Showing posts with label data center. Show all posts
Showing posts with label data center. Show all posts

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 



May 10, 2016

A simpler framework for hybrid cloud

Hybrid cloud is one of top mind projects for most IT managers, and there's little content that one can add to be original   ;-)

The hype and the attempt of many vendors (including... Cisco) to provide relevant solutions have populated the space of an incredible number of offers that make it hard to distinguish what works, what's manageable and cost effective, from what is only marketecture.




Recently Cisco decided to invest even more on cloud and, with the advent of a new CTO and some acquisitions, a revision of our approach to hybrid cloud made it easier and more effective. This post is not from official marketing and is not echoing company's direction: it's my attempt to rationalize my understanding of the new framework and to solicit your comments and feedback, so that I can leverage it when I discuss with my customers and partners.
The following picture represents the area where Cisco plays a role, offering hardware and software solutions.
When it comes to the software stack to manage the infrastructure and provide services to the users, we have a mix of Cisco products, open source solutions and integration with 3rd parties. The objective is to offer a set of pre-validated stacks that can match the different needs, granting a deterministic result.



I shared some thoughts with a group of colleagues because we're planning educational activities for our field people: instead of just providing a reference architecture (that would end being a list of products to be forced in every deal) we tried to represent the functions in the system as components of a framework, from which we'll pull the specific architecture for a given project. This, used cum grano salis, should help to be pragmatic and realize quick wins (for both the customers - think of Fast IT initiatives - and of course for Cisco).

As a result, next picture is separating the different functional layers so that they can be explained to sales guys and to customers.
It could also help to manage the possible overlap with alternative solutions that customers may choose – or already have – because every element is replaceable in the picture, based on the open API they expose/consume (as well as any well designed 3rd party product).

It is important to note that the top two layers in the picture are optional, since not all customers need those functions in their system. Based on the level of Governance that they want to have, the existing processes and the way they develop business applications (or use commercial software that only need a resource pool to be deployed), the entry point could be directly at the third layer (Multi-Cloud Management) and ITSM and PaaS would be removed.




So, while we explain all the possibilities as said above, we need to make them feel confident that it’s doable and not overly complex.
In that regard, my motto is that “cloud is not a product (or a set of), it’s a project and it’s complex in nature… regardless the products set you choose”. Generally the cost of hardware and software products is lower than development and consulting services, and customers know it.
If we can claim that a pre-built integration makes the project easier (and we can), I would stress the value of reducing the project risk and delivering outcomes faster rather than a cheaper implementation.

Selling licenses can be (almost) easy, but driving adoption with business outcomes for customers is different. Finally Cisco has built a practice that can deliver IT projects effectively and recruited partners that do the same: customers have different options to choose from.

Now, in the context of a end to end strategy defined with the customer, we can deliver projects based on agile methodologies (e.g. Scrum) and implement the architecture layers with a bottom up approach: from a strong capability to automate the Data Center (and the hybrid cloud) you can create services that are surfaced up to the consumption layers, including a self service catalog.


Software Defined What?

The bottom up approach stresses the value of the API exposed by UCS and ACI (with the further evolution from basic programmability to policy-based management, that I'm not mentioning yet - look out for next post). With the power and the granularity of those API, you can really realize a fully Software Defined Data Center (SDDC): servers and networks can be shaped via software interfaces.
By the way, I take the opportunity here to clarify that Software Defined Data Center does not mean Software Implemented Data Center: you don't necessarily need a software overlay that mimics the behavior of the hardware (living as a separate entity), you need software controllers that drive the shape and the behavior of both physical and virtual resources in the DC as a single system.
Better if they do that based on policies... like the Cisco architecture does  :-)
You will see a post dedicated to policies and application intent soon on this blog.



Competition?

We also recognize that many customers have already an ITSM solution in place, or any other form of governance. So we don't engage in competitive fights, like imposing Cisco Prime Service Catalog vs Service Now, but we rather integrate our solution with the existing components: this is a sort of compromise with a competitor that hurts my pride, but since it's for our customers' benefit... it's a good solution.

Cisco Cloud Center as a broker: the recent acquisition of Cliqr brings a great solution to Cisco to address the multi-cloud management use cases, the most important ones for the majority of customers. In the logical schema above you can see that the hybrid cloud scenario has been qualified better as Multi-Cloud management.
This reflects the fact that having a application deployed partly in your Data Center and partly in the public cloud is still a relevant use case, but many companies are more attracted by other scenarios... like moving from one project stage to next (e.g. Dev-Test-QA-Prod) using different resource pools (on premise or in cloud), or moving their assets from one cloud provider to a different one.


