Have you ever considered CI/CD as a Service?

Introduction    

Would you like to create a complete, fully configured environment for Continuous Integration / Continuous Delivery with a single request, saving you ton of times in configuring and managing the pipeline? If so keep reading this post, the first one of a series of three where Stefano and I will focus on automation in CloudCenter to align with a DevOps methodology. The entire series is coauthored with Stefano Gioia, a colleague of mine at Cisco. We will be talking about a solution we’ve built on top of Cisco CloudCenter to support CI/CD as a Service.   

To keep things simple, we've decided to split the story into three posts.  
•  In the first post (this one), we will introduce the use case of CI/CD as a Service, describing it in detail to show the business and technical benefits.  
•  The second post will guide you through automating the deployment of a complete CI/CD environment in few minutes, by implementing a service in the catalog exposed by Cisco CloudCenter.  
•  In the third post, we will show how to apply CI/CD to the lifecycle of a sample application.   

A little refresh on DevOps    

Before taking this journey let’s first clarify what we mean by using the term “DevOps.” DevOps is not a technology or a magic wand that will instantly help you unify the development (Dev) and management (Ops) of your applications.   
DevOps encompasses more than just software development.   
It's a philosophy of cooperation between different teams in a company, mostly Development (Dev) and Operations (Ops), with the ultimate goal of being more productive and successful in launching new (or updating existing) services to reflect what your customers want.    
As shown in the picture below, this is how we see DevOps: as a human brain. We know that the right hemisphere of a human brain is said to be creative, conceptual, holistic: the opposite of the left region, which is rational and analytic.  

    
Apparently, two distinct aspects that cannot always work together. But nature finds a way to allow them to cooperate for the benefit of the human body.     
The very same concept can be utilized for your company: your Dev and Ops team has to collaborate to get significant benefits in productivity such as shorter deployment cycles which means increased frequency of software releases and finally better reaction to market and customer needs by quickly deploying new application features.   

What about Continuous Integration / Continuous Delivery / Continuous Deployment?    

Today Continuous Integration, Delivery and Deployment is a common practice in IT software development.    
The central concept is about continuously making small changes to the code, building, testing and delivering more often, more quickly and more efficiently, to able to respond rapidly to changing business contexts.    
The picture below illustrates a sample CI/CD process divided into stages:  

Stages in the CI/CD process

       

• Continuous Integration 

A common practice of frequently integrating and continuously merging code changes from a team of developers into a shared code repository. Quite often, after new code is committed to a repository, the server triggers a “build” and runs some basic test. Once the application is built and all the tests are passed, it’s time to move to the next step: delivery.
  

•  Continuous Delivery  

Simply means delivering the build to a specific target (environment), like Integration Test, Quality Assurance, or Pre-Production.   

•  Continuous Deployment  

Is fundamentally an extension of Delivery (and sometimes it’s included in the Delivery process). It allows you to repeat deployment of your application to production, even many times per day. The production environment could be an on-premises environment or a public cloud. In some advanced scenario, applications can be deployed in a hybrid model, example database on-premise while business logic and front end in a public cloud. This is called a hybrid deployment.    

Usually, when defining a CI/CD pipeline you will need at least the following components:
•  A code repository to host and manage all your source code 
•  A build server to build an application from source code 
•  An integration server/orchestrator to automate the build and run test code 
•  A repository to store all the binaries and items related to the application 
•  Tools for automatic configuration and deployment    

Let’s take a look at the typical challenges of implementing a CI/CD process.  
First of all, having one single CI/CD toolset in your company is not a good option.      

Every LOB uses a different CI/CD toolset

    
As you can see from the picture above, every LOB (line of business) might have different requirements (and sometimes also a developer team inside the same LOB) and most likely they will use different technologies to create a new application/business service. They might even use different code language (Java, nodeJS, .Net, etc.) and be more familiar with a specific tool, e.g. GitHub rather than Subversion.     

How can you accommodate this diversity?    
You probably guessed it right. You can create multiple CI/CD chains and then install multiple tools (perhaps on VM or in a container) depending on the requirements coming from the developers and/or LOB.     
However, how much time you will be spending in configuring every time, for each LOB or DevTeam, a new CI/CD chain? Moreover, what about maintaining and upgrading all the components of the CI/CD toolchain to be compliant with any new security requirements from your security department?     

How long does it take to prepare, configure, deploy and manage multiple CI/CD chains? Sounds like a typical Shadow IT problem, a phenomenon that happens when a Developer Team or LOB users can’t get a fast-enough response from the IT and rush to a public cloud to get what they need. In that case, the solution was to implement automation and self-service to quickly provides the necessary environment to the end users, with the same speed and flexibility as the public cloud.    

Wouldn’t be much easier to adopt the same approach and merely automate the deployment and configuration of the CI/CD chain with a single request generated by a simple HTML form?    
Good news: that’s precisely the purpose of “CI/CD as a Service.”   

Introducing “CI/CD as a Service” 

Let us first clarify an important point: we are not discussing relocating your CI/CD resources and process to the cloud, and then consuming from there. Nor we are discussing the automation task performed by the CI/DP pipeline (push code to the repository, the automatic build of the code, test, and deployment).    

What we are proposing here is to automate the deployment and configuration of the tools that are part of your CI/CD Pipeline. With a single request, you will be able to select, create, deploy and configure the tools that are part of your automated CI/CD pipeline.    

The key things here is that the customer (a LOB as an example) can decide which are the components that will be part of the CI/CD pipeline. One pipeline could be composed by GitLab, Jenkins, Maven, Artifactory while another one could be composed by SNV,Travis,Nexus.    

Your customer will have their own CI/CD chain preconfigured, ready to be used so they can be more productive and focus on what’s matter: create new feature and new applications to sustains your business and competitive advantages.    

Let's now have a look at some of the technical and business benefits you can expect if you embrace CI/CD as a Service.

From a technical point of view, here are some good points:

•  Adaptable: your LOB/Dev Team can cherry-pick the tools they need it, from your catalog 
•  Preconfigured: all the components selected, once deployed, are configured to work immediately for you. 
•  Error-free: as you automated all the steps to deploy and configure the elements, this leaves no room for any human error or misconfiguration 
•  Clean: always have a clean, stable and up to date environment ready to be used 
•  Multi-tenant: serving multiple Line of Business (LOB) in your company: each LOB can have his own environment 
•  Easy Plug: as it’s callable by using REST API, you can easily integrate your IT Service Management system for self-service 
•  Independent Solution: can run on top of any infrastructure/on-prem private cloud    

Don’t stop the business: are you running out of on-premise resources? The solution allows you to quickly deploy the service, temporarily, in a public cloud to avoid blocking the development of your critical project.    

The majority of customers are interested in the CI/CD approach, and they are actively looking for a solution that can be easily implemented and maintained; therefore, we firmly believe that a solution for Cisco will be seen as an enabler for their business strategy.    

In the next post, we will present a solution that decouples the tools utilized in CI/CD pipeline from the deployment targets.  The Use Case is implemented by Cisco CloudCenter (CCC) a fundamental component of the Cisco Multicloud Solution.      

Credits

This post has been authored by Stefano Gioia, a colleague of mine at Cisco.

Protecting your border or offering a service to others?

The value of automation in the DataCenter

Everyone is aware of the value of the automation.
Many companies and individual engineers implemented various ways to save time, from shell scripts to complex programs and to fully automated IaaS solutions.

It helps reducing the so called "Shadow IT", a phenomenon that happens when developers can't get a fast enough response from the IT of the company and rush to the public cloud to get what they need. Doing that they complete and release their project soon, but sometimes troubles start with the production phase of the deployment (unexpected additional budget for the IT, new technologies that they are not ready to manage, etc.).

shadow IT happens when corporate IT is not fast enough

For sure, some departments are organized in silos (a team responsible for servers, one for storage, one for networking, one for virtual machines, of course one for security...) and the provisioning of even simple requests takes too long.

process inefficiency due to silos and wait time

Pressure on the infrastructure managers

So there is inefficiency in the company, that affects the business outcome of every project.
Longer time to market for strategic initiatives, higher costs for infrastructure and people.
Finger pointing starts, to identify who is responsible for the bottleneck.

