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.

Why do you run slow, fragile and useless applications and are still happy?

If you are not interested in the detail, at least browse the post and watch the amazing video recordings embedded   :-)

We have already discussed the value of automation in the deployment of software applications.
It is also clear that collecting telemetry data from systems and applications into analytic platforms enhances visibility and control, with an important return on your business.

Cisco offers best of breed solutions for both automation and analytics, but the biggest value is in their  integration end to end. Your applications can be deployed with Cisco CloudCenter and completely controlled with AppDynamics and Tetration, with no manual intervention.

Why do you need that visibility?

Thanks to the information provided by AppDynamics, you have immediate visibility of the performances and the dependency map of your software applications. Tetration exposes its compliance and the performances from a system standpoint.
CloudCenter offers your users a self service catalog where applications can be selected for deployment in one of the clouds you have configured as a target: but the smartest feature is that every deployment can also install the sensors for AppDynamics and Tetration automatically in each node of the application topology, so that telemetry data start to be collected immediately.

why we need to collect information at runtime

With that, now you have no excuse to keep running applications that do not perform well enough, that expose vulnerabilities and that produce limited business return due to poor customer satisfaction or inefficiency. The same applies to non compliant applications that break your security rules or your architectural standards, that were deployed some years ago and now are untouchable due to complexity and lack of documentation.

With such an easy integration of telemetry and the insight that you can get immediately, it makes no sense keep those monsters running in your datacenter or in your cloud. You can evolve them and remove the bottlenecks and security risks once identified.

Analytic tools add value to the application telemetry

We want to demonstrate how easy it is.

This post is a follow up to the demonstration of the integration of Cisco CloudCenter with Tetration: we extended the demo with the addition of AppDynamics, so that our applications are now completely under control when it comes to security, compliance, performances and business impact.

Architectural Overview

 

We used a well known application as an example: WordPress is an open source tool for website creation, written in php.  It uses a common LAMP stack: Apache + php + mySQL, running on Linux.

Wordpress is a two tier application, so you generally deploy two VM to run it: the front end is an Apache web server with the php application, the back end runs the database (mySQL).

We want that each tier is monitored, as a default, by both AppDynamics and Tetration. This must happen without introducing any complexity for the user that orders Wordpress from the self service catalog and must work in any target cloud. Based on the administrator preference, the user could even be unaware of the monitoring setup.

Overview of the architecture

Next paragraphs describe the architecture of AppDynamics and of Tetration, so that you understand what integration we built to make CloudCenter inject telemetry sensors in each deployment. 
Then the process triggered when a user deploys Wordpress from the CloudCenter catalog is explained.
Detailed video recording of all the steps is also provided. 

AppDynamics: Architecture of the system

AppDynamics uses agents to collect information from the running servers and to send them to the controller. Agents are specific for the runtime of various programming languages, but there are also agents that interact only with the operating systems: you choose the type of agent that best fits each node. Also databases and their transactions can be monitored.

The Controller is where users go to view, understand, and analyze that data sent by agents.

Agents send data about usage metrics, code exceptions, error conditions and calls to backend systems to the Controller.

AppDynamics overview

CloudCenter: the Application Profile

 

Next picture shows the Application Profile of the Wordpress service that we have created in CloudCenter. Each VM in the two tiers will contain the application and the required sensors for AppDynamics and Tetration. 

The Tetration injector component is an ephemeral Docker container that is used by CloudCenter just to invoke the API exposed by the Tetration cluster, so that the telemetry data are welcome when they arrive and associated to the scope of the Wordpress deployment. It disappears when the deployment is completed.

Topology of the application deployment, showing the sensors applied

As for any other application, the integration is implemented using custom scripts to deploy the agents for AppDynamics and Tetration

All application artifacts, scripts and services are stored in a Repository, and pulled by the CloudCenter agent running in each VM.

CloudCenter executes our scripts during different stages of the deployment, to add the AppDynamics Agent and the Tetration Sensor (using the same technique you could add any other agent that you use for backup, monitoring, etc.).
This is a video (2 min) showing how the Application Profile for Wordpress is built in CloudCenter:

CloudCenter integration with AppDynamics

The green boxes in next picture show the sequence of actions executed by the CloudCenter agent to deploy the AppDynamics php agent in the frontend VM: the same actions that the administrator would do manually.