Cloud Brokering and Multi Cloud Management

In the first one (promotion to next stage) it could be useful to leverage resources that are allocated based on business convenience (e.g. cost or flexibility) or compliance (e.g. data sovereignty), so the application and all the needed infrastructure are moved back and forth to the public cloud.
In the second the driver could be a dual provider strategy, or maybe a change in the market conditions that makes one provider more appealing than the current one, or a strategic switch from private cloud to public (or vice versa).


In all these cases, we offer a solution to deploy a software stack (a complete custom application, a development platform, or a commercial software product) as a self service option, where the target can be selected dynamically from a list of available clouds.
You can deploy to your local private cloud, based on vmware or any other virtualization solution, or to a Openstack based cloud, or to any of the public cloud providers if you have an account there.
Any resource pool is a possible destination for the deployment (and the life cycle management, including autoscale or retirement of the application).
The model of the deployment of the application is completely de-coupled from the selection of the target, thanks to the capabilities of the orchestrator that can configure the needed resources in almost any cloud transparently.
It uses the API exposed by the element managers of a multi vendor infrastructure on premise (e.g. vcenter, UCS Manager, the ACI controller, etc.) and those exposed by public clouds like AWS, Azure, etc.



From a logical schema to a real deployment

So we can offer users a different entry point, based on their business needs (they might need a ticketing system, or a self service catalog, a PaaS solution or directly the web portal of the multi cloud manager to model deployments and deliver them).
The customer can have one or more resource pools, allocated wherever he likes (local or in cloud), and let the broker direct the selection of the target based on predefined policies.

The schema in next picture presents different products at every layer: a solution can be based on one of them, or a combination. We have the flexibility to match the specific needs with products from Cisco, from 3rd party vendors or open source.
As an example, MANTL is a new open source project that makes the development of microservices easier if you build cloud native applications.




I will expand the detail of the single products and the open source solutions shown in this picture in my next post.
Stay tuned...


References

http://www.cisco.com/c/en/us/solutions/executive-perspectives/fast_it.html
http://www.cisco.com/web/solutions/trends/futureofit/why-cisco.html
http://MANTL.io
http://Github.com/CiscoCloud/microservices-infrastucture 
http://lucarelandini.blogspot.it/2015/10/devops-docker-and-cisco-aci-part-1.html
http://lucarelandini.blogspot.it/2015/03/aci-for-dummies.html
http://lucarelandini.blogspot.it/2015/09/the-phoenix-project-how-devops-can.html




February 23, 2016

Become a cloud provider in 3 months

This is the story of a company that decided to become a Cloud Service Provider.
They were already a successful IT outsourcer in the financial industry, with many customers' environments running in their data center.
Outsourcing was a healthy business but they started having some challenges, due to slow and inefficient provisioning processes and operations.
Any new request from a customer started a new project, so their customers started exploring public cloud services to get more flexibility and speed.
For this reason, the company decided to adopt the cloud delivery model and to offer their customers a self service catalog.



Of course a cloud project cannot be done in one night, so they were cautious in their approach.
Both technology and operational processes needed to be proven before embarking in such a challenge, but the traditional waterfall methodology made the expected return appear uncertain and distant.
To make things worse, they had tried to implement a PaaS project with a different vendor and they had spent a lot of money without tangible return.

I was engaged to support the evaluation of a new IaaS catalog that could evolve to PaaS and to self service applications management.
I made sure that the Business and IT strategy were in sync and I proposed to start with small steps to validate the approach. I also invited them to qualify the quick wins that they would expect to justify the investment and show the stakeholders an immediate return, so that the project lived enough to reach the expected success.
As you know well, many projects last too much and die before showing any business return.

We analyzed the current situation and defined a future vision. This was the driver for a gap analysis and for the prioritization of user stories, that we decided to implement in short iterations (sprints of 2 weeks, according to the Agile Scrum methodology).
Their data center was mainly based on Cisco networks and servers, but this was not the main reason for selecting the Cisco software stack for the cloud project.
After the initial workshops, some product demo and talks about other projects they understood that our people - and our partner company that implemented the project with them - were experienced enough to plan the project seriously and to chase the quick wins that we all considered so important.

The Cloud Management Platform chosen for the project was the Cisco ONE Enterprise Cloud Suite (aka ECS).



