Business Rules Re-Imagined

The Impact of Cloud, AI/ML and RPA and on Decision Management

Decision making is a key component of today’s business applications. Complex business applications must be able to make decisions following the same rules a human would follow when making those same decisions.

Because business applications are so critical –  and because they need to incorporate business know – how into the applications to support accurate decision making – the building of these applications is no longer left solely to IT developers. Software development is seeing increasing involvement from the business side. 

For example, in the past an insurance company would write an application that records insurance claims. Today, IT is writing applications to sell insurance. That is a huge change. In computer science class, developers are not taught how to sell insurance. And it is not like the insurance company lacks that expertise anyway. They have many people who know how to sell insurance, but none of them work for IT. So more businesses are realizing that they need to involve the business stakeholders in the software development process, and incorporate more business knowledge directly into these applications. 

Clearly, the business stakeholder are not developers. They are not going to write code, but they can produce models of their business, based on the business rules, the processes, the policies, and the decisions they make while conducting company business. These models can be thought of as the source code that will be deployed within the business apps. 

How does IT empower the business user to encode as much of their knowledge as possible so they can add value to the applications the organization depends on? Development teams should utilize business rules rather than simply encoding business logic into applications. When business logic is built into the application – which is the traditional way of developing business applications – the business stakeholders have no visibility. It is hard for them to see what specific policies are being applied; what the rules are; and why a decision is made. 

The solution is to outsource the decision making to a business rules engine, which makes decisions on behalf of the application, based on a set of rules written in English so the business side can understand. Business can gain much more control over the policies that are applied automatically by these applications.

A business rules engine provides multiple advantages, including:

  • Separation of the business rules from the applications
  • Visibility for business stakeholders
  • Business rules expressed in terms that the business can really understand
  • Enabling business and IT experts to collaborate more effectively
  • The ability to change rules easily and quickly
  • Consistency of rules and decision-making

A range of Red Hat customers across various industries are having great success using a rules engine to provide decision services to the organization and keeping business rules separate from application code.

A lot has changed in IT over the past few years that has impacted automated business decision making. In this blog, I will cover three of the major changes that have caused the greatest impact: Cloud, Artificial Intelligence (AI)/Machine Learning (ML), and Robotic Process Automation (RPA).

The Cloud

The cloud has dramatically altered the way we create, deploy, monitor and manage business applications, and that has a tremendous impact on people using business rules engines.

Since the start of IT, organizations have built “Monolithic” applications, which are large, difficult to understand, and challenging and time-consuming to make a change. In the last few years, thanks to the cloud, monolithic apps have been replaced by containers, and microservices architecture, making it easier to create, deploy, manage and change parts of applications. A large app can be broken into smaller components that can be developed, scaled, managed and changed independently from the other components.

The flexibility of containers and microservices simplifies decision-making because rules can be added as components rather than being embedded in the application. In the cloud, rules can modified easily in response to changes in the market or in the way the company does business, and the entire application does not have to be rewritten. This provides businesses with a level of agility they never had before.

Artificial Intelligence (AI)/Machine Learning (ML)

Another set of emerging technologies that is having a major impact on business applications is Artificial Intelligence (AI) and Machine Learning (ML). 

One way of defining ML is “rules that write themselves.” This is obviously a huge leap from where we were 10 years ago. Instead of creating the rules based on your experience and building an app based on those rules, you can now look at historical data, figure out what rules produced those results, and then apply that knowledge to make decisions going forward.

Essentially ML is used for constructing predictive models. For example, with regard to the rules covering when insurance claims are denied or paid, you have data about how you arrived at decisions in particular cases. You could use ML to build predictive models to repeat those decisions in similar cases. 

How do predictive models compare with user written rules in terms of their usefulness and viability for these types of decision applications

  • Rules are created by people, while predictive models are automatically created based on analysis of historical data
  • Rules produce results that are explainable, while predictive models produce results that are not explainable.
  • Rules are subject to human error. One of the challenges with rule-based systems is you get gaps – such as situations you forgot about, or edge cases you did not address. Conversely, predictive models are subject to historical bias. You are limited to reproducing behavior apparent from the training data. So if the data is biased, you get a biased model. 
  • Rules take a significant amount of time to produce, while it is relatively quick to generate a predictive model once you have the data.

The goal when using ML to augment decision making is to combine the advantages of applied rules and predictive models. New rule languages, like Decision Model and Notation (DMN), make this possible by simplifying the process of creating rules.

In the past, rules were created in a complex notation. Thousands of rules leave open many possibilities for error. DMN is a graphical language for encoding rules that make a decision. It makes it much easier for business stakeholders to create the source code for their decision applications. They create a graph to encode complex business logic. Then they can incorporate a predictive model into the DMN diagram, and they can incorporate business rules as well, effectively combing the best of both options

Robotic Process Automation

Robotic Process Automation (RPA) is an exciting, fast moving space right now. With RPA, software robots are developed to perform routine, repetitive work that would otherwise be done by a human worker. The advantages of RPA are all about reducing cost and headcount by automating tasks.

Time spent copying information from a back office database into a spreadsheet, and moving data around from system to system – this is not the type of work where a human worker adds value to the process, but it still has to be done. RPA allows an organization to automate those repetitive tasks. 

One of the best advantages of RPA is that it enables you to automate work without having to change your underlying systems. You can keep your legacy mainframe and other applications exactly as they are. The robot pretends to be a human and carries out the same tasks exactly the same way a human worker would. 

But it is very important to consider RPA as just another software development approach. In future, as RPA evolves, I would expect to see containerized robots roaming around your hybrid cloud. But for now, RPA is just another app and it needs to be managed just like any other app. Version control and QA are very important. 

When you create a bot, beware of the attack surface. You create an opportunity for someone to add a few lines of script to that bot. Think about the damage that could be inflicted by an automated bot with high level access to all your enterprise data. That is a key reason why RPA should be subject to the same governance as any other software.

Also it is very important to understand that the value of RPA is in the ability to automate human work, not to patch holes in IT systems. If you find yourself building bots to fix holes in IT, you really need to take a good look at the infrastructure instead. It is not productive to use bots as band aids, because the bots themselves will continuously break as things change within the infrastructure. It is more productive to focus on fixing the source of the issue in the underlying infrastructure.

For RPA to remain relevant and continue to support software development, bots should be compatible with the cloud, and be able to run in containerized environments. This is technology we expect to see in the next few years or so.

The Red Hat Solution

Red Hat is very active in the software development space and offers a range of tools designed to solve the challenges associated with incorporating rules and decision making into business applications:

  • Red Hat Decision Manager is a platform for developing containerized microservices and applications that automate business decisions. Decision Manager includes business rules management, complex event processing, and support for building DMN models.
  • Red Hat Process Automation Manager is a platform for developing containerized microservices and applications that automate both business decisions and processes. Process Automation Manager includes business process management (BPM), business rules management (BRM), and business resource optimization and complex event processing (CEP) technologies. It also includes a user experience platform to create engaging user interfaces for process and decision services with minimal coding. 
  • For development in the Cloud, Red Hat OpenShift is an enterprise-ready Kubernetes container platform with full-stack automated operations to manage hybrid cloud and multicloud deployments 
  • Red Hat Runtimes is a set of products, tools, and components for developing and maintaining cloud-native applications. It offers lightweight runtimes and frameworks for highly-distributed cloud architectures, such as microservices. 

Robotic Process Automation and Cloud Technology – Challenges and Opportunities

The original article was published on IT Toolbox on July 23, 2019. 

RPA holds incredible promise for organizations looking to drive greater efficiency and cost savings; however, the industry must overcome several crucial challenges before it can truly live up to its potential. This article unpacks those challenges and explores the opportunities ahead.