The efficiency of teams and individuals is questioned, and responsibility is cascaded through the organization from project managers to developers, to the server team, to the storage team and generally the network is at the end of the chain... so that they have no one else to blame.

Those on the top (they consider themselves on top of the value chain) believe - or try to demonstrate - that their work is slowed down by the inefficiency of the teams they depend on. They try to suggest solutions like: "you said that your infrastructure is programmable, now give me your API and I will create everything I need on demand".

Of course this approach could bring some value (not much, as we'll see in the rest of the post) but it mines the relevance of the specialists teams that are supposed to manage the infrastructure according to best practices, to apply architectural blueprints that have been optimized for the company's specific business, to know the technology in deeper detail.
So they can't accept to be bypassed by a bunch of developers that want to corrupt the system playing with precious assets with their dirty hands.

The definitive question is: who owns the automation?
Should it be left to people that know what they need (e.g. Developers)?
Should it be owned by people that know how technology works, and at the end of the day are responsible for the SLA including performances, security and reliability that could be affected by a configuration made by others (i.e. IT Administrators)?


In my opinion, and based on the experience shared with many customers, the second answer is the correct one.
By definition the developer is not an expert on security: if he can easily program a switch via its REST API to get a network segment, it’s not the same when traffic needs to be secured and inspected.

The IT Admin patrolling the infrastructure

Offering a self service catalog (or API)

A first, immediate solution could be the introduction of an easy automation tool like Cisco UCS Director, that manages almost every element in a multi vendor Data Center infrastructure: from servers to networks to storage to virtualization in a single dashboard. But what is more interesting is that every atomic action you do in the GUI is also reflected in a task in the automation library, that allows you to create custom workflows lining all the tasks for a process that you want to automate.
A common example of automation workflow is the creation of a 4-hypervisors server farm.
A single workflow starts from the SAN storage creating a volume and 4 LUN, where the hypervisor will be installed to enable remote boot for the servers. Then a network is created (or the existing management network will be used) and 4 Service Profiles (the definition of a server in Cisco UCS) are created from a template, with individual ip address, mac address and wwn for each network interface. Then, zoning and masking are executed to map every new server to a specific LUN and the service profiles are associated to 4 available servers (either blades or rack mount servers). The hypervisors are installed using the PXE boot, writing the bytes in the remote storage, configured and customized, and finally added to a (new) cluster in the hypervisor manager (e.g. vCenter).

All this process takes less then one hour: you could launch it and go to lunch, when you're back you'll find the cluster up and running. Compare it to a manual provisioning of the same server farm, eventually performed by a number of different teams (see the picture above): it would take days, sometimes weeks. 
Other use cases are simpler: maybe just creating a 3 tier application with VM and dedicated networks.

Once the automation workflow has been built and validated, it can be used by the IT admin or by the Operations everyday, to save time and ensure consistent outcome (no manual errors). But it can also be offered as a service to all the departments that depend on the IT for their projects. 

You can build a service catalog with enterprise features: multitenancy, role based access control, reporting, chargeback, approvals, etc. But you can also offer (secured) access to the API to launch the workflow, offering a degree of autonomy to your consumers. Eventually, using a resource quota: you don’t want everyone to be able to create dozens of VMs every hour if the capacity of the system can't sustain it. 

They will appreciate the efficiency improvement, for sure.

What's in it for me?

If you allow your internal clients to self serve, you will: 

• get less requests for trivial tasks, that consume time and give no satisfaction (let them play with it),
• be the hero of the productivity increase (no requests pending in your queue)
• dedicate your time and skill to designing the architectural blueprint that will be offered as a service to your clients (so that everybody plays according to your rules)
• use policy based provisioning, so that you define the rules just once and map them to tenants and environments: every deployment will inherit them
• maintain control on resource consumption and system capacity, hence on costs and budget
• increase your relevance: they will come to you to discuss their needs, propose new services, collaborate in governance

Example: network provisioning

The discussion above is valid for the entire infrastructure in the Data Center.
Now I tell you the story of a customer that implemented it specifically for the networking.

They were influenced by the trend about SDN and initially they were caught in the marketing trap "SDN means software implemented networking, hence overlay". Then they realized the advantage provided by ACI and selected it as the SDN platform ("software defined networking", thanks to the software controller and the ACI policy model).