One of the most important features considered in the decision was the possibility to create flexible templates, later exposed as self service options in the end user catalog, for the deployment of complex applications. A set of servers with different roles, and all the networks needed to make them work, can be provisioned as a dedicated and virtually separated environment (multi tenancy in a shared infrastructure that offers economy of scale).

As an example, the following picture shows a environment that could be ordered - fully configured - with a single click. It is based on a component of the ECS architecture that is named VACS (virtual application cloud segmentation):


It was easy to engage the SME (subject matter experts) for the servers, the network, the storage and the virtualization in the customer organization and to ask them to define the basic policies that we would use as building blocks for all the services to be offered.
This model-based implementation is quicker to build and easier to maintain, and it can be exposed to the end users in a way that they understand and trust soon.

The automation that we built was considered useful by the SME (after winning their initial suspicion, because every good craftsman loves manual work) because it set them free from the manual operations that previously made their work tedious and error prone.
Delegating the configuration to an automated service gave their customers a faster service and a higher quality (no rework needed because of manual errors or missing information).


One more component in the architecture is the Stack Designer.
It is a tool provided by the Cisco ECS to create templates for application provisioning. It takes IaaS templates - made in the infrastructure management layer, that in our case is UCSD, to deploy a topology of servers and networks - and layers the software stack on top of them.


You can decide what software products (or custom applications) must be installed - and configured based on the input parameters provided by the end user - including monitoring agents and backup agents, and save this new template in the repository.
The integration with Puppet, an open source solution used to provision software applications, is leveraged to install and configure the entire software stack from the images in the repository.


The new template can now be offered as a self service option in the catalog, so that the end users don't need to install and configure the software stack themselves. A end-to-end solution is provided, up and running and ready to be used.
All the components of the ECS solution are pre-integrated and this makes the project faster than you would expect. But, since they communicate through standard protocols and open API, every component of the architecture could be replaced by an alternative product (from a different vendor or from the open source community). You should not be afraid of vendor lock in  :-)

Agile Delivery

In terms of project delivery, the following table shows the different iterations that allowed to complete the delivery in only 3 months.
But the amazing result is that at every sprint (i.e. every 2 weeks) new use cases were available in a usable environment.
The first demo to a real customer (a customer of my customer) was done after 2 months from the start of the project, and the first customer was onboarded after the 5th sprint (i.e. 2.5 months).



Conclusion

This quick win demonstrates that even complex projects like building a public cloud platform can be done in a reasonable amount of time.
The era of endless projects, based on complex technology and measured in function points, has passed forever.
There are simple solutions (like ECS) that make your work easier, but a good organization and the right methodology allow for incremental building and refinement of the solution. Every iteration of the project delivers a usable result in the production environment, and you don't need to wait the completion of the entire project to start using the solution.
If you are a service provider, you can start selling your services soon and produce a ROI.
More services will be added incrementally and the catalog will be richer at every iteration.


References

Cisco Enterprise Cloud Suite
and its individual components:
- Cisco PSC - Prime Service Catalog 
- Cisco UCSD - UCS Director
- Cisco VACS - Virtual Application Cloud Segmentation

Fast IT
Cisco Prime Service Catalog in action: Cisco eStore

Scrum (agile development) 







April 21, 2015

ACI for (Smarter) Simple Minds


In a previous post I tried to describe the new Cisco ACI architecture in simple terms, from a software designer standpoint.
My knowledge on networking is limited, compared to my colleagues at Cisco that hold CCIE certifications… I am a software guy the just understands the API   ;-)
Though, now I would like to share some more technical information with the same “not for specialists” language.
You can still go to the official documentation for the detail, or look at one of the brilliant demo recorded on YouTube.

These are the main points that I want to describe:
- You don’t program the single switches, but the entire fabric (via the sw controller)
- The fabric has all active links (no spanning tree)
- Policies and performances benefit from a ASIC design that perfectly fits the SDN model
- You can manage the infrastructure as code (hence, really do DevOps)
- The APIC controller manages also L4-7 network services from 3rd parties
- Any orchestrator can drive the API of the controller
- The virtual leaf of the fabric extends into the hypervisor (AVS)
- You get immediate visibility of the Health Score for the Fabric, Tenants, Applications

Next picture shows how the fabric is build, using two types of switches: the Spines are used to scale and connect all the leaves in a non blocking fabric that ensures performances and reliability.
The Leaf switches hold the physical ports where servers are attached: both bare metal servers (i.e. running a Operating System) and virtualized servers (i.e. running ESXi, Hyper-V and KVM hypervisors).
The software controller for the fabric, named APIC, runs on a cluster of (at least) 3 dedicated physical servers and is not in the data path: so it does not affect performances and reliability of the fabric, as it could happen with other solutions on the market.

