

We demonstrated how the API exposed by the Cisco CloudCenter Suite can be easily integrated from within an Alexa skill.

Of course, this is not something you would do in the real life in a production environment 🙂

But it’s an easy and funny way to show how easy the integration is, and we found it attractive for our customers and partners.

Instead of Alexa you could use any client, like a custom script from the command line, a workflow engine, a web portal or a ITSM system like ServiceNow to achieve the same result.

Any program that can do a REST call can drive CCS (CloudCenter Suite) externally to orchestrate the lifecycle of a software deployment.

In case you use Alexa, you will code the REST client logic in the serverless implementation of the “skill” that is executed as a Lambda function. You can use different languages to create the skills: we chose node.js for the demo.

We decided to show some basic CCS features like deploying any kind of software in any cloud, or measuring the cost of all the services we are consuming in all our clouds (for running VM and containers, for consuming cloud services like load balancers or network bandwidth, for running serverless functions. etc.). Of course there is much more in the product, but we wanted to keep the demo light and funny.

The 3 modules of the Cisco CloudCenter Suite

Everything you can do in the CloudCenter web portal can also be done through its REST API, and the CCS documentation shows examples you can easily reuse and adapt.

These are the API targets, for the different modules, that we used in the implementation of the skill:

Suite Admin API

/suite-idm/

E.g.: https://na.cloudcenter.cisco.com/suite-idm/api/v1/tenants

Workload Manager API

/cloudcenter-ccm-backend/api/v2/apps

E.g.: https://na.cloudcenter.cisco.com/cloudcenter-ccm-backend/api/v2/apps

Action Orchestrator API

/be-console/

E.g.: https://na.cloudcenter.cisco.com/be-console/api/v1/workflow

Cost Optimizer API

cloudcenter-shared-api

E.g.: https://na.cloudcenter.cisco.com/cloudcenter-shared-api/api/v1/costByProvider?cloudGroupId’

Next picture shows the high level process that allows a user to get something done by Alexa, just by speaking to a Echo device or to the Alexa mobile application.

The speech recognition system translates the user’s voice to text, then the “intent” of the user is matched to one of the functions available in the skill. Skills and their intent are executed based on patterns and keywords that the system is able to recognize in the natural language, thanks to machine learning algorithms.

Recognizing an intent triggers your custom code, that is generally a Lambda function (the Amazon developer console makes it easy to write the code and to host it in the Lambda service, providing also reusable examples). The outcome is rendered as audio or, depending on the device, also as a video.

In our specific demo, we put the client code for the Cisco CloudCenter API in the serverless implementation of the intent.
These are the commands that we can give Alexa:

• give me the list of existing tenants
• list all configured target clouds
• deploy a database or a web server in a cloud
• show current cost of all cloud services

Here you can see a sample of the capabilities of Alexa when it calls the Cisco CCS API:

Building a new Alexa custom Skill: as the skill developer, you have to:

1. Define the requests the skill can handle
2. Define the name Alexa uses to identify your skill, called the invocation name
3. Define the utterances and input variables, called slots
4. Write the code to fulfill the request
5. Test it from the developer console or from your Alexa device

The documentation at the Amazon Developer console contains excellent tutorials to build Alexa skills.
You can learn easily to create a Hello World skill, then you are ready to incorporate the client code to call the CloudCenter Suite API.
Stefano has published his examples in github here, feel free to test it yourself.

This demo demonstrates that it's easy to build a client to drive the API exposed by CCS.
And it helps positioning the CloudCenter Suite as a mediation layer in your architecture, to orchestrate the lifecycle management and to define a governance model including cloud cost control.

DevOps with CloudCenter and Kubernetes in a multicloud environment

A short description of what is DevOps and how it helps companies to compete in their business with a faster innovation, followed by a demonstration of how the Cisco multicloud portfolio helps in the adoption of DevOps practices [see also this post for more detail].

If your time for reading is limited, here is the structure of the post: you can jump to the paragraphs you are interested in.