Installing and configuring AppDynamics agents

For your reference we used a shell script with placeholders, where configuration parameters are replaced by CloudCenter dynamically as listed below:

AGENT_LOCATION=“http://cc-repo.rmlab.local”

APPD_CONTROLLER="appd.rmlab.local”

APPD_CONTROLLER_PORT="8090”

APPD_ACCESS_KEY="a4abcdc7-ce1c-41cb-[cut]”

APPD_ACCOUNT_NAME="customer1”

APP_NAME="$parentJobName” ($parentJobName will be replaced by the value WPDEMO, that is the name given to the deployment by the user)

TIER_NAME="$cliqrAppTierName” ($cliqrAppTierName will be replaced by the value WSERVER, that is how the tier is identified in the Application Profile)

HOST_NAME="$cliqrNodeHostname" ($cliqrNodeHostname will be replaced by the value C3-b2a9-WPDEMO-WSER, generated by CloudCenter when it provisions the VM)

This video (2 min) shows how the existing Application Profile is updated adding the deployment of the AppDynamics agent:

Tetration: Architecture of the system

Tetration is a ready-to-use big data platform which runs a Hadoop cluster on its core.

As described in a previous post, Tetration collects telemetry streamed by software and hardware sensors. It stores metadata within the data lake and runs machine learning algorithms to provide business outcomes

Tetration sensors, downloaded from the cluster itself, embed the required configuration and don’t need any user input. As soon as they are installed, they start to stream rich telemetry and can optionally control local workload policy enforcement

Tetration overview

CloudCenter integration with Tetration

At deployment time, a dropdown list allows the user to select one of the two types of sensor: Deep Visibility, or Deep Visibility with Enforcement (of security policies).

The telemetry data for this application are segregated under a specific scope, created by CloudCenter during the provision phase using the variable $parentJobName (containing the value WPDEMO in our demonstration).

The sensor are installed in each VM via a custom script, as described by next picture:

installing and configuring Tetration agents

Wordpress VM with all the agents installed

Next video (6 min) shows how a service (Tetration Injector) is created and then added to the existing Application Profile:

Result of the deployment seen in CloudCenter, Tetration and AppDynamics

This video shows the deployment of the Wordpress application from the CloudCenter self-service catalog.

And next video shows the analysis of telemetry data in Tetration, when the Wordpress application is deployed:

Finally, we look at AppDynamics to see the analysis of the behavior of the application from a business standpoint:

Summary 

Only Cisco can offer automated end-end, real-time application intelligence giving you 360 of visibility at business and network side Do you want to run this demo in your lab? Engage with us to setup a Lab.
All source code, the CloudCenter Services and the Application Profiles are available on github.

Credits and Disclaimer

This post describes a lab activity that was implemented by two colleagues of mine, Riccardo Tortorici and Stefano Gioia.

We created a demonstration lab to show our customers how easy it is to integrate the three products.

This is not the official documentation from Cisco about the integration, that will be released soon. 

References

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

AppDynamics: https://www.appdynamics.com/

Tetration: https://www.cisco.com/c/en/us/products/collateral/data-center-analytics/tetration-analytics/datasheet-c78-737256.html

Previous post on the integration of CloudCenter with Tetration: https://lucarelandini.blogspot.it/2017/10/turn-lights-on-in-your-automated.html

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
 

Is Agile dead (already)?

I've been pushing Agile development for long time, as opposed to traditional methodologies like waterfall... or to no methodology.

I no longer deliver IT projects myself, but I help customers and partners to plan and deliver theirs.

The most important goal I set is achieving quick wins, like I described in become-cloud-provider-in-3-months.

A quick win encourages all the stakeholders (the project team, their clients, the lines of business that provide the budget, everybody up to the CEO).

Not only it demonstrates that the solution works, but it is a concrete measurement of the return on the investment.

Generally projects are not done because they are smart, but because they are supposed to generate a financial gain (more revenues or lower expenses). Even when the goal is described as a faster go to market, the ultimate target is generating more revenues.

Agile development is not the only way to achieve a quick win, but it helps.

It also helps in reducing the project risk because, if you have to fail, you fail soon (and save a useless effort).

So, when a colleague sent me this article to solicit my comment, I almost felt insulted by the author... though I'm pretty sure he was not referring to me  :-)

A note on the author: 

Matthew Kern has a long experience in the field, so he knows what he's talking about.

He’s been writing many posts since 2015 to explain that Agile is dead.

Definitely he knows the Agile methodology and its usage, so he deserves respect.

More, he published a followup of that post offering the correct interpretation: probably he received too many protests.

