Five Links: The More You Know Edition

Happy Friday, everyone.

There have been a couple of events lately that, at least tangentially, made me think about information and what we do with it. There have been a series of DDOS attacks on popular sites, at least one of which was driven by a blind army of smart devices. The other is the volatile and ultimately inaccurate polling leading into the US Presidential election. Both of these hint at the Wild West nature of technology — its flexibility and newness offers a lot of promise and a lot of unknown risks. So the theme for this week is — what is the quality of data and analytics and how do we do it “right.”

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Intro to Integration

Integration is one of those concepts that is easy to “know,” but becomes less obvious that more you try to define it. A basic, casual definition is making different things work together. The complexity, though, comes from the fact that every single part of that has to be broken down: what are the “things,” what are they doing that makes them “work together,” how are they working, and what is the goal or purpose of them working together. All of those elements can be answered differently for different organizations, or even within the same organization at different times.

An understanding of integration comes from looking at the different potential patterns that you can integrate and then defining the logic behind the integration so you can select the right patterns for your environment.

Integration Patterns

Integration itself is an architectural structure within your infrastructure, rather than an action or specific process. While getting various systems to work together has long been an IT (and organizational) responsibility, integration as a practice became more of a focus in the early 2000s. With emerging large-scale enterprise applications, there became a growing need to get those applications working together without having to redesign or redeploy the applications themselves. That push became integration.

Integration is subdefined by what is being integrated; these are the integration patterns.

There are different types of patterns, depending on perspective. There are patterns based on what is being integrated and then there are patterns based on the topology or design of the integration. Basically, it’s the what and the how.

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Upcoming Webinar: Migrating to Open Source Integration and Automation Technologies

Balaji Rajam (principal architect) and Ushnash Shukla (senior consultant) from Red Hat will be conducting a webinar about the ability to integrate data from disparate sources with people and processes. This is a crucial part of strategies for data integration.

Data is increasingly moving from being an asset within an organization to one of the key business drivers and products, regardless of industry. The ability to integrate data from disparate sources is a crucial part of business digital strategy. Many organizations have been locked into proprietary and closed software solutions like TIBCO, but as the IT environments transform again into microservices, agile, and cloud-based infrastructures, those proprietary systems may not be able to keep up – or it may be too cost-prohibitive to try. Open source offers standards-based approaches for application interoperability with potentially lower costs and faster development times. This webinar looks at three key aspects of effectively moving from proprietary to open source solutions:

  • Recommendations for migrating from TIBCO to open source applications
  • Performing data integrations
  • Defining automated business processes and logic

Registration is open. The webinar is August 9 at 11:00am Eastern Time (US).

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Fun Follow Up: Webinar Q&A

I will collect any questions asked during the webinar, and I’ll do a follow-up post on Friday, August 12, to try to capture the most interesting questions that arise.

New styles of integration are the hallmark of Digital Transformation

New Styles of Integration 2

Shakeup your integration strategy to enable digital transformation, says VP & Gartner Fellow Massimo Pezzini. Pezzini asserts that it is not just about transforming and modernizing the infrastructure and the applications concerned.  Some of the fundamental concepts of integration need to be revisited and transformed as well.  Such systemic transformation punctuate the migration of  legacy environments to microservices and the cloud.  What may have worked in the past will no longer be applicable going forward.  “Integration is dead.  Long live integration,” screamed the title of one of the sessions at the Red Hat Summit 2016.  The session was making a point.  Integration, as we knew it a few years back, is dead.  Integration in the digital world has a long life in the decades ahead.  Join me as I walk through the new styles of integration that are the hallmark of digital transformation.

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Visualizing Integration Applications

Since I’ve changed roles and started performing architect duties, I have to draw more boxes and arrows than write code. There are ways to fight that, like contributing to open source projects during sleepless nights, POCs, demos, but drawing boxes to express architectures and designs is still big part of it. This post is about visualizing distributed messaging, SOA, microservices applications in agile environments (this term has lost its meaning, but there is not better one in this case). What I like about the software industry in recent years is that the majority of organizations I’ve worked with value the principles behind lean and agile software development methodologies. As long as it is practical, everyone strives to deliver working software (rather than documentation), deliver fast (rather than plan for a long time), eliminate waste, and respond to change. And there are management practices such as scrum and kanban, and technical practices from extreme programming (XP) methodology such as unit testing, pair programing, and other practices such as CI/CD and DevOps to help implement those principles. In this line of thinking, I decided to put together a summary of the design tools and diagrams I find useful in my day to day job while working with distributed systems.

Issues with 4+1 View Model and Death by UML

Every project kicks off with big ambitions, but there is never enough time to do things perfectly, and at the end we have to deliver whatever works. And that is a good thing, it is the way the environment helps us avoid gold plating and supports principles like YAGNI and KISS, so we do just enough and adapt to changes.