Robotic Process Automation holds incredible promise for organizations looking to drive greater efficiency and cost savings; however, the industry must overcome several crucial challenges before it can truly live up to its potential. This article unpacks those challenges and explores the opportunities ahead.

By now, you’ve probably heard about Robotic Process Automation (RPA). It is not especially a new idea that’s suddenly gaining attention as businesses strive to become more digital. The promise of RPA is providing quick and significant cost savings through automation of human tasks with software robots. In fact, PwC estimates that “45% of work activities could be automated, and that this automation would save $2 trillion in global workforce costs.”

Challenges Faced by Organizations

Today, there are thousands of software robots automating everything from simple tasks like order entry and invoice preparation, to complex interactions, like issue resolution and customer service. But there are challenges awaiting many organizations, who have rushed to deploy robots.

1. Cloud Infrastructure Challenge:

First, there’s the matter of the cloud. Before RPA came along, those same organizations were busy planning multi-year efforts to reap the benefits of cloud computing. Moving IT to the cloud offers a similarly enticing cost benefit, but it is a long term project, requiring the deployment of new and emerging technologies.

Much has been invested in containers, orchestration, microservice and service mesh architectures, etc., as we lay the foundations for a serverless, data center-less future. However, RPA has some catching up to do. It is still confined to the desktop—the Windows desktop, to be precise.

The majority of software robots currently deployed are of the ‘attended’ type. This means that they exist on your Windows desktop, much like the little ‘Clippy’ assistant in bygone versions of Microsoft Office, where they do things like, move rows of data from a back office database to a spreadsheet, so that you can focus on more important things.

In the recent years, RPA has evolved to enable ‘unattended’ bots to manipulate your enterprise data behind the scenes, on Windows servers. That’s a step in the cloud direction, but still far from the notion of cloud-native bots that can cruise around your hybrid cloud and fix whatever needs fixing.

When will we see containerized bots, orchestrated by standard platforms like Kubernetes and Istio? Well, presumably not until RPA vendors realize the central role that Linux plays in modern cloud architectures. But more importantly, not until RPA goes open source. Why? Because open source software is the central pillar of modern cloud stacks, and if RPA is to have a role in hybrid cloud infrastructure, it must be open source too.

However, today, there is very little in the way of open source RPA. There are a few open source RPA-like projects such as, TagUI, Robot Framework and Sikulix, but these are very bare-bones compared to the market leading proprietary products in the market currently. The opportunity for these proprietary vendors to play in the hybrid cloud market is immense if they can embrace open source business models.

2. Cost Challenge:

The second challenge for users of RPA looking to save on labor costs is that today’s bots just aren’t all that smart. They don’t measure up to their human counterparts in their ability to figure out how to get the job done when some part of it turns out a little differently. Some bots are simple macros, repeating the same series of steps over and over. Others may have a little more intelligence, perhaps a rules engine to handle complex scenarios, but very few have anything close to actual intelligence.

The world of AI and ML is currently separate from RPA, and although some bots may be able to utilise AI services, like IBM Watson, none of them have the in-built ability to learn from past experience so they can do a better job the next time. Consequently, the anticipated cost savings don’t always materialize, and bots can be limited to highly structured and repetitive tasks. Just like with the cloud, though, there is opportunity here. I expect a marriage of RPA and AI/ML will likely happen soon, and will open up a new landscape of possibility for automated business.

3. Implementation Challenge:

Finally, there’s the implementation challenge—how to deploy RPA technology so that it supports your IT strategy rather than hobbles it. It’s easy to be tempted by RPA’s promise of a quick fix into attacking the symptoms of your problems rather than the root cause. Some organizations deploy bots as ‘band-aids’ to relieve bottlenecks in semi-automated processes, when the real problem is an ageing infrastructure that can’t accommodate new business requirements. This may solve the immediate problem, but will continuously break again with every minute change in operating processes, applications or infrastructure. Partly, it’s the ease with which an RPA bot can be deployed that’s to blame. Why go to the trouble of creating APIs for critical applications when it is easier to just have a bot screen-scrape, say, an accounts receivable app to get the one extra data field needed for the new invoices?

