One of the challenges of IT management is to balance the enterprise portfolio with initiatives that deliver on objectives and outcomes with varying timeframes and differing investment categories. Yet this balance is key to run, grow, and transform the business now and over time.
Balancing the enterprise portfolio is important to deliver on initiatives within short (within the fiscal year), medium (1 to 2 years) and long (over 2 years) timeframes. This is part of the advice for a lean startup.
Source: Gartner PPM & IT Governance Summit 2016 – Secrets of Prioritizing IT Demand – Audrey Apfel
As always, the “Internets” is a fascinating place (assuming a massive denial of service attack hasn’t cut you off from Twitter and Spotify) and there is a new trend in the things I was clicking. This is probably inspired by my recent obsession with Westworld, but I have been thinking in general about the essence of reality and how far technology can go to both conceal reality and create it. So this week’s theme is reality-bending technology: virtual reality, augmented reality, artificial intelligence, and the technologies behind it.
I had the pleasure of meeting my colleague, Steve Willmott, at the Red Hat booth at the Gartner ITXPO Symposium where we had a chance to have some insightful discussion about API Management — how it has evolved, where it is headed and its usage patterns etc. API Management is one of the techniques I called out during my session on the Relevance of Innovation at the Gartner symposium where I had made the point about the need to modernize integration techniques themselves over and above the modernization of infrastructure and applications. Just like I had made the point about “Integration is dead! Long live integration”.
To effectively plan and execute a technology-driven service or product offering, IT and business leaders should start with business architecture. Business architecture is the essential building block for mapping an organization’s business vision of what they want to accomplish. Business architecture is one of the four enterprise architecture domains – including data, applications and technology.
This has been a cool week on the web, and I noticed a trend in the things I was clicking. I saw a lot of articles and images that show relationships — mainly with the Internet of Things (relationships between devices, software, and people), but a couple of interesting ones on group dynamics.
This deserves the top spot because of how counterintuitive it is, but the post makes some excellent points about how to get group ideas more effectively. Along with pointing out a lot of the pitfalls of group brainstorming sessions, it also has advice on how to be more effective in eliciting the best ideas from a group — including creating time for independent brainstorming, providing better structure to the process, and having a final decision.
It was a great day in Minneapolis! The Microservices with Apache Camel was held at Target Field (inside the ballpark, overlooking the field of play). “Takes a lot to put together an event like this but can certainly be a lot of fun! Go microservices!,” says Red Hat associate Jen Fissel.
I had the privilege of hosting the event and kicked off the event with a reference to the connected world we live in that requires enterprises to be agile while being integrated across the systems of yesterday with the evolving applications of the future. The future of Enterprise IT, containers, are here today and microservices are the stars of the show. Welcome to Minneapolis!
Does your organization need to reduce costs and improve efficiencies? Start with a process-first approach. Before you dive into what software tool to implement or select a new solution to address a business challenge, understand your existing business processes. What steps does your organization take within the business processes? Are things manual? Can you automate and improve the way you do business?
The way the MEAP works is that every month or so Manning puts a new chapter online. As of this week chapter 5 is available and those already in the MEAP will have access to start reading the chapter.
This is a large chapter and it is one of the harder topics to confine to a single chapter. I do expect to split this chapter up in the future so that you have the basics and then more advanced topics regarding learning to effectively implement your business logic with JBoss BPM.
To give you an idea of what’s available so far:
You can read this excerpt online before you decide, but I look forward to hearing from you on the content and stay tuned for more.
Your business needs to better use its data — but what does that mean? Context matters. Data governance, reporting and analytics, business intelligence. When you approach your data architecture, first start with asking the right questions that solve business challenges. What data does the sales team need to increase sales by x %? What data does the engineering team need to work on and innovate products that provide competitive advantage?
Similar questions have inspired companies to disrupt markets. Uber started with asking questions like, how can we optimize drivers at the right locations with the most customer demand? How can we give consumers the ability to call a cab with a click of a button? Tomasz Tunguz highlights similar examples in his book Winning with Data, where he states that “the best data-driven companies operationalize data.” To operationalize data is where companies can use the right data to rapidly change the way they operate.
In order to use the right data, ask the right questions. Gartner states exactly this, “Ask the right questions” in the 2015 article Big Data Analytics Failures and How to Prevent Them. Simply, what problem or toughest business challenge is your company trying to solve with data?
At the foundation and beginning practice of enterprise architecture, dating back to the 70’s with the Zachman Framework, the principle question related to data was “what data is needed to list the things most important to the business?” The framework focuses on the “what”, what is needed, in order to produce the right enterprise, data and technology models for the best use of data.
In order to harness the “Power of Data”, HBR suggests that companies start with the business problem in mind, and then “seek to gain insights from vast amounts of data.” With stating the specific business problem, companies can narrow the search and refine how they are going to find data-driven answers to their most challenging business problems.
Red Hat Developers and author N. Harrison Ripps have just begun releasing a ten-part series in which Harrison describes the process of deploying an application using containers into a clustered environment on the cloud.
Using the ZRC IRC client as a sample application, Harrison demonstrates each step in the process of containerizing software, dealing with issues like statelessness, security, and robustness that are typically architectural hurdles for most development teams moving to a cloud infrastructure.
Parameterizing application settings is a common requirement of applications that end up deploying to any environment, and containers have only heightened this need — with the emergence of on-demand environments, scriptability and configurability of the application images being deployed is a must.
Harrison suggests that containerizing applications should happen later, while development should happen first. This might seem intuitive, but his point is that containerizing an application actually need not introduce many development-time changes that would affect the architecture of your system — it can, but it need not. For a small sacrifice of startup performance, container images can be made more configurable and flexible, supporting DevOps procedures and deployments.
Once configured, the series also demonstrates how to host the application on a private instance of the OpenShift Container Platform, including clustering, via either the Red Hat Container Development Kit (CDK), or binary download of OpenShift. Harrison goes step-by-step through the process of starting the private cloud, deploying the application, and using Kubernetes to cluster the application.
Using attached storage, Harrison introduces a window of statefulness into our container environment. This produces an application that runs on the cloud in stateless containers, but maintains its internal state throughout the lifecycle as pods are brought up and down.
Follow along and learn some of these core cloud concepts as the series is published: