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Understanding Causality and Big Data: Complexities, Challenges, and Tradeoffs

image credit: Wikipedia, Amitchell125

“Does smoking cause cancer?”

We have heard that lot of smokers have lung cancer. However, can we mathematically confirm that smoking causes cancer?

We can look at cancer patients and check how many of them are smoking. We can look at smokers and check will they develop cancer. Let’s assume that answers come up 100%. That is, hypothetically, we can see a 1–1 relationship between smokers and cancer.

Okay: can we claim that smoking causes cancer? Apparently it is not easy to make that claim. Let’s assume that there is a gene that causes cancer and also makes people like to smoke. If that is the cause, we will see the 1–1 relationship between cancer and smoking. In this scenario, cancer is caused by the gene. That means there may be an innocent explanation to 1–1 relationship we saw between cancer and smoking.

This example shows two interesting concepts: correlation and causality from statistics, which play a key role in Data Science and Big Data. Correlation means that we will see two readings behave together (e.g. smoking and cancer) while causality means one is the cause of the other. The key point is that if there is a causality, removing the first will change or remove the second. That is not the case with correlation.

Correlation does not mean Causation!

This difference is critical when deciding how to react to an observation. If there is causality between A and B, then A is responsible. We might decide to punish A in some way or we might decide to control A. However, correlation does warrant such actions.

For example, as described in the post The Blagojevich Upside, the state of Illinois found that having books at home is highly correlated with better test scores even if the kids have not read them. So they decide the distribute books. In retrospect, we can easily find a common cause. Having the book in a home could be an indicator of how studious parents are, which will help with better scores. Sending books home, however, is unlikely to change anything.

You see correlation without a causality when there is a common cause that drives both readings. This is a common theme of the discussion. You can find a detailed discussion on causality from the talk “Challenges in Causality” by Isabelle Guyon.

Can we prove Causality?

Casualty is measured through randomized experiments (a.k.a. randomized trials or AB tests). A randomized experiment selects samples and randomly break them into two groups called the control and variation. Then we apply the cause (e.g. send a book home) to variation group and measure the effects (e.g. test scores). Finally, we measure the casualty by comparing the effect in control and variation groups. This is how medications are tested.

To be precise, if error bars for groups does not overlap for both the groups, then there is a causality. Check https://www.optimizely.com/ab-testing/ for more details.

However, that is not always practical. For example, if you want to prove that smoking causes cancer, you need to first select a population, place them randomly into two groups, make half of the smoke, and make sure other half does not smoke. Then wait for like 50 years and compare.

Did you see the catch? it is not good enough to compare smokers and non-smokers as there may be a common cause like the gene that cause them to do so. Do prove causality, you need to randomly pick people and ask some of them to smoke. Well, that is not ethical. So this experiment can never be done. Actually, this argument has been used before (e.g.https://en.wikipedia.org/wiki/A_Frank_Statement. )

This can get funnier. If you want to prove that greenhouse gasses cause global warming, you need to find another copy of earth, apply greenhouse gasses to one, and wait few hundred years!!

To summarize, Casualty, sometime, might be very hard to prove and you really need to differentiate between correlation and causality.

Following are examples when causality is needed.

  • Before punishing someone
  • Diagnosing a patient
  • Measure effectiveness of a new drug
  • Evaluate the effect of a new policy (e.g. new Tax)
  • To change a behavior

Big Data and Causality

Most big data datasets are observational data collected from the real world. Hence, there is no control group. Therefore, most of the time all you can only show and it is very hard to prove causality.

There are two reactions to this problem.

First, “Big data guys do not understand what they are doing. It is stupid to try to draw conclusions without randomized experiment”.

I find this view lazy.

Obviously, there are lots of interesting knowledge in observational data. If we can find a way to use them, that will let us use these techniques in many more applications. We need to figure out a way to use it and stop complaining. If current statistics does not know how to do it, we need to find a way.

Second is “forget causality! correlation is enough”.

I find this view blind.

Playing ostrich does not make the problem go away. This kind of crude generalizations make people do stupid things and can limit the adoption of Big Data technologies.

We need to find the middle ground!

When do we need Causality?

