Showing posts with label IaaS. Show all posts
Showing posts with label IaaS. Show all posts

May 25, 2020

Cost control in a multicloud world - part 2


This post is the second part of a discussion about optimization of the cloud budget and cost control in your IT organization. The first part is here.

The CloudCenter Suite


The CloudCenter Suite is a key component in this framework: it is made of three modules that offer provisioning, lifecycle automation and – what we are discussing here – cost control.

The Cost Optimizer module collects data from the API of all the cloud providers to create a series of detailed reports, that you can use to understand where and why you spend your money. You can slice and dice the information across different dimensions, and you can schedule reports or download them to feed a billing system.

complete and granular reporting of cloud spend
complete and granular reporting of cloud spend



You can create any custom organizational hierarchy to map your business (departments, customers, projects, etc.) and give them visibility and responsibility of the budget consumption.


custom hierarchy of cost groups
custom hierarchy of cost groups



budget management with Cisco CloudCenter Suite
budget management



The Cost Optimizer gives you recommendations for rightsizing, wherever your assets are deployed, analysing their behavior. You can evaluate the suggestion and then act manually, or you can enable the tool to do it for you automatically.

recommendations for rightsizing and other optimizations
recommendations for rightsizing and other optimizations



It will also tell you when it makes sense to adopt reserved instances to get a discount, showing you how much you’re going to save.


Act now to reduce your spending… across all clouds


The best practices and the tools are there. You can choose among tools that are specific to a cloud provider (they all offer good solutions) or a cloud agnostic solution that works with all clouds.

With the Cisco CloudCenter Suite you get a fully detailed report of your inventory, all the services you are consuming everywhere, and the efficiency from a budget standpoint.

You also get actionable suggestions to save money that can be, if you configure the tool to do so, executed automatically. If you prefer, you can just get the list of suggested actions and implement them manually.

Thanks to the Cisco CloudCenter Suite you can setup a common governance model and a set of policies in one place, instead of replicating the build of reports and automation in every single cloud, based on full visibility that goes beyond the suggestions given by your service providers.

All you have to do now is to download and test the CloudCenter Suite (30 days trial), or contact us for a live demo or a discussion of your use cases.

Cost control in a multicloud world

Using public cloud is not as cheap as you expected?

Is allocating budget and verifying spending a little more difficult than they had told you?

You’ll probably find some best practices and tools for cost control in public cloud services, described in this series of two posts, useful to improve the efficiency of your consumption. They apply to every IaaS and PaaS service in a multicloud context.

What CxO expect from IT


Surveys show that the enterprise IT is getting a predominant role in front of the lines of business when they need cloud services. Not just to select the best solution for them, but to help keeping the financial aspects in control (source: RightScale State of the Cloud Report).


role of enterprise IT in cloud decisions



Looking at the initiatives, that is where budget is allocated, cost control and cost saving is on top:


Allocation of budget for cloud initiatives


Like drug dealers


Cloud providers are making a lot of money. And, of course, they want more customers and they want to retain the existing ones. Competitors steal some, and others just fly away when they realize that operating applications in production is more expensive than they had thought.

So, they offer you some candies, just to taste what a beautiful trip they can offer you. Even with a free account, you get amazing services that work very well. See also Azure and Google. They all make building business applications quick and easy.


appealing services offered by AWS


Developers are attracted by that, and they love creating cloud native applications using PaaS services. But they do not realize, or they just don’t care of, how expensive it will be to run applications in production.

In addition, they generate a lock-in because PaaS services are not portable across clouds.


Is public cloud easier or is it cheaper?


Now ask yourself this question: do you use the public cloud because it’s easier or because it’s cheaper? Or maybe you’re just lazy and you want to delegate the SLA responsibility to the service provider?

I will not discuss if it’s easier in this post. But, for sure, it’s not cheaper. Budgets go out of control very often.

Those are some tips from Amazon (source: AWS re:Invent2019)

tips for saving from AWS


Of course, cloud providers want to help you to be efficient but… not too much! The two green actions look like the most effective, now let’s see if we can do anything better.


Cost control framework


We could create a cost control framework, as the large company I took this information from.


cost saving framework



We focus mostly on two aspects: avoidance of unnecessary costs and iteration of the improvement actions.

In the avoidance best practice, we concentrate on the efficiency of VM snapshots retention: how many and how long. Storage volumes and public ip addresses should be monitored, because they generate a cost. When you use a S3 storage you can optimize the cost based on frequency of access, speed and size. And VM should not be larger than need, because you pay also the capacity in excess.  Suspending VM at night, in the weekend or whenever the business application is not used, also saves money. And so does scaling capacity dynamically

You should monitor the situation carefully, and automation helps here. You can setup alerts and governance policies, having reports sent to the stakeholders. Automation in provisioning, but mostly in reporting and resource adjustment is key.