(The business view starts here)
The need for digital innovation.
  New services, better quality
  Frequent releases
DevOps is not a technology or a product.
  Cultural change and collaboration (break silos in the organization)
        Small teams responsible for a service’s lifecycle end to end
DevOps principles.
  Feedback loop
  CI/CD – Continuous Integration and Continuous Deployment

(The technical view starts here)
Cisco Multicloud approach.
Cisco CloudCenter Suite (CCS)
Cisco Container Platform (CCP)
Our lab
Application
Infrastructure
Demo flow
Implementation
Conclusions
DevOps makes it faster and easier
Cultural change is needed (incentives)
Cisco offers an effective toolset to help the adoption of DevOps practices

The need for digital innovation.

Whatever is your business, your customers expect more and more services, greater efficiency and value added by innovation.

Providing new business services (generally supported by software applications) to customers and anticipating your competitors’ moves attracts new customers and retains the existing ones. 

Often the lines of business are not satisfied with the support they receive from the corporate IT in terms of flexibility and speed to start a new project, especially if new technologies or skills are required (e.g. cloud native applications).

A better perceived quality of IT depends also on the frequency of the release of fixes for broken services and on the process to avoid that bugs reach the production environment, being intercepted in good functional and reliability tests.

Frequent releases and the quality of the code can benefit a lot from automation in all the phases of a software project, though the end to end automation is not absolutely necessary: it is just much better. The fundamental pillars are a good organization of the work and processes that ensure a coverage of every need (no gaps in the responsibility, no grey area in communication among different departments, shared objectives instead of finger pointing).

Next picture shows the evolution of methodologies and the impact on the value perceived by the business. The small star represents the instant when business value is realized by a release of the application in production.
With the traditional waterfall projects, it happens only at the end of the project (by the way, with a lot of uncertainty due to delays and unexpected troubles during the development and the test phases).
The agile methodology reduces the risk, repeating shorter cycles of design, coding and testing that can address any surprise and correct the course of the project sooner. But the deployment in production still happens at the very end of the project.
The innovation allowed by Continuous Integration and Continuous Deployment brings the application in production at every cycle (new releases or bug fixing) ensuring optimal quality and a deterministic outcome: the business will appreciate a benefit in terms of time to market for their initiatives.

Picture 1 - CI/CD offers more business value

DevOps is not a technology or a product.

DevOps means collaboration between Developers and Operations.

The work of who is responsible for design and implementation of the code does not finish when a new build of the application is released. Developers should also collaborate in testing the system, releasing it in production, operating and measuring its KPI.

The Operation team should not just execute a defined process to maintain the system but should collaborate since the design phase of the application and, most importantly, provide a constructive feedback from the production environment that helps improving and extending the application in next development cycles.

The collaboration and the feedback loop are foundational principles in DevOps, as described in next paragraph. [See The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations]

A cultural change. 

A cultural change (breaking silos in the organization) should be promoted, with incentives and gradual adoption of practices that will improve with time: the entire organization and the individuals have to digest a new way of working, openly analyze the outcome, contribute to the progress with personal feedback and suggestions. 

Everybody should feel that they have a common goal and they are collaborating to everyone’s success.

A great book describing this cultural change is the Phoenix Project.

Small teams responsible for a service’s lifecycle end to end.

DevOps practices suggest that the entire lifecycle of a service is managed by a single team: from the inception phase and the requirements analysis, to the implementation, test, release and operations. They can be more efficient – a provide a better quality – if they know everything about the service and they can react to any problem quickly, as well as evolving it based on new requirements.

The team should include representatives from different departments (lines of business, IT Architecture, Operations…) that bring their skill and experience, so a new organizational model can be required in your company: maybe a dotted line reporting structure with functional responsibilities.

It is not necessary to build a team for each service: some services can be grouped in one team, especially if they belong to the same business area or if they are the building blocks for a composite application (in a microservices architecture).

DevOps principles.

Gene Kim defines the principles that all of the DevOps patterns can be derived from (the Three Ways) in the books “DevOps Handbook” and “The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win.” He asserts that the Three Ways describe the values and philosophies that frame the processes, procedures, practices of DevOps, as well as the prescriptive steps.