Nevertheless my first impression was negative, because he was criticizing my fundamental believes.

But reading it carefully I understood that he's not wrong. He criticizes the evolution of the Agile methodology and the usage that someone made of it as a marketing tool, also in the light of newest trends like DevOps.

In my opinion, some overstatements in the article - starting with the title - are a mean to get visibility.

Indeed, in the conclusion he explains what he really means (and I partially agree): he refers to the “Agile” brand, to politics and to commercial usage (literature, consulting, marketing...).

When he says that agile don't work for large enterprises, I would distinguish between vendors of software products and customers doing it for their own project. 

The lifecycle of a software applications is completely different in these two scenarios, and so are the business requirements, the expected quality of the product, the variety of users, the frequency of the updates and bug fixes. 

When he says that many projects fail, he highlights a fact that is common to all methodologies.

But, at least, with Agile you fail soon (that is one of the objectives: better to fail in one month than after 1-2 years of unproductive activities eating your time and money).

So, if we focus on the hype, on brands and marketing activity, Agile is being replaced by DevOps (that can be considered its evolution, taking care also of the Operations with continuous delivery and feedback) and later even DevOps will be replaced by next hype.

But they both produce a value for developers and for the IT: you can see it in the cultural shift and in the individual interpretation of the principles, rather than in  coded best practices. As an example, I’ve seen that my colleagues in Cisco Advanced Services started using Agile with visible benefits for both themselves (less bureaucracy) and customers (better and faster projects).

In conclusion, definitions are important and they help to spread the knowledge.

But theory is important for professors only, while a good practice makes developers and project managers happy.

If they adopt the principles of Agile, they work - even using Scrum informally - implementing those guidelines and produce good results, would you stop them?

It’s better to be Agile than not... 

References

http://www.agilemanifesto.org/

https://www.linkedin.com/pulse/agile-dead-matthew-kern

https://en.wikipedia.org/wiki/Agile_software_development

http://agilemethodology.org/

http://lucarelandini.blogspot.it/2016/02/become-cloud-provider-in-3-months.html

Governance in the hybrid cloud

This post shows how a company can solve one of the main issue that CIOs have today: the so called Shadow IT.

This term defines the usage of cloud services (either IaaS, PaaS, SaaS) in a project without any control, decided by the application developers or designers because they think it's beneficial for the agility of the project.

Sometimes leveraging available services is really good for a project: it's useless to rebuild something that is easily available as a standardized service. Even when the IT organization of your company (or your customer, if you're a consulting company) provides the building blocks that you need for your architecture, it could be difficult to get approvals or a fast enough provisioning.
So there are different valid reasons to incorporate public cloud services, we can't blame those that try to fully exploit a Service Oriented Architecture.

Unfortunately this way of assembling applications using any available resource you consider useful creates troubles for the IT organization.
Besides additional costs, that arrive as a surprise (developers bill to a personal credit card or to a corporate one, but sooner or later those costs will be factored into the cost of the project), some corporate rules could be violated without even being aware.
Just a few examples: storing reserved data in a database outside the company's datacenter, or invoking services without encrypting the input/output parameters, not granting the end to end High Availability or Disaster Recovery of the entire system.

The subject of costs can be easily underestimated: at development time you need very limited cloud resources, for a limited time. It costs near to zero, before the application goes to a full production environment. But after that, it will need more computing power and more storage, and of course more bandwidth, to serve all the users. Cloud services tend to increase surprisingly in these conditions.

So the CIO has a dilemma: to try to block, or limit, the usage of cloud services - limiting cost and risk but appearing like the one that slows the innovation down and prevents the lines of business from achieving their business result - or to allow maximum freedom, with the additional risk of becoming not relevant because they can bypass the IT organization?

There is a solution in the middle: IT could offer a facilitated access to cloud services, adding them to a Service Catalog where users can self serve, granting compliance by design.
Public cloud services will be selected based on agreed architectural and security policies, they will be documented, audited and reported, eventually subject to approval from a financial standpoint.

One possible implementation of such a catalog can be based on the Cisco ONE Enterprise Cloud Suite, as I did in a recent project at one of my customers.

The Cisco ECS is a reference architecture comprising one flexible Service Catalog, a automation engine and a platform for hybrid cloud that allows the extension of your datacenter into a kind of "bubble" in the public cloud. In case you need additional power, you can burst your workloads into the virtual private datacenter keeping all the security and networking policies you defined in your private cloud: even the IP address of the virtual machines does not change, as long as the secure segmentation of the application layers and any other policy.