Looking back, I can say that most of the diagrams I’ve seen around are inspired by the 4+1 view model of Philippe Kruchten which has logical, development, process and physical views.

4+1_Architectural_View_Model
4+1 View Model.  From A Practical Guide to Enterprise Architecture by James McGovern, Scott W. Ambler, Michael E. Stevens, James Linn, Vikas Sharan, Elias K. Jo, 2003.

I quite like the ideas and the motivation behind this framework: using separate views and perspectives to address specific set of constraints and targeting the different stakeholders. That is a great way of describing complex software architectures. But I have two issues with using this model for integration applications.

Diagram Applicability

Typically these views are expressed through a unified modeling language (UML), and for each view, you have to use one or more UML diagrams. If I have to use 15 types of UML diagrams to communicate and express a system architecture in an accessible way, it defeats the purpose of UML.

Death by UML
Death by UML. From Wikipedia, derived from a diagram by Paulo Merson.

With such a complexity, the chances are that there are only one or two people in the whole organization who have the tools to create and ability to understand and maintain these diagrams. And having hard-to-interpret, out-of-date diagrams is as useful as having out-of-date documentation. These diagrams are too complex and with limited value, and very quickly they turn into a liability that you have to maintain rather than an asset expressing the state of a constantly changing system.
Another big drawback is that the existing UML diagram types are primarily focused on describing object-oriented architectures rather than pipes and filters architectures. The essence of messaging applications is around interaction styles, routing, and data flow rather than structure. Class, object, component, package, and other diagrams are of less value for describing pipes and filters based processing flows. Behavioral UML diagrams such as activity and sequence get closer, but still cannot express easily concepts such filtering and content based routing, which are a fundamental part of integration applications.

View Applicability

Having a different set of views for a system to address different concerns is a great way of expressing intent. But the existing views of the 4+1 model don’t reflect the way we develop and deploy software nowadays. The idea of that directional flow — that you have a logical view first, which then leads to development and process views, and those lead to a physical view — is not always the case. The systems development life cycle is not following the traditional (waterfall) sequence of requirement gathering, designing, implementing, and maintaining.

2000px-CPT-SystemLifeSycle.svg
Software Development Lifecycle. Derived from an image by Web Serv

Instead other development methodologies such as agile, prototyping, synchronize and stabilize, and spike and stabilize are used too. In addition to the process, the stakeholders are changing too. With practices such as DevOps, developers have to know about the final physical deployment model and the operations team have to know about the application processing flows.

Modern architectures such as microservices affect the views too. Knowing one microservice in a plethora of services is not very useful. Knowing too much about all the services is not practical either. Having the right abstraction level to have a system wide view with just enough details becomes vital.

Practical Visualization for Integration Applications

The closest thing that has been working for me is described by Simon Brown as the C4 model. (You should also get a free copy of Simon’s awesome The Art of Visualising Software Architecture book). In his model, Simon is talking about the importance of a common set of abstractions rather than common notation (such as UML) and then using simple set of diagrams for different level of abstractions: system context, container, componentand class. I quite like this “outside-in” approach, where you first have 10000 foot view and with each next level, going deeper with more detailed views.
C4 is also not an exact match for middleware/integration applications either, but it is getting closer. If we were to use the C4 model, then the system context diagram would be one box that says ESB (or middleware, MOM, or microservices) with tens of arrows from north to south. Not very useful. The container diagram is quite close, but the term container is so overloaded (VM, application container, docker container) which makes it less useful for communication. Component and class diagrams are also not a good fit as pipes and filter architectures are focused around enterprise integration patterns, rather than classes and packages.
So at the end, what is it that worked for me? It is the following three types of diagrams which abbreviate as SSD (not as cool as C4):  system context, service design, and deployment.

System Context Diagram

The aim of this model is to show all the services (whether they are SOA or microservices) with their inputs and outputs, ideally having the external systems on the north, the services in the middle section, and internal services in the south. Or you could use both external and internal services on both side of the middleware layer as shown below. Also having the protocol (such as HTTP, JMS, file) on the arrows, with the data format (XML, JSON, CSV) gives useful context too, but it is not mandatory. If there are too many services, you can leave the protocol and the data format for the service level diagrams. I use the direction of the arrow to indicate which service is initiating the call rather than the data flow direction.

System Context Diagram
System Context Diagram

Having such a diagram gives a good overview of the scope of a distributed system. We can see all the services, the internal and external dependencies, the types of interaction (with protocol and data format), and the call initiator.

Service Design Diagram

The aim of this diagram is to show what is going on in each box representing a middleware service from the system context diagram. And the best diagram for this is to use EIP icons and connect those as message flows. A service may have a number of flows, support a number of protocols, implement real time, or batch behaviour.