The answer, of course, is because this problem is just a symptom of a larger issue within the IT infrastructure, RPA does not fix a spaghetti tangle of applications, data and integration strategies. Organizations with this problem need to focus on building a cloud-native foundation first. Otherwise, if the team continues to throw bots at every new business request, the entire data center will eventually collapse from unmanageable complexity.

Automating Human Work

RPA is a valuable technology when it is used to automate human work, and not to patch holes in IT systems and applications. It is made more powerful when it can integrate effectively into a modern application environment—monitoring events, using cloud services to gather information and interacting with applications via APIs.

The opportunities for automation are huge, but the supporting IT infrastructure is critical. I believe those enterprises that are able to combine a modern cloud-native application environment with open source, intelligent, cloud-native bots will have an unparalleled competitive advantage.

From BPM and business automation to digital automation platforms

The business processes that create customer value are the critical piece that links together all of the different aspects of digital transformation. But still, many of the critical activities that contribute to it are either manual or a succession of disconnected workflows or applications that prevent organizations from having an end-to-end view of how their processes deliver customer value.  

Evolving from workflows to BPM – business process management – added a whole collaborative layer and execution structure to the traditional hierarchy and project-based structure of the enterprise. When it was paired with access to the critical data and documents, alongside activity visibility and business rules, it helped to exponentially grow productivity and agility in the enterprise for many years.

Nowadays, enterprises have discovered already how to use these technologies and apply them to work with structured and unstructured processes, to create business rules to guide and support decision making, or the importance of integrating process outputs and inputs in real time to external systems that interact with the processes. These process-centric applications are even cloud-ready so you can run your processes in the cloud and open them up more securely to all of your internal and external collaborators.

But times are changing. Productivity and agility are no longer the name of the game. It is no longer enough to provide ease of use, business, and IT collaboration, or fast modification of processes and rules. Speed and support for digital transformation have become top priorities. Those process-based applications need to be quickly deployed into production, be portable, reusable and consistent across environments, and scaled in the hybrid cloud. Our customers expect cloud-native technologies at the core of their processes. They expect to run their process workloads to scale across the hybrid cloud to provide a consistent experience to their customers and collaborators. Ideally, they also want to future-proof their investments with modern technologies such as containers.

Continue reading “From BPM and business automation to digital automation platforms”

Meet application integration in the times of hybrid cloud

The concept of agile integration, depending on whom you ask, may appear as a contradiction in terms. Integration is a concept that used to be associated with “slow,” “monolithic,” “only to be touched by the expert team,” etc.. Big and complex legacy enterprise service buses connected to your applications were the technology of choice at a time when agility was not a requirement, when the cloud was barely an idea, when containers were associated with maritime shipping and not with application packaging and delivery.

Can the principles of agile development be combined with those of modern integration? Our response is yes, and we call it  agile integration. Let me show you what it is, why it is important, and what we at Red Hat are doing about it.

Software development methodologies have evolved rapidly in the last few years to incorporate innovative concepts that result in faster development cycles, agility to react to changes and immediate business value. Development now takes place in small teams, changes can be approved and incorporated fast to keep track of the changing demands of the business, and each iteration of the code has a product as the ultimate result. No more need for longer development cycles and never-ending approvals for changes. And importantly, business and technical users join forces and collaborate to optimize the end result.

In addition, modern integration requires agility, cloud-readiness, and support of modern integration approaches. In contrast with the legacy, monolithic ESBs, modern integration is lightweight, pattern-based, scalable, and able to manage complex, distributed environments. It has to be cloud-ready and support modern architectures and deployment models like containers. It also has to provide integration services with new, popular technologies, like API management, which is becoming the preferred way to integrate applications and is at the core of microservices architectures. And support innovative and fast evolving use cases such as the Internet of Things (IoT).

