The New Normal: How to Develop Mission-Critical Apps and Integrations Faster

 During the first six months of COVID, IT leaders and their CIOs came to the stark realization that their “rapid development” practices and paths to deploy minimally viable workflow applications weren’t fast enough. They needed apps developed, tested, and deployed in weeks, not quarters, and coding them from scratch was not a viable option.

Many IT leaders adapted to the dire circumstances and found ways to build apps to solve their immediate needs using low-code application development tools.

Today, some parts of the world are beginning to experience “the new normal” where leaders are testing hybrid working policies, and both businesses and consumers are experiencing pent-up demand for many products and services. Smarter and faster technology leaders recognize that a new wave of volatility creates opportunities, and organizations with the most nimble integration, application development, and data management practices have the advantage.

So, what do organizations need that’s new, different, or improved during the new normal compared to pre-COVID and COVID periods?

What’s Different About IT and Data in this New Normal?

My simple answer is that the applications and data services that organizations build today are more mission-critical and core to business operations. We’re not just digitizing departmental workflows, developing dashboards to replace spreadsheets, or creating mobile experiences for existing applications.

We’re fully modernizing applications for cloud capabilities and integrating them with many enterprise systems and SaaS applications. We’re building workflows that connect supply chains to operations and onto customers so that they have real-time information and easy-to-use experiences. The agile teams are developing the applications, but they also enable analytics, update the data catalog, and support data governance during the development process.

Business leaders have challenged IT to release mission-critical application and data service MVPs faster and demonstrate agility in making frequent enhancements. The smarter and faster technology leaders meet these expectations using integration platforms, connecting everyone to everything, and accelerating the delivery of integration projects.

How fast can organizations accelerate the development of integrations and applications? Here are a few examples:

• HealthBridge Financial reports deploying integrations ten times faster using Boomi Integrations and Boomi Flow to connect to AWS, Jira, Slack, Okta, and Mockaro on a scalable, HIPAA-compliant architecture.
• Thoughtspot, a search and AI-driven analytics software vendor, sped integration sevenfold using Boomi AtomSphere to automate order-to-cash processes across Oracle NetSuite, Salesforce Sales Cloud for CRM, and FinancialForce.
• Service providers like NNIT are four times faster connecting their internal workflow platforms to their customer’s ITSM platforms, including BMC, ServiceNow, and Cherwell, to support data exchanges on service requests, incidents, problems, and changes.

These three examples have integrations with mainstream platforms but also required customized integrations with industry-specific and other technologies. The teams took advantage of out-of-the-box and configurable integrations and then demonstrated the speed and agility of developing integrations with their other platforms.

The Overhead in DIY Integrations and Applications

I’m not surprised by these speed factors because many organizations underestimate the engineering time required to develop and deploy integrations and applications. While IT leaders want teams focused on the data flows, business logic, and user experience, much of the toil goes into developing the scaffolding required to support reliable and robust integrations. 

• Scaffolding refers to all the technical work requires to deliver the service and includes
• Configuring the cloud infrastructure using IaC or other automations
• Engineering CI/CD pipelines, version control practices, and other DevOps functions
• Enabling robust API operational capabilities, including security and monitoring
• Automating testing, reviewing code quality, and shifting left security practices

Instead of these complexities, development teams take advantage of the built-in infrastructure, operational capabilities, out-of-the-box integrations, and low-code development tools to develop minimally viable products, applications, and integrations rapidly.

But some of the more significant time savings occurs in the following areas:

• Requirements gathering, which can be reduced when prototyping and piloting the user experiences in low-code platforms
• Ensuring data flows are reliable and observable, which requires building in robust data validations and error management into data integrations
• Cleansing third-party data sources before technologists use them in applications, data visualizations, and machine learning models
• Supporting faster enhancements and easier knowledge transfer when developers build applications and integrations using low-code visual paradigms

Organizations solving these challenges with DIY algorithms or a hodgepodge of tools are at a disadvantage, while using a low-code integration and data platform simplifies the work required to develop and support data-rich applications.

Going from Rapid Builds to Faster Deploys and Business Impacts

The end game for most applications and integrations is not the MVP. Digital transformation leaders want to go from PoC to pilot and to full production deploys faster. And once the apps and integrations are live, they seek to respond to changing operating conditions and want IT to turn around changes, improvements, and new capabilities quickly and reliably.

So while low-code enabled rapidly evolving user experiences and integrations, IT and data teams must also consider implementing the best architecture and data management practices that reduce the risk of technical debt and data quality issues. Teams that DIY integrations and applications must also support the underlying technology scaffolding, and since tech changes rapidly, these are often the most complex areas of technical debt.

A full iPaaS integration platform provides full lifecycle capabilities such as API management for creating, publishing, and managing APIs. Agile data teams define, onboard, and govern new data entities and fields in a master data hub and a data catalog so that employees can leverage newly created data repositories for other business needs.

The big picture is that teams focus on implementing the business requirements instead of engineering the technical capabilities. With so much change, opportunity, and risk facing businesses today, using a low-code integration, application, and data management platform enables teams to accelerate digital transformation and evolve their technology capabilities.

This post is brought to you by Boomi

The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Boomi.