From separate systems to one reliable process.

Yes. The 6 services can be planned as clearly scoped work packages. Together we clarify the situation, the prerequisites and the result you need first. The subpages show the respective scope and the technical decisions.

Before implementation, we agree on goals, affected systems, involvement, results and acceptance criteria. Open technical questions can first be clarified in a current-state review or a pilot. Additional tasks are assessed for their impact on effort and schedule.

Documentation, briefing and responsibilities are covered in the engagement. If OTOKO® takes on ongoing tasks, we agree on an operating scope for them, including service hours and escalation paths. Your team can also take the results forward itself or with existing partners.

An interface is more than a successful data transfer. Sender and receiver must attach the same meaning to the data, handle errors and be able to introduce changes in a controlled way. We plan the architecture, implement connections and test the complete business process. Older applications and file transfers also remain in scope. The technical solution follows your requirements for data freshness, load, security and maintainability.

Partners and applications need interfaces whose behavior they can rely on. We design API contracts, set up access and protection at the gateway and organize versions, documentation and approvals across the entire lifecycle.

API guideline with naming conventions, error formats, versioning and security requirements Interface catalog with OpenAPI specification and an owner per API Gateway build with Kong, Apigee or Azure API Management, connected to your identity management via OAuth 2.0 and OpenID Connect Partner and developer portal with access management, keys and usage reports Lifecycle with approval process, deprecation of old versions and change notifications

API guideline and interface catalog Operational API gateway with identity integration Developer portal with documentation per API

We start with the cases handled by the connected systems: what data do they need, which states are they allowed to change and how do they detect errors? REST, GraphQL or gRPC are chosen depending on the use case. The description uses the format that suits the protocol, for example OpenAPI for HTTP APIs of that kind. Besides the payload, pagination, timeouts, error responses and retry behavior are defined. Examples and test cases help the consuming teams integrate the interface before the production release.

A gateway can manage access, throttle requests and enforce technical rules. Whether a specific user is allowed to read a particular order must additionally be decided in the responsible service. We plan token validation, service identities, tenant assignment and logging along this boundary. For write calls, we clarify how repeated requests are handled. Old versions follow a clear deprecation process, so that changes do not unexpectedly break partner connections.

Contract tests check the agreed structure; integration and load tests also cover behavior. We test rejected access, invalid input and timeouts as well as successful calls. The handover includes the specification, gateway configuration and responsibilities. To get started, we need typical consumers, load assumptions and the business cases that an API is meant to enable.

Independent development can help, but too many distributed services can also get in its way. We review meaningful business boundaries and implement a suitable architecture, including communication, data ownership, delivery and operations.

Domain split with event storming and bounded contexts together with the business unit Platform on Kubernetes with Helm, GitOps delivery and namespaces per team Service communication via REST, gRPC or messages, with a service mesh for encryption and routing Data storage per service with the saga pattern and outbox for distributed transactions Operating rules for logging, configuration, secrets and resilience

Domain model with service boundaries and interfaces Platform with delivery pipeline as code Operations manual with rules per service

Together with the business unit and development, we look at terms, rules and changes. Functions that regularly need to be adjusted together should not be split up lightly. A modular monolith can create clear boundaries without introducing distributed operations. Microservices become an option where independent teams, load profiles or delivery cycles offer a demonstrable benefit. The decision is documented together with its operational consequences, instead of choosing an architecture based on a trend alone.

A case that spans several services does not automatically have a shared database transaction. We plan state transitions, temporary inconsistency and compensating actions. An outbox pattern can help link a data change consistently with the event to be published. Retries require business idempotency, meaning a defined result when processing is repeated. Timeouts and dependencies are limited so that a slow service does not block the entire chain. The teams involved must be able to understand and test these rules.