Continue reading “Meet application integration in the times of hybrid cloud”

Red Hat JBoss EAP – a platform for current and future workloads

There is this myth that Java EE containers aren’t fast and agile enough to build modern applications. Although this may be true for some app server vendors, it’s definitely not the case for Red Hat JBoss Enterprise Application Platform (JBoss EAP).  JBoss EAP is a modern application platform that includes a modular structure that allows service enabling only when required, improving startup speed.

With this in mind, we decided to run a comparison between JBoss EAP and other technologies that are touted to be the best for cloud-native applications. Not to our surprise, here are the results:

Note: The performance tests above were produced without any performance optimization, and if you run the tests yourself, you might get different results depending on your hardware and memory. The conclusion from the above results is that JBoss EAP is not slower and does not use more memory than the other runtimes.

When comparing a JBoss EAP instance running Java EE Web Profile app, a JBoss EAP running a Spring application, Tomcat and Spring Boot, you can see that in our tests, JBoss EAP running Java EE Web Profile was faster, used less memory, and had the highest throughput under load. You can find the entire test suite and source code at the following location:

https://github.com/tqvarnst/eap-vs-tomcat-vs-spring-boot

Continue reading “Red Hat JBoss EAP – a platform for current and future workloads”

It’s Time To Accelerate Your Application Development With Red Hat JBoss Middleware And Microsoft Azure

The role of applications has changed dramatically.  In the past, applications were running businesses, but primarily relegated to the background.  They were critical, but more operational in the sense that they kept businesses running, more or less.  Today, organizations can use applications as a competitive advantage.  In fact, a well-developed, well-timed application can disrupt an entire industry.  Just take a look at the hotel, taxi, and movie rental industries respectively.

This can put more pressure on IT leaders.  Not only do they have to continue to run their daily business as efficiently as possible, but may also need to liberate resources to help drive innovation.  In other words, “do more with less.”  As a result, many are looking at ways to increase productivity and some are turning to modern development tools such as DevOps, containers, and microservices.  When making strategic decisions such as these, the technology, and infrastructure, should adapt to the needs of the business. Both now, and in the future.

When talking about infrastructure that can evolve as the business evolves, the answer is often the cloud.  However, when assessing application development technology that provides flexibility and enables IT leaders to better anticipate needs, it becomes a little more vague.  This is where Red Hat and Microsoft can come in.

Microsoft and  Red Hat have teamed up to offer Red Hat JBoss Enterprise Application Platform (JBoss EAP) on Microsoft Azure.  JBoss EAP is a modern application server that is designed to provide a modular cloud-ready architecture, powerful management and automation, and developer productivity. It offers support and deployment flexibility for Java EE, whether on-premise, virtual, or hybrid cloud environments. In addition, JBoss EAP is designed to fulfill the demands of modern applications in the areas of process, infrastructure, and architecture by delivering support for DevOps, hybrid cloud, and microservices, respectively.

JBoss EAP is  the cornerstone of Red Hat’s focus on and commitment to enterprise application development, and serves as the foundation for Red Hat’s portfolio of cloud-ready middleware products.  A portfolio that includes technology business rules (BRMS) and business process management (BPMS) capabilities. Combined with Microsoft’s enterprise-grade cloud computing platform, collectively, these solutions can deliver a diverse, open, lightweight, enterprise capable application development platform.

SCSK Corporation is a Japanese system integrator that designs and implements Internet of Things (IoT) solutions. The company used Red Hat JBoss BRMS to develop its own IoT platform, which it offers on Microsoft Azure, that is designed to filter, store, analyze, and visualize data sent from devices and sensors. Organizations can analyze large volumes of IoT data to help make better  business decisions. This requires a more reliable, scalable, and robust platform.  When asked if JBoss BRMS was chosen because of its complex event processing (CEP) engine, Naoaki Kato, Engineer in the SCSK Middleware Unit responded: “Yes, but there was one more important factor: the fact that it is a Red Hat product. Red Hat products have a strong track record in the enterprise market, and Red Hat offers great support.”