You can obtain important savings


This is what cost optimization saved in the context of a large SaaS service operations. Most of the saving comes from adoption of reserved instances where appropriate and from cleaning environments used for proof of concepts. The total saving is $7M per year.


savings from cloud optimization



And this is what they are planning: choosing the right instance types, rightsizing, cleaning up will save $7M more per year.


expected savings from recurring optimization
expected savings from recurring optimization


Cost control: a solution


We will examine a simple 3 steps process to save your budget.


  1. Understand your assets and ecosystem
  2. Optimize based on best practices, on investigation through your assets or... recommendations from a tool
  3. Avoid unnecessary costs and iterate of the improvement actions

Easy principles to set a governance model are:

  • Define (and enforce) budgets for your customers, projects and departments.
  • Monitor and report about that.
  • Set policies to automate suspension, autoscaling and cleanup.

Cisco offers a solution that helps you to achieve all that, quick and easy.

We have built a framework that is based on the feedback loop suggested by best practices (e.g. the second principle of DevOps recommends looking at the entire system as a whole and iterating the optimization).


the optimization loop
the optimization loop

In next post you will find a solution for implementing your cost control quickly and consistently across all the clouds you use: any combination of private cloud technologies and public clouds, with no need to adopt specific solutions for each individual target.

Keep reading, it will prove useful for your strategy.



July 19, 2019

Just one button to provision a production-grade Kubernetes cluster

(this is a guest post, authored by my esteemed colleague Fabio Di Niro)

Do you remember?


I bet all of you who are working or playing with Kubernetes remember perfectly the first time you tried to install it.
And the second.
And the third.
...
And the one that finally worked out.

And if you’re a professional you remember also the long path that brought you to own the expertise on Kubernetes that you need to install and fine-tune production grade clusters.
Or, if you’re not a Kubernetes professional, you probably remember how much time it took for you to find someone able to perform a valid Kubernetes install...and how much it costed.

To save all this time and effort to our customers Cisco released the Cisco Container Platform (CCP), a turnkey solution to easily provision production-grade Kubernetes clusters on-prem or in the cloud in minutes, with few mouse clicks and requiring little to no knowledge of K8s.
All the needed integrations with network, storage, computing and security are done automatically by CCP so that the provisioned K8s clusters are ready to run in production.
Clusters provisioned by CCP are already equipped with finely configured monitoring and logging tools like FluentD, Grafana, ElasticSearch, Kibana.
Through the Container Network Interface (CNI) you can choose whether to leverage Cisco ACI as network infrastructure or Calico (no dependence on the underlying infrastructure).

This is already great, but I thought to create a demo that may push the simplicity of those “few mouse clicks” to its limit, making possible to create a production grade cluster in just one click.







Introducing the Kubernetes dash button.

The concept is fairly simple: build a dash button that, once pressed, creates a production grade Kubernetes cluster ready to use.

Leveraging the rich set of the Cisco Container Platform (CCP) APIs this is even too easy, so I thought to add some more feature on top:

- I wanted to provision the cluster and access it just through the dash button. So, I want CCP to display on the dash button itself the IP address of the master node of the cluster created
- The start and finish of the cluster provisioning process had to be confirmed, so the communications had to be bi-directional with the dash button
- I wanted a fair battery life that would avoid me to recharge the button every day, so I needed to have electronics able to sleep or hibernate
- My lab, where I have the infrastructure and the CCP, is behind a proxy, so I can’t listen for calls inside the lab, I can just initiate communications from the lab. So, I needed a way to change the “push” of the button in a “pull” of the button press information
- I wanted to use the button everywhere I go without worrying about the local Wi-Fi settings



How it works

To satisfy all the above requirements I added a couple of elements in the picture, ending up with the following architecture:



The button is based on an Arduino ESP 32 board, it connects via Wi-Fi to my smartphone and uses its internet connection, this way I can use the button everywhere my phone has data signal. The button leverages a publish-subscribe message service (MQTT) in the cloud to bypass the limitation of the proxy I have behind my lab and reach a couple of scripts that calls the right API in the Cisco Container Platform to trigger the provisioning of a shiny new Kubernetes cluster.
Once the cluster is provisioned the IP address of the master node is returned to the dash button that shows it on its display, at this point it is ready to accept connection and be used.