The First Way – Systems Thinking

•  Understand the entire flow of work

•  Seek to increase the flow of work

•  Stop problems early and often – Don’t let them flow downstream

•  Keep everyone thinking globally

•  Deeply understand your systems

First Way Goals

•  One source of truth – Code, environment and configuration in one place

•  Consistent release process – Automation is essential (one click)

•  Decrease cycle times, Faster release cadence

The Second Way – Feedback Loops

•  Understand and respond to the needs of all customers (internal and external)

•  Shorten and amplify all feedback loops

•  With feedback comes quality

Second Way Goals

•  Defects and performance issues fixed faster

•  Ops and InfoSec user stories appear as part of the application

•  Everyone is communicating better

•  More work getting done

The Third Way – Synergy

•  Consistent process and effective feedback result in agility

•  Now use that agility to experiment

•  You only learn from failure – So fail often, but recover quickly

Third Way Goals

•  Ability to anticipate, even define new business needs through visibility in the systems

•  Ability to test and optimize new business opportunities in the system while managing risk

•  Joy

Now that you have got an idea of what is DevOps, let’s have a look at a solution from Cisco that could make it easier to adopt DevOps practices. Remember that DevOps cannot be bought: it is the set of good practices that you define and refine based on continuous improvement based on direct experience. Automation is only a part of the story.

Cisco Multicloud approach.

Cisco knows that many customers are using at least one private or public cloud, but most of them use at least two: that implies a need for consistent governance, security, networking, analytics and automation that apply to every environment.

The multicloud portfolio includes products, and reference architectures to make the adoption simpler, that span all the technologies mentioned above.

This post explains how we have built a demo using products in the automation bucket to support a DevOps use case (i.e. Continuous Integration and Continuous Deployment, aka CI/CD).

The two products are the Cisco CloudCenter Suite (CCS) and the Cisco Container Platform (CCP), briefly described in the following paragraphs before we go to the demo.

Cisco CloudCenter Suite

A solution to help the IT organization to sustain the pressure from developers and lines of business to deploy and operate a large number of applications and middleware platforms, made more complex by the availability of different possible targets (private and public clouds for running VM and containers).

Picture 2 - CloudCenter addresses the many-to-many complexity

The CloudCenter Suite is a single tool to automate the deployments and broker resources from any cloud. It helps to enforce a single governance model including cost control, approval processes, security policies and consistent architecture across different clouds.

You don’t have to learn and use separate tools from the cloud providers, neither to replicate the automation blueprints using the native automation technologies in each cloud (e.g. Cloud Formation, Heat, Powershell): you only create a single model and CloudCenter translates it into call to the specific API exposed by each private and public cloud and Kubernetes clusters.

Picture 3 - CloudCenter translates a single blueprint to API calls for all clouds

Everything you do in CloudCenter can be done through its API, that makes it easy to orchestrate it externally (e.g. from Jenkins, through a plugin that Cisco ships so that you can insert multicloud deployments in your CI/CD pipeline).

The current version of the CloudCenter Suite also includes additional modules like the Cost Optimizer and the Action Orchestrator: a useful enhancement to create a governance model and make operations easy in a heterogeneous multi-cloud environment.

Cisco Container Platform

Another software product form Cisco, that you can see as a tool for Operations to create and manage enterprise grade Kubernetes clusters.

It creates, fully configures and manages (upgrades, scales, monitors) Kubernetes clusters on-premises and in the public cloud for you.

It takes care of all the complexity of the integration with networking (options offered out of the box are Calico, Contiv and Cisco ACI), storage, security (SSO and RBAC are added to Kubernetes) as well as centralized monitoring and logging while shipping 100% open source binaries from the upstream repositories.

Our lab

We have built a simple application based on a microservices architecture, as shown by the picture. 

Picture 4 - the microservices application built for the demo

The source code of the 5 components is stored in a github repository, where new versions of the application are committed (saved) by developers. At each commit, the Jenkins orchestrator gets the source code and compiles it, building the container images ready to deploy the application.

The images are saved in a shared container registry (Harbor, see next picture) where Cisco CloudCenter will be able to retrieve them when asked by Jenkins to deploy the application. Based on input parameters provided by Jenkins, CloudCenter will target the deployment to the most appropriate environment for the current phase of the project.