I had the privilege of  discussing the partnership with numerous attendees at Microsoft Ignite 2017 and believe that the partnership has been well received.  To wrap with another quote from Naoaki Kato, SCSK: “The Microsoft–Red Hat partnership was really great news for the enterprise market.”

* The use of the word ‘partnership’ does not mean a legal partnership or any other form of legal relationship between Red Hat and Microsoft.

Red Hat partners guide your journey to cloud-native development

The big question is always, “Do we car manufacturers learn to become tech companies more quickly than a tech company learns to be an automotive player?”

That is quite a statement. When a leading car manufacturer worries about being disrupted by a technology company, you know something big is going on. No wonder so many companies are talking about disruption these days.

There is a big transition taking place. And it is not just about competition. Or innovation. Or value migration. Or the creation of new markets. It is about the fact that every company is becoming a technology company, and only those that embrace this will survive, thrive, and shape our world. Software is at the core of this change, and increasingly it appears that the cloud is where much of this is going to take place.

Customers often come to us asking, “How can I be faster? How can I innovate and lead, instead of repeat and follow? How can I do that with enterprise-grade security, reliability and resiliency?”

A good part of the answer lies in using the cloud to power business models and help run, migrate, or scale existing applications, or develop new cloud-native ones. Red Hat has offered platforms to run customers’ applications and infrastructure in the cloud for a number of years. Today, we are taking another step forward by offering cloud-native application runtimes and frameworks, fully supported and enterprise grade.

Red Hat OpenShift Application Runtimes offers a curated selection of popular cloud-native application runtimes and frameworks that are well-suited for enabling cloud-native application development.

In the words of Joe Dickman, senior vice president of Vizuri, “Red Hat OpenShift Application Runtimes establishes a foundation for building services for hybrid and multi-cloud application and systems […] in a myriad of environments using their preferred tools.”

With Red Hat OpenShift Application Runtimes, organizations can innovate directly in the cloud, from inception to production; running in the industry’s most comprehensive Kubernetes platform, Red Hat OpenShift Container Platform, and in a cloud provider of choice.

James Chinn, CEO at Shadow-Soft, adds: “With Red Hat’s latest support of Wildfly Swarm, Spring Boot, and NodeJS, our customers can feel confident building and scaling containerized workloads on OpenShift. Openshift deployed in a public cloud gives our customers the flexibility and agility to deploy an enterprise and container framework quickly and easily.”

When customers develop an application strategy for moving to the cloud, they have to choose the right runtimes, based on factors such as existing skills or the right framework for the application they need to create.

“Historically, one of the biggest challenges has been the roadmap necessary for change in legacy environments,” says Chris Hart, chief technology officer of Levvel. “OpenShift Application Runtimes helps simplify that transformation and lowers the effort and risks to getting started with cloud-native development.”

They need to decide which applications to move to the cloud and how to keep evolving and innovating. What applications get a lift-and-shift (rehost) versus reshape or re-architect? Should they create “fast monoliths” or decompose them, totally, or partially, as microservices? If so, what is the right framework for the job?

Erik Melander, EVP of solutions at Kovarus, expands on this: “Red Hat OpenShift Application Runtimes […] reduces friction by packaging and supporting a curated set of open application runtimes and letting developers make the right choice for cloud-native development.”

It is also important for them to learn about containers and how to implement DevOps methodologies and culture. Development and operations teams may need to learn new skills and change the way they work.

We are happy to have a large network of partners around the world with the expertise to support our customers along the exciting path of going to the cloud. From the top level strategy and innovation consulting, down to the most detailed testing and infrastructure set up. From defining and helping implement an application modernization strategy, to helping implement and deploy a microservices architecture.

Red Hat solution systems integrators and solution providers can help select the right option based on the technical objectives, existing skills or strategy. They can also help customers prepare for the challenges of complex microservices architectures and equip an organization to adopt DevOps practices and culture.

Start your journey here!

