Category Archives: News

Transform Your Enterprise IT: Integrate and Automate

Most enterprises deal with a variety of common IT problems to which they would find quick fixes. One such example is the need to maintain five different usernames and passwords to login to five different systems. Another typical example is the closing of a sales deal – the sales department would conclude the deal and ensure the goods are delivered; this would be updated on the sales records, however, when the finance department reconciles invoices against sales at the end of the quarter, there might be mismatches because the invoicing process was missed.


To address these issues, most enterprises will use a combination of basic IT and collaboration software to manage day-to-day requirements. And over time, these requirements will change, prompting a slight shift in the enterprise’s IT landscape too. This may result in a situation where different teams within the organization will find the most efficient ways to carry out tasks and meet their IT requirements with the use of packaged software, possibly by building their own, or even subscribing to more SaaS-type offerings.

While this might temporarily fix specific problems, it will pose long-term challenges as such measures are often not pre-planned or do not follow a particular IT roadmap. The actual negative effects of individual teams working in silos would only be felt when the company starts to grow and the use of various systems increase as well. Eventually, the use of several systems that don’t talk to each other will cause operational issues and even hurt motivation among employees.

The recurrent problems with these multiple systems working in silos include extensive manual effort, errors, blame, rework, frustration, complaints, and the need to manage multiple passwords. These in turn result in inefficiencies.

To address these challenges, the enterprise needs an easy-to-implement, cost-effective solution. There’s no guarantee though that there would be a plug and play type of system or one that could be customized to meet the enterprise’s exact requirements. The enterprise would seek a unique, bespoke solution that would either mean they change the way they work with existing software or rethink the software itself.

The most viable option would be to integrate the systems (which, of course, have proven to be efficient to meet a specific requirement) used by different functions and then explore some sort of automation that will provide relief to employees.

WSO2’s highly-acclaimed open-source middleware platform has the capabilities that enable seamless integration of IT applications, thus streamlining day-to-day business activities of a given enterprise. This in turn will boost efficiency and integration across business functions and teams and improve overall productivity as well.

For instance, WSO2 Identity Server (WSO2 IS) can define an identification for a user in a particular organization, enabling him/her to log into multiple systems on-cloud or on-premise with a single username/password.

The enterprise too will benefit as WSO2 IS offers provisioning capabilities that allow your IT to register and auto-provision new employees across multiple systems as well as easily de-provision them when they leave the organization.

WSO2 Enterprise Service Bus can meet all your integration challenges with its capability to connect various systems that speak different languages. It also comes with a defined set of connectors to further support integration of systems, be it on the cloud or on-premise.

Once all of your systems have been integrated, you can leverage WSO2 Data Analytics Server (WSO2 DAS) to pull reports from different functions within your organization and automatically collate data that will translate to valuable information required to make business decisions. WSO2 DAS has in-built dashboard capabilities that will automatically create and publish dashboards on a real-time basis.

Moreover, all WSO2’s products are 100% open source, which gives enterprises the freedom of choice and empowers the business with limitless possibilities to expand.

Learn more about WSO2’s comprehensive and open platform for your connected enterprise.

For more details on how to establish friendly enterprise IT and get more love from your team, watch this talk by WSO2’s VP Operations, Shevan Goonetilleke.

Modern Solution Development: The Battle Between ‘Retaining’ and ‘Changing’ Technology

In today’s fast-paced technology world, change is constant and rapid. New concepts continually emerge, gain traction, disappear, and reemerge. While it’s important to embrace this evolution, core concepts that work in older technology should not be tossed out either.  

During his closing keynote at WSO2Con USA 2015, Dr. Donald Ferguson – former vice president and CTO of Dell, identified concepts independent of the specific technology realization in order to highlight requirements that current technologies don’t meet.


He noted that although concepts such as loose coupling, service delivery, and asynchronous messaging have been used for various different technologies like common object request broker architecture (CORBA), Web services, and service-oriented architecture (SOA), each of these is just an improvement, yet based on the same ideas. “The key thing when going forward is to make sure that we don’t loose some of the things that we managed to bring forward because they were good,” he adds.