A 3D printed enclosure completed my project, I took an existing model but then I decided to  leverage the capabilities of CCP to deploy K8s clusters on-prem or in the cloud so I designed the two different enclosures you can see in the picture to have two different dash buttons for the two different deployment target.
All the code and 3D designs have been released and are publicly available at: https://github.com/fdiniro/CCPDashButton




Now, before doing my demo, I can ask to my customers: “How much time and effort takes you to install a production-grade, fully operationalized and secured kubernetes cluster?” and whatever answer I get I know I can answer “I can do it in 2 minutes blindfolded and cuffed”.

You can see the recorded demo here: https://youtu.be/-F-xR0XNPBs



July 25, 2018

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.




July 28, 2017

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
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
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 patrols the infrastructure
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).


3 tier application blueprint
Blueprint designed in collaboration with Security and Software Architects



Graphical editor for the workflows, with the tasks library
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
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 IT admin can audit the requests for the automation workflows
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 IT admin can inspect any run of the workflows
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 



September 19, 2016

Infrastructure as Code with Terraform and Cisco Metapod


Recently I worked with a customer to explore the concept of Infrastructure as Code.
They like open source solutions for the automation of the infrastructure and for managing the software applications life cycle.
To reach the first objective their goal is a private cloud based on Openstack, while they will use Ansible and Terraform to manage the environments for different projects.

Managing the Infrastructure as Code means that the definition of the infrastructure is maintained in text files, that could be stored in a version control system like you do with the source code of the application.
If you do that, the same lifecycle applies to both the infrastructure and the application: creation of staging or production environments, automated testing, etc.
Using blueprints helps to improve the quality of the final result of the project and grants compliance with policies and eventual legal obligations.
Benefits include speed, cost savings (avoiding a static allocation of pre-provisioned resources) and risk reduction (removing errors and security violations).
Terraform is one of the best open source tools to manage your Infrastructure as Code: it’s easy to install, learn and use (one hour).
You could start from tutorials and free examples available on Internet.

Here is an example of full automation (we'll try to get a little better result):



As a first step, to make the usage of Openstack easier on a large scale, we discussed the value of a managed service.
If the IT organization could just focus their effort on the development and operations of the business applications, instead of running the infrastructure, they would create more value for the internal customers (company's lines of business).
So I proposed the adoption of Cisco Metapod, that is Openstack as a managed service (delegation of all the tough administrative and operational work to a specialized 3rd party, while you just use the Openstack user interface and API enjoying a SLA of 99.99% uptime). 
I have described the advantage of adopting Openstack as a managed service in this post: Why don't you try Openstack (without getting your hands dirty)? 
Services offered by Cisco Metapod around Openstack
Services offered by Cisco Metapod

We created a lab where Openstack abstracts the resources from the physical and virtual infrastructure (etherogeneous servers, network and storage) and the configuration of different environments is managed by Terraform, so that you can create, destroy, restore and update a complex system in few minutes.


Free to use Openstack for your apps, instead of managing it: focus on your real business

With Terraform you can describe the architecture in a declarative form (in a manifest file).
You simply describe what you need (the desired state), not how the different components (devices and software) must be configured with all their parameters and their specific syntax.
The goal of Terraform is to match the current state of the system with the desired state.


Desired State vs Current State


Terraform is used to create, manage, and manipulate infrastructure resources. Examples of resources include physical machines, VMs, network switches, containers, etc. Almost any infrastructure noun can be represented as a resource in Terraform. Terraform is agnostic to the underlying platforms by supporting providers. A provider is responsible for understanding API interactions and exposing resources. Providers generally are an IaaS (e.g. AWS, GCP, Microsoft Azure, OpenStack), PaaS (e.g. Heroku), or SaaS services (e.g. Atlas, DNSimple, CloudFlare). 

Infrastructure as Code
Infrastructure as Code




Desired State

In my lab I reused a good example that I found on GitHub at https://github.com/berendt/terraform-configurations 
It contains all the resources you need to deploy a new Devstack instance (a all-in-one instance of Openstack, useful for developers) including the needed networks, public addresses, firewall rules on a target cloud platform. That, incidentally, is a Openstack instance (so we are deploying Openstack on Openstack).

Here is the content of the main.tf file used by Terraform: it references variables with the format ${variable_name}, including the output from actions on other resources. Dependencies between resources are managed automatically by Terraform. A separate file can contain the predefined values for your variables (like the references to the Openstack lab in my example).