In our demo lab, the environments are “integration test”, “performance test” and “production”.

They correspond to three different Kubernetes clusters that have been created in the private cloud (the first two) and in the public cloud (for the production environment).

Each environment has different policies set, that will be inherited by every application that is deployed there: for security, networking, autoscaling, etc.

The 3 Kubernetes clusters mentioned above have been generated by the Cisco Container Platform (though we could have created them manually in each cloud). The value in using CCP consists in consistent operations, speed and easiness: in few minutes we created 3 production-ready clusters, fully integrated with networking, storage, security, monitoring and logging without even touching the K8s installer or the underlying infrastructure.

The 2 clusters named “integration test” and “performance test” were created automatically inside VM in a local vmware environment, while the cluster named “production” was created in the Amazon cloud (CCP uses the API exposed by the Amazon EKS service to do everything automatically, including the integration with the AWS IAM for security).

The automated deployments will repeat, in the three environments, in a sequence that alternates them with the necessary tests and ensures the quality of the release. Though in the real world you might want to run more complex testing activities, this is a meaningful example of the efficiency you can achieve thanks to full automation of the process.

The pipeline can still be extended by adding additional tests like quality code inspection and more.

Picture 5 - the CI/CD cycle

Demo flow

Next picture is a sequence diagram showing all the actions that we have automated.

We used a color code to represent the phases that are commonly referred to as Continuous Integration (the green part) and Continuous Deployment (the orange part).

CCC stands for Cisco CloudCenter, where K8s dev, test and prod represent the 3 Kubernetes clusters mentioned above.

The entire process is completely automated and brings a new version of the application to the production deployment without any human intervention.

This complete automation is often referred to as Continuous Deployment and, though very useful and adopted by big players like Facebook (their pipeline is more complex than our simplified demo) is not very common among the customers I generally meet.

Those that adopted DevOps still prefer to have some human checks in between the activities, so that they feel they have a better control on the process and its quality.

When they have more experience, probably they will be confident enough to delegate every check to the automation tools.

Picture 6 - a sequence diagram showing the automated actions

Implementation

The automation is based on Jenkins, an open source orchestrator that benefits from the availability of hundreds of plugins: it can automate almost every component in your IT ecosystem, including Cisco CloudCenter of course.

In the Jenkins dashboard you can build different projects, like in the picture below. A project is a sequence of steps, using plugins to drive activities in the systems you want to automate (e.g. pull the source code from the repository, compile it, build containers images, trigger a cloud deployment through CloudCenter, etc.).

Picture 7 - Jenkins projects

Projects can call other projects, to make your orchestration modular and reusable. In the picture above, the project TheWall (that is the name of our demo application) calls the other 5 projects in a sequence, checking that the outcome is positive before calling next project.

So, we are able to automate the deployments in the 3 Kubernetes clusters and to run the functional test and the performance test of the application using an external tool (we used another open source product called Apache Jmeter). 

The functional test is a sequence of user transactions, executed by the test tool using a pool of user identities and a pool of input data, where assertions about the expected result are validated automatically. If the page generated by the application differs from the expected result, an error is logged, and the test can be considered failed. So, the functional test ensures that the application behaves as expected from a functional standpoint (and you can avoid a manual test for user acceptance).

The performance test, executed by the same tool, stresses the application and the infrastructure from a performance standpoint. A large number of concurrent users are simulated by the tool, invoking a sequence of user transactions with random wait time, reproducing a situation similar to the workload in a production environment. Response times are tracked and so are eventual errors, allowing the tool to declare that the test is successful or not.

Based on the outcome produced by Jmeter, the Jenkins orchestrator will continue with the Continuous Deployment pipeline or abort it, notifying the developers that something went wrong and a correction is required.

In this case, the CI/CD cycle will restart from the beginning: source code modified and committed, application built and deployed to the first environment, test executed, application promoted to next environment and tested… until the pipeline is completely executed without any warning or error and the application is released automatically in production.

Next picture shows the execution of the Jenkins pipeline for three different builds of the application. The most recent execution failed because the modification of the source code introduced an error that blocked the build. The other two executions succeeded, as demonstrated by the green color of every step in the pipeline.