Developers and the Architecture department asked to access the API exposed to self provision what they needed for new projects, but this was seen as an invasion of the property (see the picture with the dirty hands).

It would have worked, but it implied a transfer of knowledge and delegation of responsibility on a critical asset. At the end of the day, if developers and software designers had knowledge in networking, specialists would not exist.

So the network admins built a number of workflows in UCS Director, using the hundreds of tasks offered by the automation library, to implement some use cases ranging from basic tasks (allow this VM to be reached from the DMZ) to more complex scenarios (create a new environment for a multi tier application including load balancer and firewall configuration, plus access from the monitoring tools, with a single request).

Blueprint designed in collaboration with Security and Software Architects

Graphical Editor for the workflow

These workflows are offered in a web portal (a service catalog is offered by UCSD out of the box) and through the REST API exposed by UCSD. Sample calls were provided to consumers as python clients, powershell clients and Postman collections, so that the higher level orchestration tool maintained by the Architecture dept was able to invoke the workflows immediately, inserting them in the business process automation that was already in place.

Example of python client running a UCSD workflow

All the executions of the workflows - launched through the self service catalog or through the REST API - are tracked in the system and the administrator can inspect the requests and their outcome:

The Service Requests are audited and can be inspected and rolled back

 Any run of the workflow can be inspected in full detail, look at the tabs in the window:

The Admin has full control (see the tabs in the window)

References

Cisco UCS Director
Cisco ACI 
ACI for Simple Minds
ACI for (Smarter) Simple Minds
Invoking UCS Director Workflows via the Northbound API 

Hybrid Cloud and your applications lifecycle: 7 lessons learned

Hybrid Cloud is a must nowadays, I will not spend a word to convince you (you’d not be reading this post if you didn’t believe it). This is the story of a real project.

This post provides more context about the story I summarized at Just 1 step to deploy your applications in the cloud(s).

The structure of the post is:

• Motivation
• Use Cases
• Time
• Software Stack
• Benefit of the architecture we implemented
• Lessons Learned (the most important part)

Motivation for hybrid cloud, and most of the work in my customers' projects, include the following areas:

- Cost control (there is a strong debate: some swear it’s cheaper, others have discovered hidden costs: e.g. network traffic in production, after they made a business case just on the cost of VM provisioning).

- Governance model (IT must find a way to maintain control over resources usage, design patterns, compliance and security when application developers chose private cloud or public cloud).

- Mature technical solution: architecture and technology (there are many good products and system integrators in the market)

But, once you have made a decision, what will you run in the hybrid cloud?

Will your applications be spread across the boundary of your datacenter (one tier inside, other tiers outside)?

Or can we say that it is rather a multi-cloud deployment, where you have a number of resource pools that you can use as a target for deployments?

This project was made by a large corporation, to test how a hybrid cloud can be built and operated and to verify the impact on their current organization.

It is not a full production environment, it’s a pilot project that demonstrated on a small scale how easily you can build a software defined fully automated data center, including both resource pools from your local data center(s) and from public cloud providers.

The solution is expected to be cost effective, of course, but the greater benefits come from business agility and consistent governance.

Use Cases:

The evaluation was focused on 3 main use cases, all requiring that end users order the deployment of a complex software stack from a service catalog: the target for the deployment can be either the private cloud or the public cloud, or a combination of the two. These are the areas where the implementation demonstrated the value of the multi-cloud solution:

• Business Intelligence (self-deployment of R Studio and additional tools)
• ETL (self-deployment of a common software for ETL that data scientists would use in autonomy)
• High Performance Computing (HPC) on OpenStack, with the integration of a DevOps pipeline.

Subject matter experts were provided from different lines of business in the company to support the implementation activities and evaluate the result. 

The use cases represent some frequent activities that the company needs in their usual business, especially in R&D. Improving efficiency and quality in the associated processes will have an impact on the overall business outcome. Applications were selected for the self service catalog that are deployed frequently (every week) and whose installation process takes time (some man days, accounting for both infrastructure and software setup), delaying business objectives.

