For a complex, monolithic application, a ‘lift-and-shift’ to containers is often the most pragmatic first modernization step. Red Hat OpenShift on IBM Cloud provides a managed Kubernetes platform to containerize the application, which packages its dependencies and enables more agile, consistent deployments without the immediate risk and complexity of a full microservices refactoring. This aligns with the goal of improving scalability and deployment agility as a foundation for future decomposition.

IBM Cloud Cost and Asset Management (formerly Cost and Asset Management) is the service designed specifically for cost tracking, reporting, and optimization. It provides tools to identify idle or underutilized resources (like Virtual Servers), set up budgeting, and implement governance policies to control costs, making it the correct choice for this financial optimization task.

IBM Databases for Redis is an in-memory data store designed specifically for caching and session storage. It delivers the required millisecond latency for read-heavy operations. Using Redis as a cache layer for frequently accessed product data (a common pattern) reduces direct query load on the primary transactional Db2 database, improving overall application performance and scalability.

IBM Cloud SQL Query is a serverless service that allows you to run ANSI SQL queries directly on data in Cloud Object Storage. It is ideal for this scenario because it is cost-effective for intermittent use—you only pay for the amount of data processed by each query, with no infrastructure to provision or manage when idle. This aligns perfectly with the need to minimize cost during idle periods.

IBM Cloud operates on a shared responsibility model. For Infrastructure as a Service (IaaS) offerings like Virtual Servers, IBM Cloud is responsible for the security **of** the cloud (physical infrastructure, hypervisor, network). The customer is responsible for security **in** the cloud, which includes securing the guest operating system, any installed applications, middleware, and the data housed within the virtual server.

IBM Cloud Event Streams is a fully managed, high-throughput message bus built with Apache Kafka. It is specifically designed for building scalable, event-driven architectures. It allows event producers (like IoT sensor feeds) to publish messages to topics, from which multiple consumers can reliably read and process them asynchronously, providing the decoupling and durability required in the scenario.

Following the principle of least privilege, the most secure method is to create a custom IAM policy. This policy can be finely tuned to grant permissions only for specific resource types (e.g., subnets, security groups) and specific actions (e.g., view, create, delete within a specific resource group or region), providing precise control without over-provisioning access like an Administrator or broad Editor role would.

IBM Cloud Direct Link provides dedicated, private network connections between a customer’s on-premises infrastructure (or colocation) and IBM Cloud. It bypasses the public internet, offering enhanced security, predictable performance, lower latency, and higher throughput compared to internet-based connections like VPN, making it the ideal solution for sensitive hybrid cloud workloads.

IBM Cloud Code Engine is a fully managed, serverless platform that runs containerized workloads. It is designed specifically for this scenario: it automatically scales applications (including APIs) to and from zero based on HTTP requests, requires no infrastructure management, and uses a pay-per-use model based on the vCPU and memory consumed during request execution, aligning with the goal of minimizing operational overhead.

For a complex, monolithic application, a ‘lift-and-shift’ to containers is often the most pragmatic first modernization step. Red Hat OpenShift on IBM Cloud provides a managed Kubernetes platform to containerize the application, which packages its dependencies and enables more agile, consistent deployments without the immediate risk and complexity of a full microservices refactoring. This aligns with the goal of improving scalability and deployment agility as a foundation for future decomposition.0