Picture 8 - Jenkins pipeline

Jenkins logs all the activities, so that you can check what’s happened during the automated process.

Next picture shows the output of the sub-project named TheWall_Deploy_Test, that is the 7th stage in the pipeline in previous picture.

It uses the API exposed by CloudCenter to deploy the application “TheWall” to a test environment running Kubernetes, that is robust enough to sustain the workload of the performance test (while the functional test can be executed also in a smaller cluster with less computing power).

Picture 9 - output from the Jenkins CI/CD pipeline

You don’t have to code the API calls, because CloudCenter ships a plugin for Jenkins that integrates into its user interface graphically. But if you prefer, Jenkins can run scripts and commands from the CLI for you.

Conclusions

DevOps makes it faster and easier

If you adopt a DevOps methodology you bring agility to an extreme and get a business outcome from the fast release of applications. 

Cultural change is needed (use incentives)

DevOps is not a matter of technology. Your people need to work in a different way: no finger pointing between Developers and Operations, no “it’s not my job”, everybody should commit towards a common goal and enjoy their common achievement.

Initially it will be difficult, you have to teach them little by little. Offer incentives to people that shows a collaborative attitude and a spirit of innovation, let them feel like the heroes in the new adventure and grant that failures will not create any trouble. You learn from your mistakes and there is no magic wand to start directly with a perfect solution.

In addition, also traditional methodologies generate project failures: the difference is that DevOps anticipate problems and you discover them sooner, so the business impact is much smaller.

Cisco offers an effective toolset to help the adoption of DevOps practices

We all agree that DevOps is not a product. But once you start working you will see that automation helps the CI/CD process to be fluent. You can find great opens source (and free) tools – e.g. Jenkins, Jmeter, Ansible – to support your project teams, but if you also adopt Cisco CloudCenter and the Cisco Container Platform your professional life will be much easier.

Credits

The demo lab described in the post has been built with two colleagues and friends, that I want to thank here: Stefano Gioia and Riccardo Tortorici.

References

Cisco CloudCenter Suite – https://www.cisco.com/c/en/us/products/cloud-systems-management/cloudcenter-suite/index.html 

Cisco Container Platform – https://www.cisco.com/c/en/us/products/cloud-systems-management/container-platform/index.html 

Jenkins – https://jenkins.io 

Jmeter – https://jmeter.apache.org 

DevOps – http://lucarelandini.blogspot.com/2015/01/why-devops-definition-and-business.html

Recording of our demo session at Cisco Live Barcelona - https://ciscolive.cisco.com/on-demand-library/?search.event=ciscoliveemea2019&search=2826#/session/1531990063103001kztg 

Lifecycle of an application in CloudCenter with CI/CD

In a previous post we demonstrated how to automate the setup of a Continuous Integration / Continuous Deployment environment.

Now we will demonstrate how to use it: a developer can create an application that will be compiled, then built and deployed into a test environment automatically using this CI/CD toolset. 
Next picture shows the list of operations automated by the CI/CD.

 Application deployment: sequence of automated operations

These are the lifecycle steps that we will demonstrate in this post:
1.    Deploy the PetClinic application (introduced in the previous post) automatically.
2.    Push the java source code to a repository (SVN).
3.    Creating the next release of the application by modifying the java source code and saving it as a new version in the repository.
4.    Watch the Jenkins orchestrator create the new build, save it in the binaries repository (Artifactory) and use CloudCenter to deploy it.

1 - Deploy the PetClinic application automatically. 

We start by deploying the Java application PetClinic, using the Application Profile created in CloudCenter, into our development environment in the lab. The correct behavior of the application is tested by accessing its home page and verifying that it shows correctly in the browser.

 2 - Push the java source code to a repository (SVN). 

We then push the java source code of the PetClinic application into the repository (SVN) that was created in our previous task, committing it as the initial release of the application.

Source code control: committing the java code into the SVN repository 

An automated build of the application and its deployment follow, as explained by the workflow above, thanks to the Jenkins orchestrator and CloudCenter.  If we access the Jenkins GUI (see next picture) through a web browser and we select the project “repo1” we can see that Jenkins is currently creating a new build: look at the progress bar. As soon as the building process is terminated the binaries are copied into the Artifactory repository of binary files and the Jenkins process called “deploy” starts.