Time:

All the activities in the project were delivered in time (six weeks), including the setup of the hardware and software systems for the hybrid cloud, the implementation of the 3 main use cases and some additional use cases, the functional tests and the stress tests. This is a demonstration that a proper selection of the technology and a good organization of the project allow for immediate return.

Challenges like setup of the remote access to the lab for remote experts, constraints in the networking and security configuration in the lab, some missing information about the process to install the applications (essential to build the model for the automation) slowed down the implementation. See Lessons learned.

Software Stack:

This is a complete end to end solution: its adoption will happen with a phased approach, starting from the components that grant an easy and immediate impact on the most critical business requirements and adopting some non-functional components later to complete the architecture. The extension from private cloud (based on any combination of VMware, other hypervisors and OpenStack) to a hybrid cloud (integrating AWS, Azure and more) was very quick (it is just a matter of configuration and definition of the governance model). Checkmarks in the picture show what we realized in the short timeframe of the project. The rest is part of a phased plan. The blue boxes show the components provided by Cisco.

The fundamental component in this architecture is Cisco CloudCenter (CCC), that has 2 main roles: 
- providing an orchestration solution that offers users the possibility to self-deploy complex software stacks from blueprints offered in a catalog, 
- brokering cloud resources from both private and public clouds (in the project we integrated VMware, OpenStack and AWS, but more clouds are supported).

CloudCenter manages the lifecycle of software applications in the cloud (at a level of abstraction where the underlying physical infrastructure does not matter).

The OpenStack use cases for HPC are supported by a Cisco Validated Design named UCSO: it includes a reference architecture for running the Red Hat OSP8 distribution on a certified hardware platform made of Cisco UCS servers and Nexus 9000 switches. The setup process and the operations are defined by the official deployment guide and Cisco's technical support assumes responsibility on the entire stack, including the Red Hat software.

The management of the entire DC infrastructure from a single orchestration platform was made possible by Cisco UCSD (UCS Director): a single dashboard and workflow engine to manage servers, network and storage, both physical and virtual. The status, the performances and the remaining capacity of all the systems were monitored with Cisco UCSPM (UCS Performance Manager).

Benefits of the architecture we implemented

The implementation of the multi-cloud solution demonstrated the major benefits that a hybrid cloud delivers.

• A consistent architecture based on software (and eventually hardware) components that integrate easily and satisfy all the business and technical requirements.
• All components in the architecture are loosely coupled and their integration is based on standard protocols and documented open API. As a consequence, every component can be replaced by an alternative solution (from a different vendor, from the open source, from a custom build) with no fear of vendor lock in.
• The adoption of a hybrid cloud solution can happen gradually, starting with a core implementation with the most critical components (e.g. CCC, ACI and UCSO), adding more features as a second step (infrastructure automation and monitoring) with UCSD and UCSPM, eventually a unified service catalog and ITSM portal later.

Lessons Learned:

1. use cases
2. network topology
3. security and trust
4. reusable work (repositories and services)
5. engage SME and business owners
6. document
7. refine (iterations, devops)

Use Cases 
The selection of the use cases is important. You need a quick return to demonstrate the value of the hybrid cloud: the adoption of the hybrid model should address immediate business needs, that the end users can appreciate, rather than be driven just by an industry trend. 
IT projects should not start because a new technology is very smart, but because the outcome makes the business easier and more productive.
Always engage your end users in the planning phase and avoid academic use cases that have a limited appeal on the decision makers. In this project we were lucky because the preparation was done by the steering committee very well in advance.
Once the models for the automation were ready, we could test any combination of the deployment for the application tiers: everything in the private cloud, everything in the public cloud, or the front end deployed on one side and the back end on the other side. The benchmarking capabilities of the product (CCC) allowed to compare the price/performances ratio of the different options based on vSphere, Openstack and AWS - specifically for each application, with tailored reporting.
 

Network Topology

A hybrid environment connects - by definition - areas that were designed separately (your datacenter and the public cloud). They have security policies and configurations that are not meant to work together, and this makes it difficult. Before you start the setup, dedicate the right time to collect all the requirements and to design the connectivity properly. 
We had some issues with the network proxies and the firewalls because of the protocols and ports that we needed to open to allow a proper integration of the Cloud Management Platform (running on premise) with the orchestration engine (with one instance running in each cloud region used in the project, to leverage the local API exposed by the cloud provider and to manage the lifecycle of the applications in the cloud). 

