March 27, 2018

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
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.

analytics tools add value to the application telemetry
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.

AppDynamics and Tetration integration with CloudCenter
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
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
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
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:

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
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
installing and configuring Tetration agents

application VM with all the agents installed
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:


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. 


Previous post on the integration of CloudCenter with Tetration:

October 23, 2017

Turn the lights on in your automated applications deployment - part 2

In the previous post we described the benefit of using Application Automation in conjunction with Network Analytics in the Data Centre, a Public Cloud or both. We described two solutions from Cisco that offer great value individually, and we also explained how they can multiply their power when used together in an integrated way.
This post describes a lab activity that we implemented to demonstrate the integration of Cisco Tetration (network analytics) with Cisco CloudCenter (application deployment and cloud brokerage), creating a solution that combines deep insight into the application architecture and into the network flows.
The Application Profile managed by CloudCenter is the blueprint that defines the automated deployment of a software application in the cloud (public and private). We add information in the Application Profile to automate the configuration of the Tetration Analytics components during the deployment of the application.

Deploy a new (or update an existing) Application Profile with Tetration support enabled

Intent of the lab:
To modify an existing Application Profile or model a new one so that Tetration is automatically configured to collect telemetry, leveraging also the automated installation of sensors.
A Tetration Injector service is added to the application tiers to create a scope, define dedicated sensor profiles and intents, and automatically generate an application workspace to render the Application Dependency Mapping for each deployed application.
Step 1 – Edit an existing Application Profile
Cisco CloudCenter editor and the Tetration Injector service

Step 2 – Drag the Tetration Injector service into the Topology Modeler 

Cisco CloudCenter editor

Step 3 – Automate the deployment of the app: select a Tetration sensor type to be added
Tetration sensors can be of two types: Deep Visibility and Deep Visibility with Policy Enforcement. The Tetration Injector service allows you to select the type you want to deploy for this application. The deployment name will be reflected in the Tetration scope and application name.

Defining the Tetration sensor to be deployed

Two types of Tetration sensors

In addition to deploying the sensors, the Tetration injector configures the target Tetration cluster and logs all configuration actions leveraging the CloudCenter centralized logging capabilities.
The activity is executed by the CCO (CloudCenter Orchestrator):
CloudCenter Orchestrator

Step 4 – New resources created on the Tetration cluster
After the user has deployed the application from the CloudCenter self-service catalog, you can go to the Tetration user interface and verify that everything has been created to identify the packet flow that will come from the new application:
Tetration configuration

In addition, the software sensors (also called Agents) are recognized by the Tetration cluster:

Tetration agents

Tetration agents settings

Tetration Analytics – Application Dependency Mapping

An application workspace has been created automatically for the deployed application, through the Tetration API: it shows the communication among all the endpoints and the processes in the operating system that generate and receive the network flows.
The following interactive maps are generated as soon as the network packets, captured by the sensors when the application is used, are processed in the Tetration cluster.
The Cisco Tetration Analytics machine learning algorithms grouped the applications based on distinctive processes and flows.
The figure below shows how the distinctive process view looks like for the web tier:
Tetration Application Dependency Mapping

The distinctive process view for the database tier: 

Tetration Application Dependency Mapping

Flow search on the deployed application:  

Detail of a specific flow from the Web tier to the DB tier: 

 Tetration deep dive on network flow

Terminate the application: De-provisioning
When you de-provision the software application as part of the lifecycle managed by CloudCenter (with one click), the following cleanup actions will be managed by the orchestrator automatically:
  • Turn off and delete VMs in the cloud, including the software sensors
  • Delete the application information in Tetration
  • Clear all configuration items and scopes


The combined use of automation (deploying both the applications and the sensors and configuring the context in the analytics platform) as well as the telemetry data that are processed by Tetration help in building a security model based on zero-trust policies.
The following use cases enable a powerful solution thanks to the integrated deployment:
  • Get communication visibility across different application components
  • Implement consistent network segmentation
  • Migrate applications across data center infrastructure
  • Unify systems after mergers and acquisitions
  • Move applications to cloud-based services
Automation limits the manual tasks of configuring, collecting data, analyzing and investigating. It makes security more pervasive, predictive and even improves your reaction capability if a problem is detected.
Both platforms are constantly evolving and the RESTful API approach enables extreme customization in order to accommodate your business needs and implement features as they get released.
The upcoming Cisco Tetration Analytics release – 2.1.1 – will bring new data ingestion modes like ERSPAN, Netflow and neighborhood graphs to validate and assure policy intent on software sensors.
You can learn more from the sources linked in this post, but feel free to add your comments here or contact us to get a direct support if you want to evaluate how this solution applies to your business and technical requirements.


This post is co-authored with a colleague of mine, Riccardo Tortorici.
He is the real geek and he created the excellent lab for the integration that we describe here, I just took notes from his work.



