Every transition has its growing pains, and bimodal IT is no exception. The term, coined by Gartner, Inc. in 2014, has taken on a life of its own as many have adapted the concept for their own ends. This has resulted in confusion and, in some cases, disillusionment.

Well, no one said transitioning to a more dynamic and continuous process would be easy, and there’s no guarantee of success – merely a set of recommendations for the journey. However, failure, fear and skepticism should not give people license to remain stuck in their legacy systems or rush headlong into change. Let’s examine what this term “bimodal IT” actually means, how it is a step in the IT Transformation, and how do we ease the pain of transition.

What Does Bimodal Mean, Again?

Gartner defined this process within IT infrastructure and operations as “the practice of managing two separate but coherent styles of work: one focused on predictability, the other on exploration.” Mode 1 focuses on predictability and has a goal of stability. It is best used where requirements are well understood in advance, and can be identified by a process of analysis. It includes the necessary investment in renovating and opening up the legacy environment. Mode 2 is exploratory. In this case, the requirements are not well understood in advance. Mode 2 is best suited for areas where an organization cannot make an accurate, detailed, predefined plan because not enough is known about the area. Mode 2 efforts don’t presume to predict the future but allow the future to reveal itself in small pieces. Gartner ended its original, short definition with, “Both play an essential role in the digital transformation.”

Transformation is the key term here; it connotes movement toward a different state, not a permanent position. Bimodal IT creates two separate groups that work at different speeds on segregated systems. It is typically characterized by a Waterfall vs. Agile scenario. Waterfall methodology follows linear, sequential development with distinct goals for each phase. By contrast, Agile processes seek to help teams respond to unpredictability through incremental, iterative work cadences and ongoing feedback. This two-speed method may be the current de facto way of doing things and may remain this way for a while, but slowly and steadily, IT is undergoing massive and fundamental transformation to address customer and enterprise needs for agility.

Enablers of Rapid Change

Whereas it used to take up to a year to release an upgrade or new version, it’s now common to see bi-weekly, weekly,  and in some cases daily releases. What accounts for such a radical change in delivery speed? There are five over-arching trends contributing to IT transformation:

  1. Cloud services, such as Amazon, Azure and Google, have been gaining prominence by providing end-to-end services for application development and deployment. Private cloud environments are becoming commonplace as well. This leads to dynamic and agile application life cycle management.
  2. Continuous delivery and integration (CD/CI) that makes sure code is maintained in a deployable state. While thousands of developers make changes, detailed hardening and testing phases are eliminated leading to incremental testing and faster delivery.
  3. The DevOps movement, which is related to CD/CI, whereby developers and operations team are becoming more collaborative and working together. Hybrid DevOps models are coming into play in which operational staff are being embedded into development teams in the interim.
  4. Agile methodology aids in more customer-driven and faster development of software and may enable CD/CI. However, an organization doesn’t have IT transformation solely by adopting Agile methodology.
  5. Dynamic and scalable technologies and architectures like micro-services architectures that help products and services be developed incrementally, scale better and lend these products well to CD/CI. Investment in containers and virtualization has also helped this trend. These architectures are also dynamic and ever changing with application components that come and go. Containers are quite short-lived, with—on average—one-sixth the lifetime of virtual machines.

Underlying infrastructure begins to feel the strain of this acceleration of development; it poses new challenges to IT Operations teams. It requires teams to manage unparalleled amounts of data while predicting and preventing outages, in real time, and maintaining and delivering agile, reliable applications. This increased complexity makes some organizations fearful about transitioning from Mode 1 to Mode 2 completely, as concerns over new processes and operational complexity loom. In order to ensure availability, reliability, performance and security of applications in today’s digital, virtualized and hybrid-cloud environments, new approaches must be employed to provide operational intelligence to ease the transition from Mode 1 to Mode 2.

Make Change Less Painful

Gartner opened the dialog about bimodal IT to offer the concept of creating a transitional space so that organizations can transform and innovate without crashing and burning. The reason that Agile was created, for instance, was to enable a faster, more responsive process than waterfall practices can offer. However, switching to continuous delivery and integration mode too quickly could prove disastrous for certain systems, as some change carries more inherent risk than others. Following are three best practices to help ease the transition and ensure that applications continue to run at optimal levels.

  • The infrastructures that undergird today’s applications, whether in Mode 1 or Mode 2, are more complex and dynamic than ever, with underlying resources constantly changing to meet these applications’ performance requirements. You need visibility into all your data—including performance data, logs and topology—and the ability to visualize all layers of your application infrastructure stack in one place at any point of time. This allows you to identify the root cause of an outage or performance degradation in the past or the present. These tools can also provide the capability to understand the impact of a software release on the operations in the Continuous Delivery and Integration mode (Mode 2). In the absence of such tools, conducting definitive post-mortem analysis is a costly, manual and confusing process – if it can be done at all.
  • Then there is IT’s big data problem. Relying solely on traditional IT monitoring tools that trigger numerous alarms makes the job of IT operations teams even more difficult. Understanding all the raw data to make intelligent decisions in real time and sifting through the sea of alarms and telemetry data at the same time poses major challenge to IT operations teams. AI—especially machine learning—is well suited to take all the data and generate the necessary operational intelligence to distinguish critical, service-impacting events from false positives that do not require the immediate attention of an operator. As IT transitions, you need IT operations intelligence that can handle both modes of operations.
  • Prediction has become the key to preventing outages. A twin problem to the one above is that traditional monitoring tools trigger alerts only after a problem has already occurred. Look for solutions that incorporate predictive analytics to alert you to anomalous trends or potentially dangerous issues before they impact your application.

To make the transition from Mode 1 to Mode 2 easier and more manageable, automated solutions that analyze and provide insight into ever-changing applications and infrastructure topologies are essential. Equipping users with the ability to replay and analyze past incidents and to pinpoint performance degradation and root cause, while cutting out the noise and preventing future costly outages and downtime, is important to facilitate the transition. This operational intelligence connects enterprise DevOps and TechOps teams, giving them what they need to quickly address issues as they arise.

Embracing the Journey

It’s clear that organizations cannot continue in the “same old, same old” manner of operating. Digital transformation is essential, but it can be messy and confusing. IT teams need to carefully evaluate which aspects can proceed to Mode 2 and which ones need to remain in Mode 1 for the time being. Bimodal IT is not a destination in itself but part of the journey toward uni-modal IT that is continuous, dynamic and agile.


About the Author:

jf-headshot-3J.F. Huard, Ph.D., founder and CTO of Perspica, is a hands-on leader in analytics, platform integration and enterprise system management software with a strong ability to communicate with business and technical experts. He is passionate about product design, architecture and technology and has demonstrated experience in growing and managing technical organizations of various size and scope. Huard is an accomplished product manager and engineering manager, delivering on time and specification. He is a result-oriented professional recognized for taking on major initiatives, adapting to rapidly changing environments, and resolving mission-critical issues impacting bottom line success.

His work and research interests focus on the application of statistics to data center and communications networks with quality of service delivery guarantees. He has a special interest in the resource optimization of algorithms for very large-scale problems, as well as in the development of new products that uses mathematics under the hood.

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