He explains these similarities, improvements, and limitations are apparent when comparing SOA to microservices for instance; features such as programming style, code type, messaging type, and the use of databases are similar in both concepts whereas there are certain important distinctions in means of evolution, systematic change, and scaling. “It’s more about how you do it – the internal architecture, than the externals. With one exception – smart endpoints and dumb pipes” says Ferguson. This concept encourages the microservice community to use a light-weight message bus (a hub) that acts solely as a message router and leaves the smart part of things (receiving a request, applying appropriate logic and producing a response) to the service itself.

But as Ferguson states, “You don’t want just a hub, you want it to be active”. If you open any book on enterprise application design patterns, they first show you what not to do – a monolithic point-to-point architecture. To avoid doing this you need to connect everything through a hub that needs to be able to reformat, route and combine messages as well as understand different protocols and data types that will travel across it. This is where middleware, or specifically the enterprise service bus (ESB) becomes important.

Ferguson notes that dumb fast messaging seems more appealing than using a powerful ESB but it just repeats the fallacies of quick point-to-point connections. Using an active hub and taking advantage of middleware to do it is much more advantageous because it adds value and improves robustness, reusability and scalability.

He further adds that any organization can realize tremendous value from microservices and other new technology; however, this could sometimes result in the risk of losing benefits like interface dependency and optimized composition that emerged in the past. “This needs to be done through application design patterns and middleware that empowers them…that’s part of the value WSO2 is,”he concludes.

WSO2’s complete middleware stack includes the WSO2 integration, API management, security and analytics platforms. By leveraging these components and more you can easily develop modern solutions despite what technology you use.

To learn more, watch Don Ferguson’s presentation at WSO2Con US 2015.


How you can Increase Agility and Expandability with Event Driven Architecture (EDA)

From ordering your favorite kind of pizza or a taxi to manufacturing and financial processes, everything is event driven today. People expect to do everything immediately, get instant feedback on the status of their request, and interact in real-time with anybody involved in the process.

John Mathon, the former vice president of enterprise evangelism at WSO2, wrote a white paper which explores how you can keep pace with these demands by implementing event driven architecture (EDA) in your enterprise.

EDA is essentially a messaging system that notifies interested parties of events that occur in order for them to benefit from it. The publish/subscribe model was implemented in the earliest real-time event-driven systems. Anonymity, discoverability and guaranteed delivery were a few of the characteristics that made it popular.

But this simple model deemed insufficient for the demanding and varied needs of subscribers, notes Mathon. Here came the rise of the enterprise service bus (ESB), which standardized enterprise integration patterns, the business process server (BPS) which allowed messages to trigger business processes that dealt with events and business activity monitor, now named data analytics server (DAS), to monitor the health of enterprises through statistics.

These tools became standard components in an EDA and are useful even today, which is why IoT is reusing pub/subs all over again.

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The easiest, fastest and most efficient way of implementing EDA in your enterprise is to incorporate already existing event-driven technologies. You may think writing dedicated software would be more cost efficient and cater more to your specific needs, but in the long run the cost of maintenance would be over a dozen times more than the initial cost of development.

Existing tools are designed to increase performance and reliability of your system. It’s also easy for non-programmers to use because of features such as drag-and-drop components. They can handle large loads and are robust, secure and resilient to failure.

You can choose a specific tool for a specific problem. For example, long-running processes use BPS and short-running ones use message broker (MB). Also, when the tools are combined together it can provide additional power by working together to achieve one goal.

The problem with combining tools is that they can each be large monolithic entities that require significant communication bandwidth and can cause increased load on servers. WSO2 solves this problem because all the tools you require are built as light-weight components with the same base framework making it possible to combine them in the same Java runtime.

When implementing an EDA you need to keep in mind the message flow rates and the characteristic of the message flows. Make sure not to create extremely large messages or do a lot of computation during processing. You also need to consider whether you will be designing for microservices; your architecture design depends on this. API management is another key factor that you need to keep in mind. And lastly, you need to know which tool to use for which job.

WSO2 offers a full suite of open source components for EDA to implement highly scalable and reliable enterprise grade solutions. This includes a complete middleware stack, which includes the WSO2 integration, analytics, security and API management platforms.

For more details download John’s whitepaper here.

Connected Finance: Unleashing the True Potential of Finance with Technology

Evolution in technology has made customers more demanding, and at the same time, created new opportunities for financial institutions. The meteoric evolution of technology has prompted customers to look for quick and convenient ways to carry out banking needs, making mobile and online services popular. Financial companies need to make sure that they can deliver these services independent of location in a secure manner. It has also become compulsory to accommodate mobile payments and virtual payments in the connected finance ecosystem, resulting in a complex IT landscape.

Enterprises in the financial industry recognize the importance of delivering these needs to remain competitive; however, the challenge is to build a real-time system that centrally connects everything. Services and APIs are used to seamlessly connect the various backend components to build a robust connected ecosystem.

Asanka Abeysinghe, VP of Solutions Architecture at WSO2, recently authored a white paper – Connected Finance Reference Architecture – in which he discusses the significance of creating a connected finance system. He also explains how a middleware platform can be used to address each and every challenge faced at implementation.

Here are some highlights from this white paper.

The connected finance architecture will primarily facilitate regular, day-to-day functionalities, as well as call center-type functionalities, virtual payments, credit card payments and payment gateways. It will also make the vast amounts of data centrally accessible, allowing decision makers to gain business insights via customized reports and dashboards.

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Given the sensitive nature of the industry, this aspect is important and needs to be addressed properly. For this, the architecture should connect all the systems and ensure all security measures have been incorporated. Each and every transaction should be closely monitored while ensuring all transactions flow through the same layer allowing the company to  monitor, manage, and govern financial transactions.

In addition, Asanka explores the role of event-driven architecture (EDA) in the connected finance ecosystem along with an architectural pattern for monitoring gateways. He discusses how WSO2’s complete cloud architecture enables enterprises to implement a hybrid deployment that complies with the tight regulations of the financial industry.

For any financial company, becoming a connected business will help to provide customers a better service as well as enable them to become more efficient and profitable overall.

For more details on the Connected Finance Reference Architecture, download and read the white paper here.

Introducing WSO2 Gateway Framework – A Slight Change in Course Post Alpha Release

In November 2015, we announced a high performance, lightweight, and configuration-driven message gateway – WSO2 Gateway – based on standard gateway patterns. We made available an Alpha version with a plan to announce general availability this year. This product provides fully decoupled protocol handling layers and message processing layers, making it easier for users to configure messaging behavior at each layer independently.

A few months later, and as we progressed with our GA release plan, we realized there was a broader need and changed our strategy to instead use this component as a framework for all WSO2 integration-based products: the gateway framework will become the core of other gateways, such as the API gateway of our API management offering, and power the next generation of our enterprise service bus.
The original gateway code is still accessible on GitHub.

The Microservices Discussion: Didn’t We Do This Before?

Microservices is a trending term right now. The enterprise programmers’ corner of the Internet seems to be stuffed to the brim with talk of microservices – Mark Russinovich, CTO of Microsoft Azure, even wrote a blogpost calling it a revolution.  Chris Hart of wrote at length about it, linking it to the Unix philosophy.  By all accounts, microservices seem to be changing the world…

Or are they? On the 24th of March, we (WSO2) hosted a meetup in Colombo, based on Microservices. In it, Kasun Indrasiri and Afkham Azeez tackled what we think is a pressing question: what are microservices, and how are they different from what we’re already doing?

By now, everyone knows what the monolith is – the dreaded single-unit architecture that ends up becoming a nightmare to deploy, build on and scale. It is self-contained and is, in essence, a silo unto itself.

Enter microservices: the philosophy that a single application should be composed of multiple fine-grained, loosely coupled services that are built and deployed independently of each other.

Kasun explored this concept in minute detail in an earlier blogpost, pointing out that microservices need to follow the Single Responsibility Principle: each microservice handles a limited and focused business operation, and as such should have very few operations and a simple message format. That’s so you don’t end up just building miniature monoliths. Harries Blog contains a diagram that illustrates this well:  

However, in all of this, the software industry seems to be forgetting that such a development style has already existed for a while now. Some time ago one of the hottest buzzwords was Service Oriented Architecture, or SOA: essentially, unassociated, self-contained units of functionality communicating with each other to get a job done, usually with some kind of interface in between.

Sounds familiar?

While the definitions of microservices seem less vague, Microservices, Kasun pointed out, is actually little more than SOA done right.  Indeed, as Azeez noted, the software industry likes to reinvent old things by slapping a new name onto them.  It’s not a new paradigm, and nor is it a panacea; there are instances where it’s not the most optimal route to take.

It’s possible that ‘microservices’ started trending because we now have better and easier tools for facilitating this kind of development. Docker and Kubernetes have practically hammered in these basic concepts into a lot of developers’ heads. All it needed was a name.  For a more nuanced understanding of microservices, read “Scope Versus Size: a Pragmatic Approach to Microservices Architecture” by Asankan Abeysinghe, VP of Solutions Architecture at WSO2.

Either way, here’s a toast to microservices – for keeping the spirit of SOA alive and kicking. .


Deep Huge: AI Predicts Donald Trump Becoming the Next President


Predicting the Presidential Election is practically a national sport. However, traditional predictors – especially the talkshow hosts on Fox News – have historically been terrible at calling the next set of numbers. It took Nate Silver’s exceptional statistical skill to show us that with public data, you could accurately predict the election down to the last winning percentage – if the mind doing the calculations was good enough.

Artificial Intelligence has evolved exponentially over the years. We’ve gone from Deep Blue beating Gary Kasparov to DeepMind mastering Go. A Japanese AI just wrote a novel that almost won a literary prize. We may not have another Nate Silver, but the world is in a position to create his machine analogue.

Which is why we at WSO2 have constructed a system designed for the sole purpose of election math. While Google and Microsoft have been happy to use their gifts to play board games and embarrass themselves on Twitter, ours, powered by WSO2 Machine Learner, has been set the task of picking the next POTUS.

Deep Huge, as we’ve called the system (a nod to Deep Blue) predicts that Donald Trump will almost certainly win. That is, if he picks the former Governor of California, Arnold Schwarzenegger, as his Vice President.

To state it in numbers: there is a 52.3% chance that Donald Trump will win by himself, regardless of his choice of VP; with Schwarzenegger, there is a 99.4% chance that Trump will defeat all others and become the next POTUS.

How it works

Like Nate Silver’s FiveThirtyEight itself, Deep Huge’s predictions are probabilistic. We use poll data from the Associated Press, historical records. earlier elections, news articles, secret NSA surveys and Twitter for exploring sentiment and secondary issue mapping. This data is then fed into WSO2 Machine Learner, which computes the prediction model. 

Since sources other than polls are not representative, we have paid more attention to trends rather than absolute numbers, and extrapolate the poll predictions while using other sources as calibrations.  The current model analyzes the win probability of presidential candidates and then runs this against an array of potential vice presidents.

At the start of the elections, the probability matrix was far too diffuse for any prediction to be useful. However, as the candidates dropped out and campaign tactics solidified, the predictions become more accurate. Deep Huge has successfully modeled the key pitfalls such as shifts of public opinion and the problems with running your own email server.

Every model shows that the choice of a VP is critical, as the second most powerful player in the game brings their own voterbase with them. 


In this case, the former Terminator not only solidifies Trump’s position in California, but Schwarzenegger offsets concerns—particularly among men—about Trump’s small hands.

The two men also share strong similarities, including a desire for closing the Mexican border. Schwarzenegger also has a track record of what one might consider Trump-like, politically incorrect statements, such as in 2007, where he urged Hispanic journalists to “Turn off the Spanish television set” and “Learn English”.

Other potential Republican VP candidates provided small gains or even losses to Trump’s odds of winning the 2016 US presidential election. Notably the probability of Trump winning the general election was 53.4% with US Senator Ted Cruz, 46.2% with former Alaska Governor Sarah Palin, and 65.1% with Fox journalist Megyn Kelly.

According to the latest research, in today’s connected world there are just three and a half degrees of separation between an also-ran and America’s next president,” said Dr. Sanjiva Weerawarana, WSO2 founder, CEO and chief architect. “Our Deep Huge project demonstrates the power of combining streaming, batch and predictive analytics to take a pulse on American voters’ sentiments and provide insights into the winning combination of presidential and vice presidential candidates in 2016.”

Deriving secondary insights

We noted while digging into the model that, in the GOP, the divide between campaign position in terms of key issues between Trump and Cruz is semantically closer, while in the Democratic party, the semantic divide is much larger. This makes it harder for the party to rally the voters who are divided in primaries. Further analysis revealed that divide proved to be a major turning point in earlier election outcomes.

To train itself to this level of accuracy, Deep Huge has to date run 11,302 simulations on available prediction data from the previous years, comparing it against the actual results to dynamically build a prediction model using Random Forest Regression.

While it may bear some passing resemblance to 538’s model, it has not been taught the concepts of weighted polling averages and state fundamentals. Its prediction model has been learned and built by the neural network itself, using features from social media sentiment, news articles, poll numbers in terms of campaign issues, and to compute a constantly evolving prediction model.

In Conclusion

In the process of building Deep Huge, we’ve gained valuable insight to the uncertainty inherent to elections. While we’re thrilled to have created the machine analogue of Nate Silver, we hope that one day we will be able to scale Deep Huge to predict any election throughout the globe – one bot to predict them all.

We’re also heartened by the fact that after hearing of this prediction, Donald Trump has reversed his stance on outsourcing and decided to have his campaign planning computed by WSO2 Machine Learner running in Sri Lanka.

And by the way… April Fool.

Deep Huge isn’t real, but WSO2 does keep an eye on politics via our Election Monitor project. This offers a real-time window on the US Election unfolding across Twitter and across mainstream media – mapping influence, sentiment, popular opinion and so much more.  Visit

Big Data and Politics: How the Internet sees the US Election

Nothing is a hotter topic than the US Election, especially if you’re a statistician at heart. Legions of us have been mesmerised by the idea of predicting who gets to be the most powerful President on the planet.

This year, however, it’s far more fun to kick back and watch the Internet collectively explode over each and every one of the candidates in the limelight. What with Clinton’s emailgate, Bernie’s economics, Ted Cruz’s household issues and Donald Trump’s existence …

WSO2 is a technology company. We looked around and realized that we had the tools to observe this theater on an unprecedented scale. We’d like you to join us.

Which is why we present to you the WSO2 Election Monitor.

At its heart, the Election Monitor is the WSO2 Enterprise Service Bus (ESB), Data Analytics Server (DAS) and Complex Event Processor (CEP). The ESB scans Twitter, pulling conversations about the US Election every second. DAS and CEP go to work on these tweets.

 The first thing we’ve done is build this (real-time) counter of the number of unique Twitter accounts talking about each camp. In a 24-hour time window, as of the time of writing, the Republicans seem to be dominating the Twittersphere.


That’s a huge margin, isn’t it? Let’s find out why as we go along.


This is firstly a live feed of what we’re getting from Twitter. The gray columns are the interesting ones: they display the most popular recent tweets – recent being not more than 12 hours ago. Donald Trump often dominates both fields. Occasionally, Bernie seems to break through. As of the time of writing, in the “Popular from candidates” column, Donald Trump has three tweets, one of them about a reporter touching him. The others are one tweet from Clinton Enough is enough”  and one from Bernie talking about deficits.


This is consistent for what we’ve seen so far; ever since the site went live,  Trump’s snazzy one-liners have consistently gotten more retweets and favourites than Bernie and Clinton’s policy-centric tweets. It would appear that one man / tweep from the Republican party is more popular than every other candidate put together… are we really surprised that there’s more people talking about the Republicans than the Democrats?

But what about their followers? Using candidates’ hashtags, we can peek into the conversation by sifting through tweets and finding the most used conversations in that space.

Trump’s people are talking about the border. No surprise there. They’re also talking about New York. That corresponds with the fact that Hillary Clinton just took aim at Trump in a N.Y. ad. It shows a white Trump supporter sucker-punching an African American protester.  

Clinton? The email scandal hasn’t left her behind. There’s talk of war, probably because Clinton tweeted about defeating ISIS recently. There is a LOT of discussion regarding an upcoming debate with Bernie.

Bernie’s community, too, is talking about the debate. There’s few other clues in his wordcloud at the moment.

 Ted Cruz’s community is talking about his wife. That’s because he’s mired in a bit of controversy now: the family man is being dodgy about questions regarding his marriage. There’s a lot of questions about his principles.  

There’s one man missing from this: John Kasich. As of the time of writing, he’s got 143 votes. Cruz had 463. Trump has 736. They all need to hit 1,237 for nomination.

As remote as Kasich’s chances look in the polls, he barely exists on Twitter. For now, we must exclude him.


Step three of the site is the community graph – or, as we call it, the attention graph. Here we map out the most popular accounts talking about the US election. The larger an account’s bubble is, the more popular it is.

What do we see? Donald Trump has gathered more attention to himself than any other tweep. It’s not even a small margin. Dan Scavino comes in at a distant second. Everyone else is miniscule, like little asteroids orbiting Planet Trump. And yet even those tiny accounts get over 2000 likes and retweets. These are the people who are essentially driving opinion on Twitter.

The fourth and final part is how the media’s opinion of a candidate changes over time. By analyzing news articles published online, we can determine shifts as campaigns unfold.

Consider how attitudes have changed towards Hillary. Here’s her standing on the 15th of March:


Here’s her standing on the 17th:


Opinion has swung her way. Examine the titles of the news articles on those days. On the 15th of March: “Was Hillary Clinton Bribed For Her Iraq War Vote?” And “The Cure to Hillary Clinton’s Problem With Millennials? Donald Trump.” Not that good.

On the 17th? “How Hillary Clinton Triumphed on Tuesday” and “Hillary Clinton Becomes Kween of Broad City”.  Short on the heels of a victory comes better press.

It’s fascinating to see how the American media react to candidates as they take on world events. Opinion on Trump, for example, hit rock bottom over his views on China and implications that supporters could go haywire.

Our collection of insights has just gotten started, of course. As the election unfolds, all of this will be running. While we can’t say that Internet is go along to predict who wins, we think it’s a pretty interesting gauge of what the people and the press of America are thinking.

Drop by The project has been deprecated, but we’ve preserved a snapshot of the data so you can see what it was like.

It’s football season and we kick off with WSO2 BigDataGame

Few other professional sports generate more data than American Football – especially when the Big Game beckons. Things heat up. Tables are drawn, graphs are computed and analysts take to the predictions game like moths to a flame.

WSO2 Machine Learner is the latest addition to our products portfolio, and while it was build as a high performance, open source predictive analytics platform that takes enterprise data, uses machine learning to analyze patterns and generates models that can be accurately used to make business predictions, there’s no reason why you can’t use it for sports analysis too.

This is exactly what our team set out to do a few weeks ago. In a fit of experimentation, we connected WSO2 Machine Learner with the data it needs to try and predict the Big Game.

Setting up for the Big Game

American football basically has three seasons. Preseason, regular season and playoffs. After a bit of searching, we came across, which had the data on all the teams for many years, and collected the historical data for 2012, 2013 and 2014.

A few rules were established:

  1. Pre-season data should not be considered because some of the best players don’t play in them.
  2. Injuries, are very common and really skew the data, especially if it’s a quarterback who gets hurt.
  3. Teams that have won the Big Game have usually had a great defense.
  4. Some teams start off the season slow and then begin playing better to make the playoffs.

Taking all this into consideration, we paired Random Forest regression with stacked autoencoders.

And it works! We did a little bit more calculation and arrived at a mathematical 76.5% accuracy rate, which was confirmed by our first set of predictions for the four games held the weekend that the Bengals played the Steelers.

We quickly built out a site so that anyone can test it out for themselves.


You’re free to run any two teams you want against each other and see which one stands the best chance of winning.

Do note that we’re still in the process of tweaking it. Right now, we’re basically predicting probabilities of success – and while we have faith in our product, there’s a whole lot of things that are impossible to account for, injuries in particular. There’s also no predicting the effects of morale on a team; that stuff is sorcery.

However (while it will take more data to confirm this) we’re confident that, as of the time of writing, BigDataGame is one of the most accurate solutions on the web.

For more on how we did it and to pair out your own favourite teams head on out to

The Year That Was 2015

As 2015 comes to an end, we take a look back at the year that was filled with new products, great people, and reasons to celebrate.

This year was a big year for us as we marked 10 years of WSO2. From the humble beginnings of a handful of people, a small office in Colombo, and an idea for a revolutionary middleware platform, we have grown to be a strong contender in the enterprise middleware space with a 500+ team, 5+ office locations, and brand name customers all around the world. The 10-year website we launched gives you a glimpse of how far we have come in this short period of time.

The website got a new look,

We won championships,

Took WSO2Con to London and San Francisco,

And rolled out a great set of products.