The ACI fabric supports more than 64,000 dedicated tenant networks. A single fabric can support more than one million IPv4/IPv6 endpoints, more than 64,000 tenants, and more than 200,000 10G ports. The ACI fabric enables any service (physical or virtual) anywhere with no need for additional software or hardware gateways to connect between the physical and virtual services and normalizes encapsulations for Virtual Extensible Local Area Network (VXLAN) / VLAN / Network Virtualization using Generic Routing Encapsulation (NVGRE).

The ACI fabric decouples the endpoint identity and associated policy from the underlying forwarding graph. It provides a distributed Layer 3 gateway that ensures optimal Layer 3 and Layer 2 forwarding. The fabric supports standard bridging and routing semantics without standard location constraints (any IP address anywhere), and removes flooding requirements for the IP control plane Address Resolution Protocol (ARP) / Generic Attribute Registration Protocol (GARP). All traffic within the fabric is encapsulated within VXLAN.

The ACI fabric decouples the tenant endpoint address, its identifier, from the location of the endpoint that is defined by its locator or VXLAN tunnel endpoint (VTEP) address. The following figure shows decoupled identity and location.


Forwarding within the fabric is between VTEPs. The mapping of the internal tenant MAC or IP address to a location is performed by the VTEP using a distributed mapping database. After a lookup is done, the VTEP sends the original data packet encapsulated in VXLAN with the Destination Address (DA) of the VTEP on the destination leaf. The packet is then de-encapsulated on the destination leaf and sent down to the receiving host. With this model, we can have a full mesh, loop-free topology without the need to use the spanning-tree protocol to prevent loops.

You can attach virtual servers or physical servers that use any network virtualization protocol to the Leaf ports, then design the policies that define the traffic flow among them regardless the local (to the server or to its hypervisor) encapsulation.
So the fabric acts as a normalizer for the encapsulation and allows you to match different environments in a single policy.

Forwarding is not limited to nor constrained by the encapsulation type or encapsulation-specific ‘overlay’ network:





As explained in ACI for Dummies, policies are based on the concept of EPG (End Points Group).
Special EPG represent the outside network (outside the fabric, that means other networks in your datacenter or eventually the Internet or a MPLS connection):



The integration with the hypervisors is made through a bidirectional connection between the APIC controller and the element manager of the virtualization platform (vCenter, System Center VMM, Red Hat EVM...). Their API are used to create local virtual networks that are connected and integrated with the ACI fabric, so that policies are propagated to them.
The ultimate result is the creation of Port Groups, or the like of, where VM can be connected.
A Port Groups represents a EPG.
Events generated by the VM lifecycle (power on/off, vmotion...) will be sent back to APIC so that the traffic is managed accordingly.



How Policies are enforced in the fabric

The policy contains a source EPG, a destination EPG and rules known as Contracts, made of Subjects (security, QoS...). They are created in the Controller and pushed to all the leaf switches where they are enforced.
When a packet arrives to a leaf, if the destination EPG is known it is processed locally.
Otherwise it is forwarded to a Spine, to reach the destination EPG through a Leaf that knows it.

There are 3 cases, and the local and global tables in the leaf are used based on the fact that the destination EP is known or not:
1 - If the target EP is known and it's local (local table) to the same leaf, it's processed locally (no traffic through the Spine).
2 - If the target EP is known and it's remote (global table) it's forwarded to the Spine to be sent to the destination VTEP, that is known.
3 - If the target EP is unknown the traffic is sent to the Spine for a proxy forwarding (that means that the Spine discovers what is the destination VTEP).



You can manage the infrastructure as code.

The fabric is stateless: this means that all the configuration/behavior can be pushed to the network through the controller's API. The definition of Contracts and EPG, of POD and Tenants, every Application Profile is a (set of) XML document that can be saved as text.
Hence you can save it in the same repository as the source code of your software applications.

You can extend the DevOps pipeline that builds the application, deploys it and tests it automatically by adding a build of the required infrastructure on demand.
This means that you can use a slice of a shared infrastructure to create a environment just when it's needed and destroy it soon after, returning the resources to the pool.

You can also use this approach for Disaster Recovery, simply building a clone of the main DC if it's lost.