The answer depends on what are we going to do with the data. For example, if we are going to just recommend a product based on the data, chances are that correlation is enough. However, if we are taking a life changing decision or make a major policy decision, we might need causality.

Let us investigate both types of cases.

Correlation is enough when stakes are low, or we can later verify our decision. Following are few examples.

  1. When stakes are low ( e.g. marketing, recommendations)?—?when showing an advertisement or recommending a product to buy, one has more freedom to make an error.
  2. As a starting point for an investigation?—?correlation is never enough to prove someone is guilty, however, it can show us useful places to start digging.
  3. Sometimes, it is hard to know what things are connected, but easy verify the quality given a choice. For example, if you are trying to match candidates to a job or decide good dating pairs, correlation might be enough. In both these cases, given a pair, there are good way to verify the fit.

There are other cases where causality is crucial. Following are few examples.

  1. Find a cause for disease
  2. Policy decisions ( would 15$ minimum wage be better? would free health care is better?)
  3. When stakes are too high ( Shutting down a company, passing a verdict in court, sending a book to each kid in the state)
  4. When we are acting on the decision ( firing an employee)

Even, in these cases, correlation might be useful to find good experiments that you want to run. You can find factors that are correlated, and design the experiments to test causality, which will reduce the number of experiments you need to do. In the book example, state could have run a experiment by selecting a population and sending the book to half of them and looking at the outcome.

Some cases, you can build your system to inherently run experiments that let you measure causality. Google is famous for A/B testing every small thing, down to the placement of a button and shade of color. When they roll out a new feature, they select a population and roll out the feature for only part of the population and compare the two.

So in any of the cases, correlation is pretty useful. However, the key is to make sure that the decision makers understand the difference when they act on the results.

Closing Remarks

Causality can be a pretty hard thing to prove. Since most big data is observational data, often we can only show the correlation, but not causality. If we mixed up the two, we can end up doing stupid things.

Most important thing is having a clear understanding at the point when we act on the decisions. Sometime, when stakes are low, correlation might be enough. On some other cases, it is best to run a experiment to verify our claims. Finally, some systems might warrant building experiments into system itself, letting you draw strong causality results. Choose wisely!

Twice the Capabilities, Half the Name

Not every Web Application has a corresponding Web API, and not every Web Service has a corresponding Web interface, but we’re seeing steady growth among customers who are building Web Applications and their APIs together.  These APIs are invaluable for leveraging advanced users and integrating with partners, but also are driven by a demand for rich applications such as native iPhone, iPad, and Android applications.

In response to this growing demand, we’ve added an exciting new feature to the WSO2 Carbon family: full support for Apache Tomcat, the leading open source servlet container. We’ve added this feature to the WSO2 Web Services Application Server — our Apache Axis2-based platform for hosting Web Services and APIs.

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As demand grows for Web APIs side by side with Web sites, a unified server provides a powerful and convenient way to provision and host both capabilities on a single server runtime, manage them through a unified console, with a single set of administrator privileges.  This unified approach offers double the benefits but at much less than double the complexity — all the benefits of the WSO2 Carbon framework, and all the skills you have in managing them, can now be applied to Web Applications.  Even multi-tenancy for deployment in the cloud — more on that in a subsequent post!

What better way to celebrate the lean nature of the product than with a new, leaner name!  appserver_logo_h23With version 4.0, the WSO2 Web Services Application Server, now no longer limited to just Web Services, is now called simply the WSO2 Application Server.  Download it today or try it out as a service at https://appserver.cloud.wso2.com!

Afkham Azeez, Senior Architect and Senior Manager

Azeez’s blog: http://blog.afkham.org/

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New: WSO2 Named a Leader in New ESB Analyst Report

In the latest Forrester Wave on ESBs, they declared that WSO2 was a “Leader” and scored WSO2 a 4.47 out of a possible 5.0 for “Current Offering.”

This follows two recent Gartner SOA Magic Quadrants that listed WSO2 as a Visionary. Whether or not you follow Gartner, Forrester, or more specialized analysts such as Redmonk imageor the 451 Group, this is a great sign for WSO2 – we are gaining not just customer traction but also visibility from the wider industry. I often think that we are one of the IT world’s best kept secrets: a 120 person company that competes head on with Oracle, IBM and Tibco in the middleware space; that is used by one of the world’s biggest e-tailers to do more than 800m transactions a day; that has a complete multi-tenant, elastic Platform-as-a-Service; and that does this all completely as a Modular, Open Source, and Lean codebase.