Another important requirement is to have a unique repository for all the artifacts, the blueprints and the installation packages for the applications: it should be reachable from all the target clouds that you plan to use, regardless its location (it can be either in the private or in the public cloud, but all the servers you deploy will access it to stand up a new instance of the application). 
The same applies to any public repository that is used in the setup of the applications (both commercial software and open source components, e.g. packages installed using yum).
See also CCC Components Overview for more detail.

Security and Trust

It's important that a good level of trust is established between the architects building the hybrid cloud and the operations team, especially the security guys. Special rules and new policies need to be setup to allow the new platform to work, it's impossible to keep the same old governance model that addresses a single end user identity. 
Sometimes I feel like I'm living - again - the same conflict that I had with Database Administrators, when I tried to configure JDBC database connection pools in the first Java application servers in the 80's. The system should be trusted, and a delegation of the decisions (authentication, authorization and audit) accepted.

Reusable work (repositories and services)

When you model a software application to automate its deployment, you should identify any building block that can potentially be reused in a different model. If you create a reusable (parametric) deliverable and save it individually in a common repository, next time you'll have the work ready to be reused.
This applies to architectural building blocks like database servers, web servers, load balancers, firewalls, distributed caches, etc. 
If they have been created as separate services, instead of just being a part of a monolithic model, they will appear in your designer's palette everytime you model a similar application and you can drag and drop them in the topology. We did that in the project and we saved a lot of time in the implementation. 

Engage SME and business owners

It is important that subject matter experts (SME) collaborate at the definition of blueprints and the build of the automation model. Even though documentation exists for the deployment of the application, you should work together. 
The user knows all the requirements, he knows how to verify and troubleshoot, he has encountered all the setup issues already.
I've learned that the best way to document the setup process for an application, so that you can use it as a reference for the automation, is to ask the SME to install it in front of you in a clean environment where the application was never run, and record a video of the process. It's faster than writing documentation, more complete and reliable. We did that using the desktop sharing feature in Webex and we recorded the sessions.  

Document

While you do the work, keep track of all the steps. Take (maybe informal) notes, but mostly take a lot of screen shots to document what you did. You can keep them on a wiki or on a shared folder, they will help a lot when you have time to create the formal documentation of the project. If you need to troubleshoot, eventually involving other people, this information will be unvaluable.
Of course, versioning and taking snapshots of all deliverables also helps in case you need to go back for whatever reason. 

Refine (iterations, devops)

Create the implementation for a minimum viable product (MVP) as soon as you can. Get the product (i.e. the entire self service catalog, or just the implementation of a single application blueprint) to early customers as soon as possible, to get their feedback before you go too deep in the implementation.
Applied to a hybrid cloud scenario, this will help to evaluate:
- quality of the service you are building, including documentation
- how much the users need it and use it in the real world
- performances of the distributed environment and any bottleneck (network, computing, configuration)
- security implications 

You will have all the time to make it perfect, through iterations that improve the implementation, collect feedback, allow for tuning the design and the configuration. No need to work in a hurry and make mistakes, while you keep your users waiting for the final "perfect" product but they don't see any progress.

Just 1 step to deploy your applications in the cloud(s)

As described in my previous post about Terraform, the deployment environment for a new application can be created "on demand" by configuring physical and virtual resources.

Good open source products allow to describe the desired state and to automate the setup of a target infrastructure.

They can also deploy your software application and configure it properly.

But is some use cases this is not enough.

You might want to offer your users - depending on their needs and their skills - a visual catalog in a web portal.

You might want to apply a governance model based on policies, use different clouds as possible targets for the deployment, offer a easy way to manage the life cycle of the deployment (start, stop, scale up/down, terminate) and get reports on usage of the resources.

If this is the case, there are good solutions available.

One of these is Cisco Cloud Center, a powerful tool that offers two main use cases: 

• modeling the deployment of a software stack (creating a template or blueprint for common deployments) and 
• brokering cloud services (different resource pools available from a single catalog).

A easy to consume (and manage) self service catalog

Open Source or commercial products?