Supporting quotes:

“For our customers that are developing applications to create and sustain competitive advantage, developer productivity is an ever-present challenge. We are excited to see Red Hat addressing this problem with the launch of Red Hat OpenShift Application Runtimes, which reduces friction by packaging and supporting a curated set of open application runtimes and letting developers make the right choice for cloud-native development.”
Erik Melander, EVP of Solutions at Kovarus

“We’re excited about Red Hat OpenShift Application Runtimes because it simplifies the adoption of beneficial technologies for our enterprise customers. Many companies know they need to achieve higher release velocity and improved reliability using approaches like microservices architecture and more modern development and operations tools. Historically, one of the biggest challenges has been the roadmap necessary for change in legacy environments. The OpenShift Application Runtimes help simplify that transformation and lowers the effort and risks to getting started with cloud-native development. We’re looking forward to seeing this accelerate our customers’ success.”
Chris Hart, Chief Technology Officer, Levvel

“We are excited about the announcement of Red Hat OpenShift Application Runtimes as it signals Red Hat’s continual commitment to meeting our customers where they are today and positioning them for success in the future. With Red Hat’s latest support of Wildfly Swarm, Spring Boot and NodeJS, our customers can feel confident building and scaling containerized workloads on OpenShift. Openshift deployed in a public cloud gives our customers the flexibility and agility to deploy an enterprise and container framework quickly and easily. And like any public cloud deployment, you can start small and scale elastically as workloads demand.”
James Chinn, CEO, Shadow-Soft

“Organizations that are investing time and resources in cloud-native architectures must look at leveraging containerized workloads to provide a robust, flexible and reliable infrastructure that can respond quickly to changing customer needs. Red Hat OpenShift Application Runtimes establishes a foundation for building services for hybrid and multi-cloud application and systems in a programmable way that provision and decommission infrastructure and applications resources in a myriad of environments using their preferred tools.”
Joe Dickman, Senior Vice President, Vizuri

 

Announcing Red Hat Fuse Online Technical Preview

On May 2, 2017, we announced a new open source project called Syndesis.io. Syndesis.io provides a low code environment for agile integration. We also demonstrated key capabilities at the Red Hat Summit 2017 keynote.

Building on our foundational work in Syndesis.io, we have expanded those capabilities into a new product and are happy to announce Red Hat Fuse Online as a technical preview.

Continue reading “Announcing Red Hat Fuse Online Technical Preview”

Introducing OpenShift Application Runtimes Public Beta

Executive Summary

  • Red Hat OpenShift Application Runtimes is now in public beta, meaning you can try it!
  • Red Hat OpenShift Application Runtimes includes a collection of supported application runtimes.
  • Each runtime is designed to simplify cloud-native development by using Red Hat OpenShift capabilities in a manner natural to the language runtime.
  • Try it! Go to developers.redhat.com/rhoar. Choose an example and runtime, and watch it get forked to your github account and deployed to OpenShift. Feedback welcome on StackOverflow.

Continue reading “Introducing OpenShift Application Runtimes Public Beta”

There is no magical OFF switch for legacy apps

I really dislike the term “legacy apps,” especially when it is used by vendors. It feels like they are calling my baby (i.e. my app) with a bad name.  I love the quote by Martin Fowler, “All we are doing is writing tomorrow’s legacy software today.”  I am certainly not advocating to stick to your old applications forever.  All applications and systems have a life-cycle that goes from build to retire. Somewhere in between lies the stage of renewing the capabilities of the system, often named as modernization, enhancement, or rehab. This is the most important phase from the perspective of extending the life of the application and enhancing the long term value harvested from it.

In IT, each generational transition has called for modernizing and redesigning applications, business processes and IT infrastructure to exploit new technologies’ capabilities and efficiencies. App modernization isn’t carried out as a fashion statement or status symbol but for hard business reasons. Regardless of the era, the benefits of a periodic app overhaul include better performance, more features, greater usability, and higher reliability.

Continue reading “There is no magical OFF switch for legacy apps”

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