Focusing just on the ESB I recently heard from a customer that they have run their WSO2 ESB cluster with zero downtime for more than 2 years. What does that mean? They run a cluster for continuous availability: even during updates the cluster remains up and active – using a graceful restart model they can push configuration updates through the system without affecting any clients or losing any messages. So despite multiple updates and even hardware changes the cluster has been live continuously for more than two years with not a single second of downtime.

Our ESB is strongly based on Apache Synapse, and generally analysts do not evaluate Apache projects, because their clients are looking for a complete supported commercial solution. That is ok, but I think that Apache Synapse deserves a strong mention at this point. I submitted the proposal for Apache Synapse to Apache in August 2005. Some of the initial discussion around Synapse avoided the use of the word ESB – but the reality of the development from the very first line of code is that we were (and are) building an ESB. WSO2 has had a strong commitment to Synapse from day one, but there are other excellent contributors and I want to thank the whole Apache Synapse team – in my mind this rating by Forrester is not just a rating for WSO2 but for the underlying Apache Synapse ESB as well.

Here is hoping that this wider exposure helps turn WSO2 from the best kept secret to the best known alternative to bloated, costly and proprietary platforms!

Paul Fremantle, WSO2 CTO
Paul’s blog: http://pzf.fremantle.org/

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Public Services Gateway and Internal Services Gateway Patterns

I wrote earlier about defining a Generic API in your SOA by encapsulating the heterogeneous service platforms that you find in your infrastructure. The two patterns I’ll discuss today are sub-patterns that we can refine from the features provided by the Generic API pattern.

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The Internal Services Gateway (ISG) pattern exposes services in the underlying service platforms to internal service consumers by using the Generic API pattern. The WSO2 Enterprise Service Bus (ESB) is deployed in the local area network (LAN) and exposes backend services as proxy services. This aggregates the backend services into a unified services layer and simplifies the backend service contracts.

Security policies for authentication and authorization can be designed appropriately for the context that only internal consumers will be allowed access to the services. Some ISG deployments only consider network level security provided by the infrastructure, others leverage Single Sign-On (SSO) through an internal user store hosted by Active Directory, LDAP, and RDBMS, or Windows-based Kerberos tokens.

The Public Services Gateway (PSG) pattern exposes select services to external service consumers. In a normal infrastructure this is achieved by deploying a WSO2 ESB in a “DMZ” (demilitarized zone where security is carefully managed – I’ll provide more information about DMZ practices in a future post) and exposing the services to external service consumers. The DMZ ESB pre-processes service requests coming from the public service gateway, and thus originating outside the core network, and routes only valid and authorized messages to the actual service platforms deployed in the LAN.

Pre-processing steps typically consist of message validation, filtering, and transformation. Compared with the ISG, a PSG should maintain a higher level of security due of course to the origin of service requests coming from outside. The PSG should be configured to use the relevant security policies and bridge into the internal security policies by using the security protocol switching capabilities of WSO2 ESB. SSO support for external consumers can be implemented using SAML2 tokens or any other Secure Token format (such as OpenID).

Two implementation models are popular: a PSG consuming services through an ISG or a PSG directly consuming the backend services. In addition to message-level validation the PSG can extend validation to the attachments coming with the message, for example executing virus checks by configuring WSO2 ESB to execute a virus check program.

In summary these two patterns provide clean, proper control of services exposed variously to the internal and external consumers. Security policies appropriate to each type of customer can be developed, deployed, and managed simply through the internal registry in the ESB or through and external WSO2 Governance Registry instance.