Jenkins: following the build process  

If we access the “deploy” job in Jenkins, we can see that a new build of the PetClinics application has been sent to CloudCenter to be deployed. This is made possible by the plugin that integrates Jenkins with Cloud Center.

Jenkins: deployment of the PetClinics application through CloudCenter

Cloud Center: viewing the deployment details of the deployed PetClinic application 

PetClinic: home page of the deployed application

 3 - Creating next release of the application by modifying the java source code and saving it as a new version in the repository. 

Let’s assume now that another developer is working at improving the front end of the application and he is ready to commit a major chunk of code. For the sake of the demonstration we will only change the picture and the text on the homepage but we will show that, as soon as we commit the modifications to SVN, the new application is automatically deployed in the Development environment via Cloud Center (as you already know, the Development environment could be in any on-premises/hosted private or public cloud).

Application lifecycle: creating a new version of the code of PetClinic

We will modify the file petclinic/src/main/webapp/WEB-INF/jsp/welcome.jsp changing the text and the pet image (see next picture). Once we are done we save the new version of the file and commit it (right click, SVN Commit).  After waiting a few minutes for the whole chain of operation to finish, we will find out a new deployment of the application in Cloud Center –> Projects –> Project PetClinic  Now we can navigate the application, in the test environment, to see how the new release looks like: you can see that the puppy picture and the text message have been updated according to the edit done by the developer.

PetClinic: home page of the modified application

Conclusion  

The two use cases shown in this series of posts:
•    creation of a CI/CD environment as a service, and
•    automated Deployment of every new release of an application
demonstrate the power of CloudCenter as an orchestrator in deploying applications across a multicloud environment.

Every stage of the project (dev, test, prod…) can be associated to a different deployment environment, potentially in different clouds, having its own set of configuration, policies and rules. This information is stored in CloudCenter as part of the governance model you build for your IT.

The application will move automatically from one phase of the project to next one, if it passes the specific tests (i.e. integration, functional and performances tests, run by the automation tool) after each deployment.

In future posts we’ll show how to also automate these tests in a CI/CD pipeline. 
We will use open source tools like Apache Jmeter to run functional tests designed together with the application and automated by scripts stored in the same source code repository.
And we will run performance tests with the same tool, of course after CloudCenter has moved the deployment to a target environment that is able to sustain the load we generate.  

Credits 

This post is co-authored with a colleague of mine, Stefano Gioia.

References:

CloudCenter 

Creating a complete CI/CD environment in few minutes

In a previous post we introduced CI/CD as a Service (CD/CDaaS) and talked about how it can transform and increase the efficiency of your DevOps practice, to serve development teams and Line Of Business (LoB) better.

In this post we will show how to effectively create a CI/CDaaS with Cisco CloudCenter, either for an organization’s internal use or to offer it to your customers, in case you’re an IT service provider.

With our CI/CDaaS we are able to:

1 - Automate the creation of a complete environment for a development project, including:

• a source code repository (we chose SVN, but it could be GitLab or any other), 

• an integration server / orchestrator (Jenkins),

• an artifact repository for the builds (e.g. JFrog Artifactory or Nexus, but it could be any solution including a simple web server or an FTP server)

• a number of workstations (one per developer) ready to be used with all the needed tools: Eclipse, database tools, etc.

• a remote desktop access to the workstations, even if the developers don't have access to the network where the project environment is created

2 - Integrate all the above tools end-to-end, creating a complete chain for CI/CD with no human intervention required.

3 - Get every build - generated automatically after any commit in the source code repository - deployed automatically in one of your targets, selected according to the project phase, e.g. development in an on-premises VMware environment, integration test in on-premises OpenStack, and production in AWS public cloud.

4 - Get acceptance tests - required to promote a deployment to the next phase/environment - executed automatically after each deployment in one of the environments.

Everything we describe is implemented using Cisco CloudCenter as the main orchestration engine, in a multicloud context, meaning you can select any private or public cloud as a target for the deployment).

The next picture represents a project leader ordering the deployment of the CI/CD toolset for two distinct projects, possibly in different clouds. 