Any orchestrator can drive the API of the controller.

The XML (or JSON) content that you send to build the environment and the policies is based on a standard language. The API are well documented and lot of samples are available.
You can practice with the API, learn how to use them with any REST client and then copy the same calls into your preferred orchestrator.
Though some products have out of the box native integration with APIC (Cisco UCSD, Microsoft), any other can be used easily with the approach I described above.
See an example in The Elastic Cloud Project.

The APIC controller manages also L4-7 network services from 3rd parties. 

The concept of Service Graph allows a automated and scalable L4-L7 service insertion.  The fabric forwards the traffic into a Service Graph, that can be one or more service nodes pre-defined in a series, based on a routing rule.  Using the service graph simplifies and scales service operation: the following pictures show the difference from a traditional management of the network services.




The same result can be achieved with the insertion of a Service Graph in the contract between two EPG:



The virtual leaf of the fabric extends into the hypervisor (AVS).

Compared to other hypervisor-based virtual switches, AVS provides cross-consistency in features, management, and control through Application Policy Infrastructure Controller (APIC), rather than through hypervisor-specific management stations. As a key component of the overall ACI framework, AVS allows for intelligent policy enforcement and optimal traffic steering for virtual applications.

The AVS offers:
  • Single point of management and control for both physical and virtual workloads and infrastructure
  • Optimal traffic steering to application services
  • Seamless workload mobility
  • Support for all leading hypervisors with a consistent operational model across implementations for simplified operations in heterogeneous data centers



Cisco AVS is compatible with any upstream physical access layer switch that complies with the Ethernet standard, including Cisco Nexus Family switches. Cisco AVS is compatible with any server hardware listed in the VMware Hardware Compatibility List (HCL). Cisco AVS is a distributed virtual switch solution that is fully integrated into the VMware virtual infrastructure, including VMware vCenter for the virtualization administrator. This solution allows the network administrator to configure virtual switches and port groups to establish a consistent data center network policy.

Next picture shows a topology that includes Cisco AVS with Cisco APIC and VMware vCenter with the Cisco Virtual Switch Update Manager (VSUM).





 

Health Score

The APIC uses a policy model to combine data into a health score. Health scores can be aggregated for a variety of areas such as for infrastructure, applications, or services.

The APIC supports the following health score types:
      System—Summarizes the health of the entire network.
      Leaf—Summarizes the health of leaf switches in the network. Leaf health includes hardware health of the switch including fan tray, power supply, and CPU.
      Tenant—Summarizes the health of a tenant and the tenant’s applications.



Health scores allow you to isolate performance issues by drilling down through the network hierarchy to isolate faults to specific managed objects (MOs). You can view network health by viewing the health of an application (by tenant) or by the health of a leaf switch (by pod).



You can subscribe to a health score to receive notifications if the health score crosses a threshold value. You can receive health score events via SNMP, email, syslog, and Cisco Call Home.  This can be particularly useful for integration with 3rd party monitoring tools. 

Health Score Use case: 
An application administrator could subscribe to the health score of their application - and receive automatic notifications from ACI if the health of the specific application is degraded from an infrastructure point of view - truly an application-aware infrastructure.


Conclusion

I hope that these few lines were enough to show the advantage that modern network architectures can bring to your Data Center.
Cisco ACI joins all the benefit of the SDN and the overlay networks with a powerful integration with the hardware fabric, so you get flexibility without losing control, visibility and performances.

One of the most important aspects is the normalization of the encapsulation, so that you can merge different network technologies (from heterogeneous virtual environments and bare metal) into a single well managed policy model.

Policies (specifically, the Application Network Policies created in APIC based on EPG and Contracts) allow a easier communication between software application designers and infrastructure managers, because they are simple to represent, create/maintain and enforce.

Now all you need is just a look at ACI Fundamentals on the Cisco web site.


March 25, 2015

Invoking UCS Director Workflows via the Northbound REST API


This is a guest post, offered by a colleague of mine: Russ Whitear.
Russ is the UCS Director guru  in our team and, when I saw an internal email where he explained how to use the UCS Director API from an external client, I asked his permission to publish it.
I believe it will be useful for many customers and partners to integrate UCSD in a broader ecosystem.

This short post explains how to invoke UCS Director workflows via the northbound REST API. Authentication and role is controlled by the use of a secure token.  Each user account within UCS Director has a unique API token, which can accessed via the GUI like so:

Firstly, from within the UCS Director GUI, click the current username at the top right of the screen. Like so:


User Information will then be presented. Select the ‘Advanced’ tab in order to reveal the API Access token for that user account.