Asanka Abeysinghe, Director of Solutions Architecture
Asanka’s blog: http://asanka.abeysinghe.org/

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Enterprise Architects Appreciate “Lean”

Standing out from our conversations with dozens of Enterprise Architects at last week’s Forrester Enterprise Architecture Summit 2011 in The cloud descends on San Francisco for the Forrester EA Summit 2011 [Jonathan Marsh from the Golden Gate Bridge 2/16/2011]San Francisco was the interest in and appreciation of “lean” approaches to integration challenges.  From a lot of nodding in the room after Paul’s assertion that a lean solution was a key factor in eBay’s choice to use the WSO2 ESB in their ultra-scale deployments, to expo floor conversations with Enterprise Architects who are tired of suffering under bloated old industrial middleware and perking up at the idea that this is not inevitable, I came away with the impression that we may be on the cusp of a “lean” wave.

Let me be clear, while the WSO2 Carbon platform is lean it’s not skinny.  Through a sophisticated componentization model based on OSGi, there are hundreds of features to choose from, comprising a complete middleware platform from data to screen.  You just don’t typically need them all at once.

What are some of the factors that are driving the lean movement?  I think they include:

  • Simplified installation, configuration, and provisioning.
  • Low resource use, specifically modest disk and memory footprints.
  • High performance as a result of a simple straight-line approach to the problem at hand.
  • Immense productivity and reliability gains which occur when a tool addresses the problem at hand directly, not through multiple layers of generalization and abstraction.

This lean mentality kind of reminds me of my Microsoft days during which Windows Server Data Center Edition was introduced.  DC is essentially a version of Windows Server stripped down to its leanest, most performant and secure core.  It surprised me at the time that they charged significantly more for less actual code.  But it does demonstrate the value proposition of “lean,” and why it may now be a trending topic in the field of Enterprise Architecture.

Jonathan Marsh, VP Business Development and Marketing
Jonathan’s blog: http://jonathanmarsh.net/blog

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Why Governance isn’t just for SOA – but Identity too!

People often think of security in terms of barriers. But anyone who looks after a barrier knows that its an ongoing process. And managing processes is what we call governance. A few years ago, I would talk to people who had put in place a firewall. They were convinced they were now “secure”. But then I’d ask what process they had to monitor the firewall and its logs. Unfortunately too often a look of “do I have to do that?” crept onto their faces. Without governance, a firewall is no good: if you don’t know someone is making a concerted effort to attack you, they will eventually get through.

It is not just firewalls that require governance. Increasingly I see examples of security issues that also are linked to governance. I think Wikileaks is a good example: whoever did it had too much access (not policy based but simply yes/no) and there was no “alert” that perhaps an unusual access pattern was in operation. Similarly I recently heard of a situation where an employee kept their online work log in for six months after they left the company.

Too many keys, copyright 2011 Jonathan MarshThere are two prime causes for this:

  • Firstly, there are too many identities. Each of us knows we have tens if not hundreds of identities on different systems. And there is no overall control of those identities.
  • Secondly, there are too many places that permissions are checked, or not checked. On the whole we rely on each application to implement permissions and there is a huge lack of consistency between these systems.

Its possible to fix some of these problems with manual governance processes. But even better is to automate them: the least human effort giving the most security.

We believe that there are two key technologies that can help:

1. Federated Identity Tokens

For example – SAML2 – the Security Assertion Markup Language v2 is a standard for XML-based identity tokens. These tokens give us two big benefits: single-sign on and federated identity. SAML2 can help unify as many systems as possible around a single identity. You can configure Salesforce or Google Apps to accept SAML2 tokens from a system driven by your internal LDAP. When an employee leaves, all you need to do is to remove them from your LDAP system and they are automatically shut out of all SAML2 based systems. This is an example of federating the identity from your internal model into Salesforce or Google. Amazingly, unlike most security systems that make life harder, SAML2 actually helps your users, because it gives them single-sign on onto many different websites.

How does SAML2 do this? The key benefit of SAML2 is that the user authenticates to a single “identity server”. Then this server creates a token which is trusted for a limited time by the target. The token can contain a variety of information (“claims”). These claims can be used as part of any authorization process. For example, a claim could assert that the user is logging in from a secure network.

2. Policy-based authorization and entitlement

For example: XACML – the XML Access Control Markup Language – does for authorization what SAML2 does for authentication. It allows a single policy based model for who can access which resources. XACML is very powerful too. It can work in conjunction with SAML2 to create very rich security models. For example, you can allow different access to users who are logged into a secure computer on a secure network as opposed to users coming via their laptop from Starbucks.