Creating a complete chain for CI/CD with no human intervention, for two different tenants, with CloudCenter

 

Step 1: Self-service in the CloudCenter catalog

Accessing the self-service catalog in CloudCenter, the user can order the deployment of a single application or a complex set of components, like our CI/CDaaS service (we call these Application Profiles):

Application Profiles in the self-service catalog

As you can see from the image above, we have created 2 Application Profiles for this demo. The use case is having a development team that releases daily builds of a web application (PetClinic), so we have built:

1. A cloud-agnostic Application Profile to deploy PetClinic, that takes the binary files required for the deployment from a common repository (that will be the Artifactory server created by our CI/CD service described below). The name of this Application Profile (that is a service in the CloudCenter catalog) is “Clinic”. You can select one specific version of the application binaries that you want to deploy from the Artifactory repository (by default you use the last build available).
   
   Please note that we will not focus on the way a generic Application Profile is built and deployed, because it’s covered in the CloudCenter documentation, but PetClinic is functional in our example as developers will generate new builds that need to be deployed.

2. A cloud-agnostic Application Profile to deploy the CI/CD toolset including SVN, Jenkins and Artifactory, installed in their own VM. The name of this service in the CloudCenter catalog is “AdvancedDevOpsEnv”; it creates an operating project environment where the “Clinic” application can be deployed automatically at every new commit made by a developer.
   
   This is the implementation of our CI/CDaaS concept.

 

Step 2: Deploying the CI/CD toolset

When you “order” the AdvancedDevOpsEnv service you have to set the name of the new project and some options for the deployment (which cloud target, the amount of resources to be allocated when VM or containers are created, etc.); the next picture shows the order wizard in CloudCenter, where you make these selections.

CloudCenter order wizard: you can choose where to deploy the CI/CD toolset and the size of each VM

You can monitor the progress of the deployment while the job runs (it takes approximately 15 minutes to complete) as you can see in the image below:

Watching the progress in CloudCenter: last deployment state is "Deployed"

Once the deployment is complete, you can see the details of the new VM that has been created by clicking on the server representation on the left (e.g. Jenkins – see next picture) and expanding the list of running nodes on the right.

Please Note:

• The IP address of the VM is exposed by CloudCenter.
• You can access the VM via SSH or RDP directly from the browser (that is very important because connectivity and security are proxied by CloudCenter, so you don't really need any access to the actual network where the VM is deployed).

Accessing the details of the VM and the log of actions executed by the agent

Step 3: verifying the configuration made by CloudCenter

The Jenkins orchestrator is automatically setup with a connection to the SVN source code repository (see the Jenkins job “repo1”, that is the name provided by the user for the repository when he ordered the deployment) and with Cloud Center (see the Jenkins job “deploy”).

The Jenkins orchestrator and the 2 tasks created by CloudCenter

The only manual configuration we need is to set the login and password used by CloudCenter to access the SVN repository (we were not able to automate this configuration): you just need to click on the Jenkins task repo1 (next picture), then click Configure and enter your credentials (in our example, user001/C1sco123). At this point, Jenkins is fully configured and ready to go.

Jenkins: setting credentials to access the SVN repository

The jFrog Artifactory is also ready to receive binaries from Jenkins, at each new build of the application, because CloudCenter sets the required information when configuring Jenkins and Artifactory. Note that the Artifactory repository name (repo1) is the name used for the SVN repository, provided by the user when he ordered the deployment.

The Artifactory repository for binaries (it will host all the builds generated by Jenkins)

Finally, we configure a new Repository in CloudCenter (there might be many), that needs to point at our new Artifactory repository to deploy new builds of your application automatically as they are released.

Cloud Center: setting up a repository for the artifacts that will be deployed

Here we set the IP address of the Artifactory server:

Setting up the repository on Cloud Center

We have now completed the setup of a CI/CD environment for a new project, just consuming a reusable service that creates it in 15 minutes (CI/CDaaS).

In the next post will show how to use it, following the lifecycle of the PetClinic application from editing the source code to automated deployment.

Credits 

This post is co-authored with a colleague of mine, Stefano Gioia.