In the same project where I used Terraform to deploy Apache on Openstack, I also used Cisco Cloud Center to deploy a portal application on Openstack.

But at the same time, I offered the possibility to target the same deployment to a public cloud (AWS in this particular case) or to the private cloud (choosing between Openstack and vmware in this particular case). No duplication of the effort was needed, because the model you creat is not referred to a specific cloud as a target. It will be matched, when a user orders it, with one of the cloud avaliable for him or for his project.

So I was able to show the difference between a free, open source solution (Terraform) and a commercial product (Cloud Center) in a similar scenario.

The second option addresses different needs of the organization and offers a richer solution.

It’s up to you to evaluate which one fits your requirements better. 

Modeling, policies and multitenancy

One of the differences is that Cloud Center offers a graphical editor to model the topology and the dependencies among all the building blocks of your deployment.

You have a library of services (software applications from a repository, physical and virtual services like load balancers and firewalls).

Services can be dragged and dropped in the editor, then you set their properties and dependencies. 
The architecture of the application you're modeling can be based on a single server or a number of servers with different roles.

If the application architecture has multiple tiers, every tier gets its own attributes and policies: as an example, you can set the minimum and maximum number of instances in a cluster of web servers (or application servers or database servers). 

Autoscaling policies will tell the orchestrator to increase or decrease the number of servers based on metrics like consumption of cpu or memory, inbound/outbound traffic, etc.

Everytime the cluster changes, the orchestrator will modify the configuration of load balancers and firewalls accordingly: no manual intervention is needed.

Models are saved in the catalog and offered to users in a multitenant organization: every tenant is given a portion of resources (target cloud environments) and services (models available in the catalog to deploy applications) that the tenant administrator can offer to his own users and groups... and sub tenants. Every tenant cannot see other tenants' stuff.

A graphical editor to model blueprints for application deployment in hybrid cloud

Dashbooard and Reporting

Every user has a dashboard that shows the consolidated information about all the applications he has deployed (or the other users in the same tenant), and can manage the lifecycle of all the deployments.

Of course the administrator of the system sees the global view including all the assets.
Active VM per cloud and per application are shown in the dashboard, as well as associated costs.

Cloud Center's Dashboard

A powerful reporting features allows to filter deployments and costs by user or group, application, environment and cloud.
Data can also be exported in different formats, to be consumed by humans and other systems.

Unified reporting

Architecture

The architecture of the Cloud Center product is based on two Virtual Machines: the Manager (CCM) and the Orchestrator (CCO).

The Manager is the engine where policies and application models are defined, and where the user portal runs. The Orchestrator lives within each of the target clouds (indeed, there is one CCO in each cloud region), receives commands from the Manager and executes them locally using the API of the cloud platform.

Cisco provides orchestrator images that are specialized for every cloud supported by Cloud Center.  So you have a single place to manage all your cloud resources, and a single model to maintain: you don't need a model, or a workflow, or a script for every target cloud where the syntax of that specific API is used. You create a single model, that is completely decoupled from the target of the deployment: this reduces the amount of work (a single model instead of many) and makes the maintenance of the model easier and more consistent (you don't have to evolve many models for the same application).

 

Cisco Cloud Center architecture

Comparison

Two solutions for the same use case, one for free and one at a cost?
Indeed they address different requirements: as described above, Cloud Center is for enterprise organizations that need to rationalize their usage of cloud resources. It is used by the corporate IT to provide flexibiliy and agility to their developers (within a governance model), to standardize the architecture of their projects based on blueprints (including what products, what versions, what setup configuration they prefer) and to get reports on consumption.

Service providers can use Cloud Center to broker third parties' resources, offering a single catalog to their customers. The hierarchical multi tenant organization and the sophisticated cost models that can be offered make it simple.

I suggest you to consider it if you are using, or plan to use, two or more cloud providers (counting also your private cloud or your virtualized data center). You will see an immediate benefit in terms of compliance and efficiency.

References

http://www.cisco.com/c/en/us/products/cloud-systems-management/cloudcenter/index.html
http://www.cisco.com/c/en/us/solutions/data-center-virtualization/one-enterprise-suite/index.html
http://docs.cliqr.com/display/CCD46/CloudCenter+Documentation+4.6