If you are not interested in the content of this file (I guess it applies to 70% of my readers) you can skip it and go to next picture... there is also a good recorded demo down there   :-)

 

main.tf (the manifest file where Terraform ready the desired state of all the resources):

provider "openstack" {
  user_name  = "${var.user_name}"
  tenant_name = "${var.tenant_name}"
  password  = "${var.password}"
  auth_url  = "${var.auth_url}"
}

resource "openstack_networking_network_v2" "terraform" {
  name = "terraform"
  region = "${var.region}"
  admin_state_up = "true"
}

resource "openstack_compute_keypair_v2" "terraform" {
  name = "SSH keypair for Terraform instances"
  region = "${var.region}"
  public_key = "${file("${var.ssh_key_file}.pub")}"
}

resource "openstack_networking_subnet_v2" "terraform" {
  name = "terraform"
  region = "${var.region}"
  network_id = "${openstack_networking_network_v2.terraform.id}"
  cidr = "192.168.50.0/24"
  ip_version = 4
  enable_dhcp = "true"
  dns_nameservers = ["208.67.222.222","208.67.220.220"]
}

resource "openstack_networking_router_v2" "terraform" {
  name = "terraform"
  region = "${var.region}"
  admin_state_up = "true"
  external_gateway = "${var.external_gateway}"
}

resource "openstack_networking_router_interface_v2" "terraform" {
  region = "${var.region}"
  router_id = "${openstack_networking_router_v2.terraform.id}"
  subnet_id = "${openstack_networking_subnet_v2.terraform.id}"
}

resource "openstack_compute_secgroup_v2" "terraform" {
  name = "terraform"
  region = "${var.region}"
  description = "Security group for the Terraform instances"
  rule {
    from_port = 1
    to_port = 65535
    ip_protocol = "tcp"
    cidr = "0.0.0.0/0"
  }
  rule {
    from_port = 1
    to_port = 65535
    ip_protocol = "udp"
    cidr = "0.0.0.0/0"
  }
  rule {
    ip_protocol = "icmp"
    from_port = "-1"
    to_port = "-1"
    cidr = "0.0.0.0/0"
  }
}

resource "openstack_compute_instance_v2" "terraform" {
  name = "terraform"
  region = "${var.region}"
  image_name = "${var.image}"
  flavor_name = "${var.flavor}"
  key_pair = "${openstack_compute_keypair_v2.terraform.name}"
  security_groups = [ "${openstack_compute_secgroup_v2.terraform.name}" ]
  floating_ip = "184.94.252.189"

  network {
    uuid = "${openstack_networking_network_v2.terraform.id}"
  }

  provisioner "remote-exec" {
    script = "deploy.sh"
    connection {
      user = "${var.ssh_user_name}"
      key_file = "${var.ssh_key_file}"
    }
  }
}


To make it simple, for this blog post I replaced the part that deploys Devstack with a simpler setup of a web server (Apache).

deploy.sh (Terraform will copy and execute it on the remote instance as soon as it is created):

#!/bin/bash

# author: Joe Topjian (@jtopjian)
# source: https://gist.github.com/jtopjian/4ffc82bfcbbcc78d07e4

sudo apt-get update
sudo apt-get install -y -f apache2


The goal is to demonstrate how easy it is to create a new software environment on a Cisco Metapod Openstack target from scratch and run it. 
The following pictures show the Metapod console before and after running the "terraform apply” command on my computer.

This is before I run the command:

The Openstack console from Cisco Metapod: view of the tenant networks
The Openstack console from Cisco Metapod

And this is the expected result (network and server infrastructure created, apache installed):

Terraform has created all the required resources in Openstack
Resources created in Openstack

Next video (the most important part of this post) is a recorded demonstration of the creation of the new Apache server: you can see the launch of the “terraform apply” command that, after reading the manifest file, creates a network, a subnet, a router with two interfaces, a floating ip and a instance on Openstack. Then the Apache web server is downloaded and installed in the new instance.
The Metapod console is left in the background and you see the Openstack objects pop up as they are created.
Finally the home page of the new web server is tested.

 


 


Conclusion

It is very easy to get rid of the delays, the misunderstandings and the inefficiency of many current IT organizations.
If you standardize the process that developers follow to obtain the environment for a new project - in all the phases of the life cycle - you can enable a faster go to market for new business initiatives making your customers happy.
It would be a first step towards DevOps (more is required, mostly in changing the culture of both developers and people in operations).

Infrastructure as code is a brilliant way to create the needed infrastructure on demand (and release it when no longer needed), to maintain it based on blueprints and manage the definition of the infrastructure with the same tools you use for the application source code: a text editor (or your preferred IDE), a version control system, an automation tool.

If you have a IaaS platform like Openstack, provisioning of both virtual and physical resources is made easy.
If you do a further step forward with a managed service, someone will grant that your Openstack is correctly configured for production, up to date and in perfect health. You enjoy all the benefits, without the hassle of setting it up and operating it daily.




References:
Configuration to run acceptance tests for Terraform/OpenStack - https://github.com/berendt/terraform-configurations
Why don't you try Openstack (without getting your hands dirty)? - http://lucarelandini.blogspot.it/2016/06/why-dont-you-try-openstack.html