In this new digital age, IoT, AI, API-based, mobile, and blockchain applications, etc. are becoming more and more pervasive – and for good reason.
Advancements in wireless and networking technologies, coupled with superior sensors and high-performance computing capabilities, foreshadow immense value generation through IoT applications. In fact, IDC predicts that the number of IoT devices will reach 75 million and generate around 79 zettabytes of data by 2025.
Connected applications – connecting data, your business, and your customers
The “connected applications” ecosystem is quite complex – driving decisions and actions potentially across numerous entities based on analysis of real-time data throughout a distributed environment, which is exchanging information over an intricate communication architecture.
To effectively manage the connected applications application landscape, IT organizations must embrace fit-for-purpose processes and methodologies, and the right technology and functional skills to adequately align with the business. And, traditional technology or function-oriented IT operating models must evolve to address specific characteristics of connected applications within the enterprise landscape.
Key imperatives that you should look to address in the operating model include:
Becoming a customer and business-centric IT organization.
Connected applications are primarily systems that leverage real-time field data. Application management teams need to render agility efficiently to effectively create the desired business outcomes.
Teams organized according to product (and in specific scenarios, according to feature) in both form and function will perform more effectively – and most importantly – will stay more customer oriented. These team units must be cross and multi-functional and possess all the necessary front and back-end skills, with a measured focus on business outcomes. As a whole, distributed teams with good collaboration tools can be quite effective for connected ecosystem.
The overall IT service governance practices for these digital age apps should enhance business agility, increase ROI, and promote collaboration with partners to drive delivery and innovation.
Utilizing Agile methodologies and DevOps practices.
The need for agility makes the connected applications landscape evolve rapidly. Requirements include both functional and non-functional elements. Agile and DevOps practices, which are amplified with automation across the software delivery lifecycle (including downstream activities) are essential in meeting accelerated responsiveness and time-to-market requirements. Security and software quality assurance practices must also evolve to adequately address the specific non-functional requirements of applications, for example, usability, performance, security, etc.
The connected applications landscape involves various technologies and generally comprises complex applications. Product teams need multiple skills to effectively manage all workflow dependencies within the team to develop these applications efficiently. Profiles with multiple skills and full-stack developers are better suited, as they are more efficient in solution development and issue resolution. Additionally, provisions to impart product-specific functional and domain knowledge within the team must be considered to ensure adequate understanding of connected application use cases – for example – automotive-connected cars or manufacturing-connected factories, etc. This will ensure overall service and product quality.
Building scalable, flexible, and adaptable apps.
Digital-age apps are dynamic. These applications require large-scale global implementations and deployments with new features, applications, and specific components, which are continuously developed and integrated in response to emerging business needs and regulatory requirements – or to ensure technical consistency.
Team design constructs must synchronize with customer teams in an agile manner and foster a collaborative ecosystem to effectively engage with client and partner teams, in order to leverage existing applications, workflows, and broker services for the business.
Developing a comprehensive data management framework.
The massive amount of data generated from IoT devices is the key to the value of connected applications. To operationalize actions with this massive amount of data, it is important to have the right tools to collate data from all input sources with various network protocols and ingest transformed data into a cloud or on-premise system. In some scenarios, actions may be automated based on AI models running on real-time data. So, a clear data strategy, along with design structures and processes are essential in this data flow.
Applying intelligent IT operations for zero service disruption.
The monitoring stack must adequately cover all device infrastructure configurations, network, security, performance and application, and infrastructure – with the objective of maximum service availability and business continuity. Alerts and thresholds must be configured to ensure the right reactivity to problematic events.
Like any production system, audits and logs are crucial inputs for security and service improvement (optimizing, debugging, etc.). A typical IoT logging stack consists of device logs (capturing information on device connections, errors, memory usage, events, etc.), IoT registry audit logs (registry-level operations), network logs (utilization, traffic, availability), application logs (usage, performance, availability) and platform and infrastructure logs. Centralized and consolidated logs in structured formats are backed by strong visualization tools and help in holistic analysis, for example, event correlation, troubleshooting, etc.
Providing continuous service improvement of connected applications.
A two-prong approach for continuous service improvement focuses on improving the present and preparing for the future. Typical issues reported by customers in the connected ecosystem include unresponsive applications, application unavailability, data errors, etc. Preventive and self-help solutions that minimize user inconvenience should be investigated and deployed in an ongoing manner. Also, rigor must be maintained to ensure security and regulatory compliance.
Over time, IT teams can develop various technology accelerators that improve the velocity for developing new applications and solutions. As massive data is generated by devices, the continuous evolution in data learning is critical for staying relevant and effective.
The sheer amount of data generated by these applications can offer your business an unprecedented potential for control and efficiency throughout your operations. Essentially, the business value and commercial success of connected applications relies heavily on their usability, availability, and reliability – so it helps to have a capable expert who can assist you in your journey here.
When sourcing ADM services support in the connected applications landscape, it’s essential to find a partner who can bring together all the right assets and capabilities, in order to deliver on your desired business outcomes.
Capgemini’s ADMnext – business-focused ADM services for conquering the connected applications landscape
As a dynamic set of business-focused ADM services, Capgemini’s ADMnext offering puts the achievement of your business imperatives above everything else – and can unlock the massive potential that the connected applications landscape holds by helping you:
- Become a customer and business-centric IT organization
- Utilize Agile methodologies and DevOps practices
- Build scalable, flexible, and adaptable apps
- Develop a comprehensive data management framework
- Apply intelligent IT operations for zero service disruption
- Provide continuous service improvement for connected applications.