Once retrieved, this token needs to be added as an HTTP header for all REST requests to UCS Director.  The HTTP header name must be X-Cloupia-Request-Key.
X-Cloupia-Request-Key : E0BEA013C6D4418C9E8B03805156E8BB


Once this step is complete, the next requirement is to construct an appropriate URI for the HTTP request in order to invoke the required UCS Director workflow also supplying the required User Inputs (Inputs that would ordinarily be entered by the end user when executing the workflow manually).

UCS Director has two versions of northbound API. Version 1 uses HTTP GET requests with a JSON (Java Standard Object Notation) formatted URI. Version 2 uses HTTP POST with XML (eXtensible Markup Language) bodytext.

Workflow invokation for UCS Director uses Version 1 of the API (JSON). A typical request URL would look similar to this:

http://<UCSD_IP>/app/api/rest?formatType=json
                 &opName=userAPISubmitWorkflowServiceRequest
                 &opData={SOME_JSON_DATA_HERE}

A very quick JSON refresher

JSON formatted data consists of either dictionaries or lists. Dictionaries consist of name/value pairs that are separated by a colon. Name/value pairs are separated by a comman and dictionaries are bounded by curly braces. For example:

{“animal”:”dog”, “mineral”:”rock”, “vegetable”:”carrot”}

Lists are used in instances where a single value is insufficient. Lists are comma separated and bounded by square braces. For example:

{“animals”:[“dog”,”cat”,”horse”]}

To ease readability, it is often worth temporarily expanding the structure to see what is going on. 

{
    “animals”:[
        “dog”,
        ”cat”,
        ”horse”
    ]
}

Now things get interesting. It is possible (And common) for dictionaries to contain lists, and for those lists to contain dictionaries rather than just elements (dog, cat, horse etc…). 

{ “all_things”:{
        “animals”:[
            “dog”,
            ”cat”,
            ”horse”
        ],
        “minerals”:[
            “Quartz”,
            “Calcite”
        ],
        “vegetable”:”carrot”
    }
}


With an understanding of how JSON objects are structured, we can now look at the required formatting of the URI for UCS Director. When invoking a workflow via the REST API, UCS Director must be called with three parameters, param0, param1 and param2. ‘param0’ contains the name of the workflow to be invoked. The syntax of the workflow name must match EXACTLY the name of the actual workflow. ‘param1’ contains a dictionary, which itself contains a list of dictionaries detailing each user input and value that should be inserted for that user input (As though an end user had invoked the workflow via the GUI and had entered values manually.

The structure of the UCS Director JSON URI looks like so:


{
    param0:"<WORKFLOW_NAME>",
    param1:{
                "list":[
                       {“name":"<INPUT_1>","value":"<INPUT_VALUE>"},
                       {"name":"<INPUT_2>","value":"<INPUT_VALUE"}
                ]
            },
    param2:-1
}


So, let’s see this in action. Take the following workflow, which happens to be named ‘Infoblox Register New Host’ and has the user inputs ‘Infoblox IP:’,’Infoblox Username:’,’Infoblox Password:’,’Hostname:’,’Domain:’ and ‘Network Range:’.








The correct JSON object (Shown here in pretty form) would look like so:








Note once more, that the syntax of the input names must match EXACTLY that of the actual workflow inputs.

After removing all of the readability formatting, the full URL required in order to invoke this workflow with the ‘user’ inputs as shown above would look like this:




Now that we have our URL and authentication token HTTP header, we can simply enter this information into a web based REST client (e.g. RESTclient for Firefox or Postman for Chrome) and execute the request. Like so:
 






If the request is successful, then UCS Director will respond with a “serviceError” of null (No error) and the serviceResult will contain the service request ID for the newly invoked workflow:




Progress of the workflow can either be monitored by other API requests or via the UCS Director GUI:




Service request logging can also be monitored via either further API calls or via the UCS Director GUI:




This concludes the example, that you could easily test on your own instance of UCS Director or, if you don't have one at hand, in a demo lab on dcloud.cisco.com.

It should be enough to demonstrate how simple is the integration of the automation engine provided by UCSD, if you want to execute its workflows from an external system: a front end portal, another orchestrator, your custom scripts.

See also The Elastic Cloud project - Porting to UCSD for the deployment of a 3 tier application to 3 different hypervisors, using Openstack and ACI with Cisco UCS Director.