XACML does this by being able to capture complex “entitlement” logic into the Policy. The Policy is an XML file that can be stored in a smart registry. For example a policy might state that user Paul may access a salary update process between 9AM and 5PM GMT if Paul is in Role Manager.

 

The title of this blog is that governance is not just for SOA. SOA Governance has been — in our view — an area where the architecture community has learnt a lot of useful lessons. Let’s try to apply the SOA Governance lessons to Identity and Security Governance.

In the SOA world a common pattern for governance is the combination of a Registry and an ESB. The secret to this is:

  • Using policy and metadata instead of code, and managing the metadata in a Registry.
  • Moving towards a canonical model and transforming legacy systems into the canonical model.
  • Putting in place central logs and monitoring.

It turns out we can learn exactly the same lessons for Identity:

  • Using XACML to have a consistent model and way of defining authorization and entitlement using policy instead of hard-coding it into apps and storing these policies in a Registry.
  • Audit Log, Copyright 2011 Paul FremantleUsing SAML2 as a canonical model for Identity and bridging that into legacy systems as much as possible.
  • Using common auditing across your Policy Enforcement Points (PEPs) to ensure a single central audit log.

With this kind of model the governance becomes much more simple and automated. Removing a user’s login permission can remove login from everything. Authorization can be based on policies, which can be managed using processes. Even remote systems like Salesforce will still be included in the audit, because when a user signs in via SAML2, the SAML2 token server will create an audit event.

OpenID and OAuth are alternatives that perform similar and complementary functions to SAML2 and XACML, and are supported by a number of websites and web-based systems.

Good governance is tricky, and an ongoing process. The best way to get good governance is to automate it around simple straightforward approaches. The trio of metadata, canonicalization and log/audit is a great start and putting in place a solution around that architecture is an effective way to improve your Identity Governance.

 

 

Portions of this post have previously appeared in an article written by the author for Enterprise Features

Paul Fremantle, WSO2 CTO
Paul’s blog: http://pzf.fremantle.org/

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Recognizing the Stars

No, this post is not about the Golden Globe Awards. This post is about another special awards ceremony that also took place last weekend — the annual WSO2 Awards Night!

Every year here at WSO2 we pay tribute to the top outstanding contributors. The entire team  really contains a whole bunch of stars but some do shine especially bright. Without imagetheir passion, commitment, and attitude to shine the extra mile, we would not have come this far in redefining middleware and providing support services matched by no other.

Like the Globes we’ve got a bunch of categories too: Outstanding Contributor of the Year, Customer Delight, and Outstanding Team of the Year.

And this years’ winners were … drum roll please …

Outstanding Contributor Award: Samisa, Azeez, Supun, Buddhika, Charitha, Saminda, Milinda, Evanthika, Krishantha, Chathuri, Padmika, Janath, Devaka, Shankar, Sumedha, Udeshika

Customer Delight Award: Prabath, Senaka, Hiranya, Asanka Abeysinghe, Chamith, Kasun, Nirosh

And the Outstanding Team of the Year Award goes to … the QA Team, for putting out 46 releases, about 150 patches, and 16 cloud releases, while remaining (mostly) sane.  Incredible work!

This year for the first time, we also gave out long service awards for those who’ve been in the Company for five years, which is practically since its inception. There were nine long-timers in total, including yours truly! 🙂

Its been a great team to work with and each year only gets better than the one before. So here’s to another outstanding year — 2011 here we come!

Hasmin AbdulCader, WSO2 Director of Marketing

Hasmin’s tweets: http://twitter.com/HasminA

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How much should you care?

A couple of weeks ago, I recorded a podcast with Paul O’Connor and Dana Gardner. Paul O is someone I’ve worked with on and off for about four years now, first as he helped customers Podcast iconnavigate SOA and now as he leads their thinking in Cloud. It was immense fun recording the podcast with Paul, but, if anything, we only scratched the surface of Paul’s thinking. He is one of the real visionaries of how Cloud is going to affect large businesses IT and completely rewire it.

Paul O believes that the end-game of true cloud computing is the ability for a business to completely focus on the business and have the IT from infrastructure to development completely available as a Service. Paul calls this the Grand Unified Theory of Cloud: consuming IT entirely as a service.