The Year of Platforms

One of our key advantages is our unified comprehensive middleware platform, which is of course 100% open source (and will continue to be so). This year we identified individual platforms that position our products and defines our offering as a platform of platforms. Based on the needs of your architecture you can choose which platform to start with and enhance them in an iterative manner on-premise or in the cloud.

We also looked at the common architecture patterns such as EDA, ROA, and the new kid on the block Microservice Architecture (MSA). We introduced the Architect’s Vault specifically for enterprise architects so that they can learn how to enhance their projects and be a leader in their space.

In addition, WSO2 and Axiata launched a radical new open source digital enablement platform for Mobile Network Operators: WSO2.Telco. The platform represents a new milestone in agility and scalability, allowing telcos to expose, manage and orchestrate multiple network services at a fraction of the cost of legacy systems. Check it out here.

New Products and Upgrades

This year we launched four new products

  • WSO2 App Manager, the industry’s first 100% open source product to provide a unified approach for securely managing an enterprise’s applications across multiple platforms.
  • WSO2 Data Analytics Server, which combines into one integrated platform real-time and batch analysis of data with predictive analytics via machine learning to support the multiple demands of Internet of Things (IoT) solutions, as well as mobile and Web apps.
  • WSO2 Machine Learner, pairing data gathering and analytics with predictive intelligence to help you understand not just the present, but to predict scenarios and generate solutions for the future.
  • WSO2 API Cloud, the public cloud version of WSO2 API Manager giving a complete API platform as a service (PaaS), right-sized for an enterprise’s current demands and backed by the power to scale as their needs grow.

And also introduced products which are currently in Alpha with GA expected early next year.

  • WSO2 Gateway, an ultra high performance, lightweight and configuration-driven message gateway based on standard gateway patterns.
  • WSO2 Microservices Server offering an end-to-end microservices architecture to ensure agile delivery and flexible deployment of complex, service-oriented applications.
  • WSO2 Process Center which provides a complete, end-to-end solution for business process management

Many existing products got major upgrades too:

  • WSO2 Enterprise Service Bus has several new inbound endpoints that enable transports to work in multi-tenant environments, new functionality for creating custom inbound endpoints, and 100+ connectors.
  • WSO2 API Manager supports Swagger 2.0, is open to third-party key servers for authenticating API Consumers, and includes enhances analytics
  • WSO2 Identity Server includes workflow support and is Fast Identity Online (FIDO U2F) compliant.
  • WSO2 Enterprise Store enables greater extensibility and customization in managing any enterprise asset type, adds REST APIs for the Store and Publisher components, and enhances role-based access.
  • WSO2 Governance Registry now integrates WSO2 Enterprise Store and WSO2 API Manager capabilities, providing a single center for governing APIs, services, tokens and more via a consumer-like interface.
  • WSO2 Message Broker  adds new features and enhancements to provide enterprises with a scalable and distributed architecture for easily managing the high messaging volume demands of IoT solutions.
  • WSO2 Business Process Server now includes the Activiti BPM engine, which supports BPMN 2.0, the specification recognized as one of the most IoT-aware approaches to process modeling.
  • WSO2 Data Services Server supports the open, standard OData 4.0 protocol, which enables the use of RESTful APIs to query data from a range of sources.

Looking Forward to 2016

Apart from new products such as a Dashboard Server, Log-analytics Server and IoT Server, a major update comes in the form of  WSO2 Carbon 5. Carbon is our middleware kernel that powers our products and will include

  • An artifact deployment engine
  • A startup order resolver
  • Execution multi-tenancy with containers
  • Logging with Log4J-2.0
  • Transport management
  • JDK-8 features
  • RESTful kernel foundation services

This also signifies a change in our product strategy. All WSO2 products will have three main components:

  • Runtime: to run the different types of artifacts and execute functionality
  • Tooling: to manage, develop, configure and integrate the product
  • Analytics: to monitor the product’s execution

There will also be a change in our PaaS strategy. Not only will we be supporting Apache Stratos but also Container as a Service platforms such as Kubernetes. Even with the public cloud, the plan is to transition from Stratos to Docker and Kubernetes by early next year.

Our vision is to continue to create lean, high-performance middleware runtimes that enable agile and iterative architecture. We aim to provide a powerful platform for your digital transformation, so here’s to a fantastic 2016!