Managing Common and AI-Based Application Dependencies During a Migration

Applications, like stars that form constellations, need each other—they’re interdependent. During migration, however, this dependence can sometimes be a service’s greatest strength and weakness. Modern applications are complex, often consisting of multiple interconnected components, each with its own set of dependencies and requirements. With the rise of artificial intelligence (AI)-based applications and their need for sophisticated infrastructure and data processing capabilities, this complexity is becoming quite a challenge. Not mapping and monitoring application dependencies can significantly decrease service performance during and after migrations. This includes common types of dependencies such as database dependencies; service dependencies such as web server, authentication, and Domain Name System (DNS) dependencies; and emerging AI dependencies.

Database Dependencies

According to Flexera’s 2024 State of the Cloud Report, understanding application dependencies (54 percent) and assessing the technical feasibility of implementing a migration plan (45 percent), are top concerns for cloud decision-makers and executive leaders during a migration.

Applications often rely on shared data sources such as databases or APIs, creating dependencies between applications. This interdependence can extend across IT environments, including on-premises and cloud setups. For example, Microsoft Teams may depend on an API to integrate with OneDrive for file sharing and version control. Similarly, a healthcare app such as Cerner may rely on Oracle Database to store and manage patient records securely.

When a database is located on-premises, the migration process can become very tricky. It involves not only moving the data to the cloud but also ensuring that applications can still access the database. For monolithic and custom apps, this may even require implementing data replication mechanisms to keep the on-premises and cloud databases synchronized across hybrid environments. Also, data security and compliance considerations can become more challenging because they may have stricter regulatory requirements compared with cloud-based databases.

Service Dependencies
Properly managing service dependencies is crucial for ensuring the availability, reliability, and performance of applications. To function properly, applications often depend on external services, such as payment gateways; internal systems, such as DNS for domain resolution; and authentication services; as well as other systems such as inventory tracking systems or customer support platforms. These service dependencies need to be managed during migration to ensure that applications continue to work as expected in the cloud environment. For example, a web application may rely on a payment gateway to process transactions, an ERP system to manage business processes such as accounting and inventory, DNS for domain resolution, and authentication services to ensure secure access to the application.

Managing service dependencies involves understanding the interactions between different components of the application and its supporting infrastructure. This includes identifying all external services and internal systems the application relies on, as well as understanding the data flow between these components. Organizations should also consider the utilization trends and performance requirements of the application and how these dependencies may impact service-level agreements (SLAs). Additionally, organizations should have a strategy for monitoring and troubleshooting these dependencies to maintain optimal performance and reliability. Failure to manage these dependencies effectively can result in downtime, data loss, or other disruptions that can negatively impact business operations.

Overall, managing cloud migrations is about ensuring the long-term success of applications in the cloud environment. By understanding and managing service dependencies, organizations can minimize the risk of service disruptions and ensure that applications meet the needs of users and the business.

AI Dependencies

AI applications and algorithms can create unique dependencies, often relying on specific datasets, libraries, or frameworks. For example, a machine learning model may require a specific dataset for training or a particular library for inference. Managing these dependencies is crucial for ensuring the smooth migration of AI applications and the tools they use for their modeling to the cloud.

One strategy for managing AI dependencies is to use containerization techniques. Containers, such as Kubernetes, provide a lightweight and portable way to package applications, along with their dependencies, making it easier to deploy and manage them in the cloud. Additionally, organizations can leverage cloud-native AI services and platforms such as Amazon SageMaker that provide preconfigured environments for AI workloads. These platforms can help simplify the management of AI dependencies and ensure the necessary resources are available in cloud environments.

Another important consideration for managing AI dependencies is data integration. AI applications normally require access to large and constantly evolving datasets, which are integrated into environments to ensure the AI system’s performance and accuracy. Organizations should ensure that data pipelines exist to transfer data from on-premises systems to the cloud or other on-premises domains—using dedicated network connections or VPNs—and that the necessary data processing and storage resources are available and AI workloads can scale effectively.

Managing Dependencies

To effectively manage application dependencies during cloud migration, organizations should adopt a comprehensive approach that includes at least the following key steps:

• Thoroughly inventory and map applications to identify mission-critical ones and assess their dependencies
• Implement a phased approach to migration, starting with less critical applications before moving on to more complex ones
• Leverage monitoring and visibility solutions, such as NETSCOUT’s nGenius Enterprise Performance Management, to identify performance issues; cover blind spots; and help increase an IT team’s understanding of consumption patterns, application utilization, and overall user experience to rapidly troubleshoot problems such as downtime, slow responses, or degraded functionality

Dependencies are an inevitable aspect of migrations. By understanding dependencies and implementing strategies to manage them effectively, organizations can ensure a smooth and successful migration to the cloud.

Contact us to see how NETSCOUT solutions can help you manage dependencies during a migration.