I personally don’t agree: I think that there needs to be a sliding line that divides IT from the pieces I have to care about to the pieces I don’t. Twenty years ago I cared about processor instruction sets and assembly code. Today I don’t. Today, I don’t care what actual hardware my Amazon images run under — there is a rough measure and the details don’t bother me. On the other hand, if I was doing algorithmic trading, I care even about the clock frequency I can rack the machine up to. I don’t believe that we will ever get to a line where the business doesn’t care about any of the details — that simply opens up an opportunity for another business to find competitive advantage by finding something to care about. But I do agree with Paul: at the moment we are forced to care about too many aspects.

Here at WSO2 we are trying to create a platform where you can stop caring about 99% of the middleware issues and we can provide a platform that just takes care of that for you. The real Grand Unified Theory of Cloud for me is being able to choose exactly what to care and focus on in your IT, and have the other parts just work — as a service.

Find the full podcast and transcript here.

Paul Fremantle, WSO2 CTO

Paul’s blog: http://pzf.fremantle.org/

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Good Things Come in Threes

In keeping with our Solutions Architecture focus, we’ve just released three new whitepapers describing reproducibly successful patterns we’ve seen (and helped) our customers achieve.  Complete with architectural diagrams and requirements, I’m sure readers of this blog will find these solutions interesting, and applicable to specific challenges they may be facing.


WSO2 Mobile Gateway Solution: Extend the Boundary of Your Enterprise Through Innovative Mobile Experiences

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WSO2 FIX Gateway Solution:Interoperable Connections for the Financial Industry


WSO2 SAP Message Gateway Solution: Cost-Effective SAP NetWeaver Replacement

Naturally, each of these solutions makes effective use of the WSO2 Enterprise Service Bus.  Enjoy!

Jonathan Marsh, VP Business Development and Marketing
Jonathan’s blog: http://jonathanmarsh.net/blog

Defining a Generic API

With a premium placed on loose coupling, a typical SOA deployment displays a high degree of heterogeneity. Different service platforms run in scattered datacenters on a variety of server hardware, operating systems, and development platforms. The services expose different communication and security standards. Individual SOA implementation and maintenance teams will become acclimated to the level of heterogeneity with exposure to the environment, but when an external or internal consumer tries to access the SOA, they will come face to face with this complexity.

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A common way to simplify and normalize interactions with a heterogeneous environment is to provide a unified API for service consumers — a unified, generic service layer.

One of our commercial bank customers with multiple service platforms began a project of defining a unified services layer, generalizing the the multiple service platforms active in the bank. At first they approached the problem in the traditional way: writing wrapper/proxy services in front of each of the existing services.  As part of an engagement with WSO2 they changed to a “Generic API” solution pattern which dramatically simplified the project by hiding the internal complexity of each service behind a user friendly API, a common URL for service access, and unified security policies.

The “Generic API” pattern installs a common API for the existing service infrastructure, converts traditional applications to services exposed over a normalized set of communication and security protocols, and provides a foundation supporting the easy addition of future service platforms.

image

When implemented with WSO2 products, the Generic API pattern leverages the WSO2 Enterprise Service Bus (ESB) and WSO2 Governance Registry. The WSO2 ESB connects with the back-end service layers and legacy applications, and exposes them through a new service layer.  This is easily accomplished with the proxy service capability of the WSO2 ESB.  Supporting a wide variety of of the transports and message formats, the WSO2 ESB provides a central hub for protocol switching and security mediation between the heterogeneous systems.

With sophisticated transformation capabilities, the WSO2 ESB extends the Generic API pattern to the problem of unifying data models, by converting or mapping messages representing different data models into a common and easily consumed model.

Storing and publishing common metadata such as service descriptions and policies describing the generic API also aids new developers interacting with the system.  In the deployment above, the WSO2 Governance Registry provides a common repository for storing and sharing all the necessary SOA artifacts.

The Generic API pattern provides the foundation for other other solution patterns as well.  In future posts we’ll discuss solution architectures for a Public Services Gateway and an Internal Services Gateway pattern.

Asanka Abeysinghe, Director of Solutions Architecture
Asanka’s blog: http://asanka.abeysinghe.org/

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