Service Design Diagram
Service Design Diagram

At this level, we want to show all possible data flows implemented by a specific service, from any source to any destination.

Deployment Diagram

The previous two diagrams are the logical views of the system as a whole and each service separately. With the deployment diagram, we want to show where each service is going to be deployed. Maybe there will be multiple instances of the same service running on multiple hosts. Maybe some services will be active on one host, and passive on the other. Maybe there will be a load balancer fronting the services.

Deployment Diagram
Deployment Diagram

The deployment diagram is supposed to show how individual services and the system as a whole relates to the host systems (regardless whether that is physical or virtual).

What Tools Do I Use?

The system context and the deployment diagrams are composed only of boxes and arrows and do not require any special tools. For the service design diagram, you will need a tool that has the enterprise integration pattern icons installed. So far, I have seen the following tools with EIP icon support:

Other development tools that could be also used for creating EIP diagrams are:

A system context diagram is useful to show the system wide scope and reach of the services, a service design diagram is good for describing what a service does, and a deployment diagram is useful mapping all that into something physical.

In IT, we can expand work and fill up all the available time with things to do. I’m sure given more time, we can invent ten more useful views. But without those basic three, I cannot imagine describing an integration application. As Antoine de Saint-Exupery put it long ago: “Perfection is finally attained not when there is no longer anything to add but when there is no longer anything to take away.

Summit Preview: Integration Highlights

It is almost time for Red Hat Summit, in lovely San Francisco. Are you ready? You still have time to register!

I am doing a handful of preview posts. The session list is amazing, with about a dozen different tracks or focus areas, everything from application development (the heart of middleware) to cloud to systems management to storage. There are so many gems in these sessions; if you can attend, try to hit these. And if not — keep an eye out on the Summit page and social channels like Vimeo and YouTube. A lot of presentations post recordings or slide decks after Summit, and there is an incredible variety of information.

Today, I want to look at integration paths. There are a lot of really diverse and complex topics here, being broken down into real-life examples, things like data virtualization, API management, integrating data streams from multiple sources and protocols.

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Building an API-Based Connected Healthcare Solution: Q&A Followup

Christina Lin (a technology evangelist for Red Hat) and Sameer Parulkar (middleware product marketing manager for Red Hat) conducted a webinar earlier this week about data integration challenges which specifically face healthcare providers. As promised, this is a brief roundup of the major questions that came out of the webinar and pointers to more detailed information about the demo. (If you would like more background on integration challenges in healthcare, we do have posts on integration architecture for healthcare and another on how to overcome integration challenges.)

A Quick Summary

The recording of the full webinar is available here, but I’ll summarize it briefly if you can’t watch it yet.

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The Core Value of Integration

There is a new Red Hat infographic that summarizes the benefits (and power) of integration. I am only using excerpts here because it is a large-ish infographic, and it’s definitely worth viewing the whole thing. This is just a taste. (Even better, download the underlying whitepaper; it is very much worth reading.)

value-fuse-integration

The headline-making numbers come down, not surprisingly, to cost-savings:

  • 488% ROI in three years
  • Payback in 8.2 months
  • Over $1.4 million in annual savings

The most interesting thing that I saw is definitely part of that headline, but it’s a smaller part of it — over half ($838,800) of those annual savings come from making your IT staff more productive. When an application is integrated, it requires about 41% fewer staff to maintain it. There is a lot a variation here (defining integration is a whole ‘nother blog post) but the idea of saving money, increasing individual productivity, and reducing the staff to maintain applications doesn’t necessarily translate into cutting costs or reducing staff. The power of that, the core value of integration as I read it, is reallocating those precious resources to different operations for your company. Instead of keeping your current apps running, you could have a lot more available people and space to try to do new things, to reinvest in what your company does and move forward.

That’s pretty cool.

Messaging: The Underappreciated Element of Integration

Many people take integration messaging for granted, and many organizations assume that any messaging platform is as fully featured as any other. But in today’s increasingly connected world, with the emergence of major trends in consumer and enterprise technology like mobile, cloud computing, big data, and the Internet of Things, your organization needs to carefully review its messaging platforms and capabilities if you hope to continue to reliably serve your customers and deliver and maintain critical advantages over your competition.

To illustrate how vital and varied messaging platforms can be, let’s explore what exactly messaging is and compare several different approaches to meeting your organization’s messaging needs.

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Red Hat announces availability of containerized middleware capabilities on OpenShift

A little more than two years ago, we announced Red Hat’s “xPaaS” initiative to provide Red Hat JBoss Middleware on OpenShift and introduce a new way of building and deploying enterprise applications. Our efforts in executing against that vision and roadmap have entailed a lot of work and have been very exciting.

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