DocsHow it WorksGeneralHow It Works Cadence.CI is a DevOps platform built around three principles: observability, collaboration, and security. This page covers the architecture and concepts that underpin the platform. Core Technology Cadence.CI relies on Mélodium to implement distributed pipelines by handling data streams, event reactions, and process management in a way that is scalable, reproducible, and fault-tolerant. Data Streams as First-Class Citizens Mélodium treats data streams as the fundamental unit of computation. Streams can be distributed, transformed, and processed across multiple nodes, enabling real-time and scalable data handling. Streams are typed and generic, allowing for safe and reusable pipeline code across different data types and environments. Event-Driven and Reactive Programming Treatments react to incoming data or events rather than following a predefined execution order. This is particularly useful for integration pipelines, real-time analytics, and distributed task processing where execution depends on data availability. Cross-Platform Support Mélodium’s distribution system runs on diverse platforms, from constrained embedded systems to large-scale cloud infrastructure. Abstraction layers handle platform-specific details, letting pipeline authors focus on logic rather than deployment. Infrastructure and Distribution Cadence.CI dynamically spawns runners across diverse infrastructures and cloud providers in a truly infrastructure-agnostic way. Infrastructure Agnosticism Cadence.CI keeps users free to choose and mix cloud and on-premises environments. Runners can be deployed on: Public clouds (Scaleway and AWS today, more providers planned) On-premises infrastructure (any Kubernetes cluster, self-managed or Melodium-operated) Hybrid environments (mixing cloud and on-prem) Dynamic Runner Spawning Runners are provisioned on demand and terminated when the job completes: On-demand provisioning: runners spawn only when needed, eliminating idle resource costs. Auto-scaling: the system scales up or down based on pipeline demand. Ephemeral runners: each runner is created for a specific job and destroyed afterward, improving both efficiency and security posture. Unified Abstraction Layer Mélodium shares pipeline specifications with Cadence.CI regardless of the underlying infrastructure. Cadence.CI translates Mélodium’s requests into provider-specific actions, launching an EC2 instance on AWS, an instance on Scaleway, or a pod on Kubernetes, while presenting a consistent interface to the pipeline author. Monitoring and Debugging Cadence.CI provides monitoring and debugging for Mélodium executions, aggregating logs and execution data from runners regardless of whether they run on cloud, on-prem, or hybrid infrastructure. Log and Debug Aggregation Runners upload logs and debug data to Cadence.CI in chunks as execution progresses, appearing in the dashboard shortly after each upload, and you can browse them per run, including a full program dump of what was executed. Run-Level Execution Data For each run, Cadence.CI records: Execution state: request, start, and end times, current status (scheduling, running, finished, unschedulable), and the success/failure result. Entrypoint and parameters: the exact treatment entrypoint and input parameters the run was launched with. Resource requests: CPU, memory, and storage requested for the run’s engine, containers, and service containers. Treatment-level debugging, time-travel replay, alerting, and metrics export are on the roadmap. Organization and Security Roles and Invitations Users belong to an organization and hold a role (Admin, Operator, or Lambda) that governs what they can do, such as managing cluster tokens or browsing cluster details. Admins can invite new users to the organization by email, and roles and access apply at the organization level. Team-level grouping and per-project/per-runner permission scoping are on the roadmap. Bring Your Own Infrastructure Cadence.CI follows a “Bring Your Own Infrastructure” (BYOI) model: pipeline orchestration runs on Cadence.CI, while compute runs on infrastructure you control, your own cloud provider account or your own Kubernetes cluster. This model provides: Data sovereignty: sensitive data stays within your private infrastructure, and runners can be placed in specific regions to meet data residency requirements (GDPR, CCPA, etc.). Network isolation: runners can be deployed in isolated VPCs, on-prem data centers, or air-gapped environments. Compliance alignment: because you control the infrastructure, you can meet strict requirements (HIPAA, PCI DSS, SOC 2, ISO 27001) by running on already-certified environments. Ephemeral runners: runners are short-lived, eliminating idle attack surface. Organizations that prefer to run on infrastructure operated by Melodium can use shared or dedicated clusters instead, see Kubernetes integration for the distinction. Per-team runner/secret scoping and IAM integration with external identity providers are on the roadmap. Core-Level Security Cadence.CI leverages Mélodium’s runtime properties for security guarantees that are built into the execution layer itself: Fail-fast validation: the entire program is validated at startup. Invalid configurations and unsafe setups halt immediately, before any runner is spawned or any compute is provisioned. In-memory secret handling: sensitive values are identified in memory, kept isolated to the treatment using them, and securely erased after use. 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