Digital Transformation
Staged modernization of legacy systems,
without interruption to the business.
Legacy systems hold years of business rules and data and cannot simply be switched off. InterCloud modernizes them in stages, moves them to AWS, connects them to the rest of the application landscape and makes the data they hold available for decision-making.
Application Modernization
Replacing a Legacy Monolith With a Maintainable Platform
The work starts with an assessment: a review of code and database, a map of dependencies, and an analysis of which functions are used, by whom and how often. This produces a modernization plan that ranks components by business value and risk, so that the first releases address the components with the highest value.
Migration follows the strangler-fig pattern. New services built on Spring Boot and Next.js take over one capability at a time behind a routing layer, while the existing system continues to serve the remaining functions. Users work with a single application throughout, and no component is switched off until its replacement has proven itself in production.
Where the code is sound and only the platform is outdated, we re-platform the application instead. The application is containerized and moved to AWS ECS, proprietary middleware is replaced and the database is brought to a supported version of PostgreSQL.
- Assessment with a ranked modernization roadmap
- Strangler-fig migration behind an API gateway or reverse proxy
- Re-platforming of Java EE and other JVM applications to Spring Boot and containers
- Data migration with reconciliation reports for every cut-over
Cloud Migration
A Migration to AWS in Waves, Each With a Rollback Path
A migration involves more than copying servers. We establish the account structure, networking and security first, then move workloads in waves, each with its own rollback path.
Landing zone first
Start from an account structure that matches your network and compliance requirements. AWS Organizations with separate accounts for production and non-production, central logging, IAM roles in place of shared keys, and a VPC design to suit. The entire configuration is defined in Terraform, reviewed and versioned.
Migration waves
Downtime remains within an agreed window. Workloads are grouped by dependency and moved in waves, beginning with the least critical, and each wave has a test plan, a cut-over window and a rollback step. Databases are moved with replication.
Right target for each workload
Application services run in containers on ECS, databases on managed PostgreSQL and event-driven jobs on serverless functions. Lift-and-shift is used only where a rewrite is not yet justified, and the reasoning behind each choice is documented.
Security in every wave
Your data stays protected while it moves. Encryption at rest and in transit, secrets in a managed store, least-privilege roles and Cloudflare at the edge for TLS, WAF and DDoS protection apply in every wave. A security review is carried out as part of each wave.
Cost visibility
Every environment and team can see its spending from the start, through tagging standards and budgets. After the migration, end-sizing and reserved capacity are reviewed once actual usage is known.
Hand-over or managed operations
Your team receives the Terraform code, runbooks and training needed to operate the environment, or InterCloud continues to operate it under a managed operations agreement.
System Integration
Integrations That Replace Re-Keying Between Your Systems
Enterprises run ERP, HR, CRM, e-commerce and many departmental tools, and staff often re-key data between them. We replace manual transfers with integrations that are documented, monitored and owned by your organization.
Synchronous requirements are met with REST APIs described in OpenAPI, and asynchronous flows use events and queues so that a slow or unavailable system does not block the others. Legacy SOAP services, file transfers and database links are wrapped in adapters so that the rest of the landscape works with one consistent interface.
Every integration records what it transferred and when, retries safely and raises an alert on failure. Reconciliation therefore becomes an exception procedure instead of a monthly task.
- REST and OpenAPI contracts, versioned and published to your teams
- Event-driven integration with queues and idempotent consumers
- Adapters for SOAP, SFTP, flat files and direct database interfaces
- Integration with GlowScale, Orbio and third-party ERP, CRM and payment systems
Data & Analytics
Reliable Reporting for Management Decisions
Reporting projects usually fail on data quality and timing. We therefore build the pipeline and the definitions first, and the dashboards afterwards.
Data warehouse
Compare trends over time from one central store. The warehouse runs on PostgreSQL or an AWS analytics service and is fed by scheduled and event-based pipelines from your applications, with history retained.
Shared definitions
Finance and operations work from the same figures. Each measure, such as revenue, stock on hand or cycle time, has one agreed definition, documented and applied in every report.
Dashboards and reports
Each role sees the figures it needs. Role-based dashboards for executives, managers and operational staff, scheduled reports by e-mail, and exports for further analysis in spreadsheets.
Prepared for AI
Assistants and forecasting depend on clean, governed data. The same warehouse supplies InterCloud AI and the models described under AI & Data Solutions.
Roadmap
A Typical Transformation Roadmap
The phases overlap in practice. Their order below reflects what must be in place before the next step can be taken safely.
- 1
Assess and prioritize
An inventory of applications, data and integrations, interviews with business owners, and a roadmap that identifies short-term improvements, foundations and long-term replacements.
- 2
Build the foundations
The AWS landing zone, CI/CD pipelines, monitoring and an API gateway are established. These components are shared by everything that follows and are usually the first visible delivery.
- 3
Migrate and modernize in waves
Workloads are moved to AWS, legacy components are replaced one capability at a time and systems are connected through documented interfaces. Each wave ends with users working on the new version.
- 4
Consolidate data
Pipelines into a warehouse, agreed definitions and the first dashboards are delivered. Data quality issues found at this stage are added to the application backlog.
- 5
Operate and improve
The environment moves to managed operations or is handed over to your team, with a quarterly review of what to modernize, retire or automate next.
Know the risk and cost before you commit
A modernization assessment provides a ranked roadmap and a clear view of risk and cost before your organization commits to the full program.