October 20, 2017

Turn the lights on in your automated applications deployment - part 1

A very common goal for software designers and security administrators is to get to a Secure Zero-Trust model in an Application-Centric world.
They absolutely need to avoid malicious or accidental outages, data leaks and performance degradation. However this can be very difficult to achieve sometimes, due to the complexity of distributed architectures and the coexistence of many different software applications in the modern shared IT environment.
Two very important steps in the right direction can be Visibility and Automation. In this blog, we will see how the combination of two Cisco software solutions can contribute towards achieving this goal.
This is the description of a lab activity, that we implemented to show the advantage from the integration of Cisco Tetration Analytics (providing network analytics) with Cisco CloudCenter (application deployment and cloud brokerage), creating a really powerful solution that combines deep insight into the application architecture and into the network flows.

Telemetry from the Data Center

Tetration provides telemetry data for your applications

Cisco Tetration Analytics captures telemetry from every packet and every flow, delivers pervasive real-time and historical visibility across your data center, providing a deep understanding of application dependencies and interactions. You can learn more here:
Main use cases for Tetration are:
  • Pervasive Visibility
  • Security
  • Forensics/Troubleshooting, Single Source of Truth
The architecture of Tetration Analytics is made of a big data analytics cluster and two types of sensors: hardware and software based. Sensors can be either in the switches (hw) or in the servers (sw).
Data is collected, stored and processed through a high performance customized Hadoop cluster, which represents the very inner core of the architecture. The software sensors will collect the metadata information from each packet’s header as they leave or enter the hosts. In addition, they will also collect process information, such as the user ID associated with the process and OS characteristics.

Tetration high level architecture
Tetration high level architecture

Tetration can be deployed today in the Data Center or in the cloud (AWS). The choice of the best placement depends on whether you have more deployments on cloud or on premises.
Thanks to the knowledge obtained from the data, you can create zero-trust policies based on white lists and enforce them across every physical and virtual environment. By observing the communication among all the endpoints, you can define exactly who is allowed to contact who (white list, where everything else is denied by default). This applies to both Virtual Machines and Physical Servers (bare metal), including your applications running in the public cloud.
As an example, one of your database servers will be only accessed by the application servers running the business logic for that specific application, by the monitoring and backup tools and no one else. These policies can be enforced by Tetration itself or exported to generate policies in an existing environment (e.g. Cisco ACI).

Behavior analysis of workloads deployed everywhere
Behavior analysis of workloads deployed everywhere

Another benefit of the network telemetry is that you have visibility on any packet, any flow at any time (you can keep up to 2 years of historical data, depending on your Tetration deployment and DC architecture) among two or more application tiers. You can detect performance degradation, ie increasing latency between two application tiers and see the overall status of any complex application.

How to onboard applications in Tetration Analytics
When you start collecting information from the network and the servers into the analytics cluster, you need to give it a context. Every flow needs to be associated to applications, tenants, etc. so that you can give it business significance.
This can be done through the user interface or through the API of the Tetration cluster, matching metadata that come associated with the packet flow. Based on this context, reports and drill down inspection will give you an insight on every breath that the system does.

Automation makes Deployment of Software Applications secure and compliant

The lifecycle of Software Applications generally impacts different organizations in the IT, spreading responsibility and making it hard to ensure quality (including security) and end-to-end visibility.
This is where Cisco Cloud Center comes in. It is a solution for two main use cases:
  • modeling the automated deployment of a software stack (creating a template or blueprint for deployments)
  • brokering cloud services for your applications (different resource pools offered from a single self-service catalog). You can consume IaaS and PaaS services from any private and public cloud, with a portable automation that frees you from lock-in to a specific cloud provider.
Cisco CloudCenter: one solution for all clouds
Cisco CloudCenter: one solution for all clouds

Integration of Automated Deployment and Network Analytics

It is important to note that both platforms are very open and come with a significant support for integration API. The joint usage means benefitting from the visibility and the automation capabilities of each product:
  • Application architecture awareness (the blueprint for the deployment is created by the software architect)
  • Operating System visibility (version, patches, modules and monitoring)
  • Automation of all configuration actions, both local (in the server) and external (in the cloud environment)
Tetration Analytics
  • Application Dependency Mapping, driven by the observation of all communication flows
  • Awareness of Network nodes behavior, including defined policies and deviations from the baseline
  • Not just sampling, but storing and processing anytime metadata for any single packet in the Data Center

The table below shows how each engine provides additional value to the other one:
Leveraging the integration between the two solutions allows a feedback loop between applications design and operations, providing compliance, continuous improvement and delivery of quality services to the business.

Consequently, all the following Tetration Analytics use cases are made easier if all the setup is automated by CloudCenter, with the advantage of being cloud agnostic:
Cisco Tetration use cases
Cisco Tetration use cases

Of course one of the most tangible results claimed by this end-to-end visibility and policy enforcement is security.
More detail on the integration between CloudCenter and Tetration Analytics are described in the second part of this post, where we will demonstrate how easy it is to automate the deployment of software sensors along with the application, as well as preparing the analytics cluster to welcome the telemetry data.


This post is co-authored with a colleague of mine, Riccardo Tortorici.
He is the real geek and he created the excellent lab for the integration that we describe here, I just took notes from his work.