I'm not going to describe the Cisco ECS, because you can find the official documentation here.
I'm showing how we extended the services offered in this catalog with CliQr Cloud Center for managing the provisioning and the lifecycle management for applications in the cloud. So the great capabilities of Cisco ECS in term of IaaS are complemented with the offer of the deployments of simple or complex applications and software stacks, that you can target at any cloud just selecting from a drop down list.

I mean that the template for the deployment is not cloud dependent,  and the user can - within the limits of his authorization level and the corporate policies - choose to provision it in the private cloud (e.g. on vmware in the corporate data center) or in the public cloud (e.g. AWS or Azure).
The lifecycle operations (start, stop, resume, delete, etc.) will be also offered as well as the migration to a different cloud: from private to public after the QA test is done and you're ready for production, from a public provider to a more convenient one, etc.

THIS POST HAS BEEN REDACTED

After the publication of this post Cisco announced the intent to acquire Cliqr (not because of the post :-) ), and our policies require that we don't speak of deals while they are in progress. I can't show the way we integrated Cliqr in this project because the official statement on the reference architecture will be communicated by Cisco after the acquisition is eventually completed.

References:
http://blogs.cisco.com/datacenter/introducing-cisco-one-enterprise-cloud-suite
http://www.cliqr.com/

A powerful DevOps tool: Ansible

Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications— automate in a language that approaches plain English, using SSH, with no agents to install on remote systems.

http://ansible.com/

At the Openstack Summit in Vancouver I attended a great session presented by two Cisco colleagues:

Juergen Brendel (@brendelconsult), David Lapsey (@devlaps) both from Cisco Metacloud.

These are my notes, that you could find useful as a easy introduction.

But I suggest you to watch the recording of their session at the end of this post, because it is very educational.

Configuration Management tools

They are better than scripts, that in turn are better than written manual instructions, that are better than a seasoned administrator's memory.

CM tools describe the desired state of a resource (i.e. a server) via assertions (ensure that… exists/installed/...): a declarative way to provision resources.
Comparison of existing tools:

puppet dates 2005, chef dates 2009 - they are powerful and rich

salt dates 2011, ansible dates 2012 - they are easy and quick

Ansible

It's written in Python, uses YAML to create Playbooks (description of the desired state)

It's simple: no central server to maintain, no keys management, NO AGENT on the managed servers - but requires ssh and python on the target server (powershell support is coming).

Ansible executes commands in explicit order (so there are no race conditions due to dependencies).

Modules

Modules are pieces of code that do a single thing.

There are hundreds of modules available to reuse.

They’re copied to the target server at runtime, executed there (they return results) and then deleted.

Inventory file

It defines hosts and groups them so that you can apply same commands to all at once.

Adhoc commands apply to groups - example: ansible -i hosts europe -a “uname -a", where europe is a group.

Playbooks

they are written in YAML and tell Ansible what to do (a sequence of tasks)

Projects layout

A Ansible project is made of:
config files

inventory files

group variables

yaml file

Roles

contains tasks, handlers, templates, files, vars

apply to servers (that have the same role)

can be included in playbooks

Usage of API

to manage infrastructure and services

there are modules available for public cloud and private cloud management systems

Vagrant

Vagrant is a tool that matches Ansible very well:
it is used to create VM in cloud

it can use Ansible as a provisioner

written in Ruby

commands:

vagrant up - creates the vm

vagrant provision - calls Ansible

Takeaways

A single Ansible playbook can be used to deploy apps locally and in the cloud

Download Ansible for free from Github.

DevOps - Tools and Technology

This post is the continuation of the DevOps - Operational model post in this blog.

We have seen how DevOps processes and organization can help the agility of IT, enabling a huge value for the business.

Let’s investigate the tools that smart organizations use to implement DevOps in the real world.

And let’s try to understand how, in addition to code management, the lifecycle of a sw application can be optimized by managing the infrastructure as code.

At the end of the day, we want to apply the following picture to the infrastructure as well.

 

Usually different environments are created to run application, often cloned for each Tenant (customer, project...): development, integration test, QA test, production, Disaster Recovery

The infrastructure must provide similar topology and functions, with different scale and HA requirements.

Those environments are sometimes used for few days, then they are no longer needed and the resources could be reused for next project.

If we were able to generate a new environment "end to end" when it is required, and to release all the resources to a shared pool, this  would help a lot in the optimization of resources usage.

The economy of scale provided by shared infrastructure and resource pools will add to the simplicity and speed of the operations.

The following picture shows the cycle of the builds (for both the sw application and the infrastructure) that optimizes the time and the resources.

From http://www.rightscale.com/blog/cloud-management-best-practices/continuous-integration-and-delivery-cloud-how-rightscale-does-it:

There are a number of tools and solutions that can help automating this process.

Some apply to specific phases, other to the end to end DevOps.

You can find a good list at http://en.wikipedia.org/wiki/Comparison_of_open-source_configuration_management_software

Also collaboration tools help the team(s) to work together for their own and the entire company's benefit: from http://www.collab.net/solutions/devops

The most used DevOps tools, as far as I know from direct experience and investigation, are jenkins, vagrant, puppet, chef.

Here is another possible chain of tools that cover the entire process:

From http://pages.cloudbees.com/rs/cloudbees/images/Continuous-Delivery-Infographic.pdf

Stateless Infrastructure (also known as SDDC)

We understood that the maximum benefit comes from being able to create and destroy environment on demand, allocate resources just when needed (we can also consider Disaster Recovery as a important use case in this scenario, but in that case you should also ensure that data have been replicated before the event).

Infrastructure as code is a core capability of DevOps that allows organizations to manage the scale and the speed with which environments need to be provisioned and configured to enable continuous delivery.

Evolving around the notion of infrastructure as code is the notion of software-defined environments.

Whereas infrastructure as code deals with capturing node definitions and configurations as code, software-defined environments use technologies that define entire systems made up of multiple nodes — not just their configurations, but also their definitions, topologies, roles, relationships, workloads and workload policies, and behavior.

Stateless Computing and Stateless Networking are important innovations that some vendors (Cisco could be considered a leader here) brought to the market in last 5 years.

Policy based configuration and the availability of software controllers for all the components of the architecture allow the separation of the modeling from the physical topology.

Servers

As an example, UCS servers (up to 160 in one management domain, but domains can be joined to share resources and policies) are stateless.

You can imagine each server (either a blade or a rack-mount server) as a dumb piece of iron, before you push its identity, its features (e.g. number, type and configuration of the network interfaces) and its behavior as a piece of configuration.

It is like adding the soul to a body.

Later you can move the same soul to a different body (maybe more powerful, such as from a 2-CPU server to a 4-CPU one). The new machine will be restarted as if it was the same.

This can be useful to recover a faulty server, to do DR but also to repurpose a server farm in few minutes (and eventually restore the previous state the day after).

The state (identity, features and behavior) is defined by a XML document that can be stored, versioned and managed as code in a repository (other than in the embedded UCS Manager).

This abstraction of the server from the actual machine makes the management easier and was the main factor for the incredible success of UCS as a server platform.

Networks

Similarly, in the networking domain, we have had a quantum leap in network management with Cisco ACI (Application Centric Infrastructure).

For those that have not met ACI yet, I have published a “ACI for Dummies” post.

In few words, ACI brings the management of physical and virtual networks together.

It has a very performant and scalable fabric, made of spine and leaf switches, that are managed by a software controller called APIC.

APIC also integrates the virtual switches in the different hypervisors, so that its policy model can be extended to the virtual end points.

A GUI is provided to manage APIC, but essentially you would drive it through the excellent open API offered to orchestration systems and - of course - DevOps tools.

XML (or JSON) artifacts can be stored in a repository as code, and pushing them to APIC will create your new Data Center on the fly.

You can create new Tenants with dedicated resources, or deploy the infrastructure for a new application in such a way that it is isolated (in terms of security, performances and stability) from others, though running on a shared infrastructure.

It would take just the time of a REST call, where you push the new policy to the controller.

And of course you could use the same templates in the different environments: development, integration test, QA test, production, Disaster Recovery

The previous generation of network devices (e.g. the Nexus family) can be managed in a DevOps scenario as well.

They offer API and have puppet agents onboard. And a version of the APIC controller has been created also for networks outside ACI (APIC-EM - https://developer.cisco.com/site/apic-em/discover/overview/).

The Cisco DevNet community prodives a lot of information and samples at https://developer.cisco.com/site/devnet/home/index.gsp

I wrote a short post on Ansible here: http://lucarelandini.blogspot.com/2015/05/a-powerful-devops-tool-ansible.html where a great recorded session from the Openstack Summit is linked.

You might be interested also in my post on DevOps, Docker and Cisco ACI.