
Inaki Rodriguez engineered robust observability and deployment automation features for the silogen/cluster-forge repository, focusing on GPU metrics, AIRM onboarding, and secure, scalable cluster management. He leveraged Kubernetes, Helm, and OpenTelemetry to streamline configuration, automate onboarding workflows, and enhance monitoring with Grafana dashboards and Prometheus integration. Inaki improved reliability by refactoring deployment pipelines, cleaning up legacy configurations, and implementing RBAC and secret management best practices using YAML and Shell scripting. His work addressed operational pain points, reduced manual intervention, and enabled faster, safer releases. The depth of his contributions is reflected in the breadth of features delivered and critical bugs resolved.

Sept 2025 monthly summary for silogen/cluster-forge focusing on security, reliability, and deployment automation across the stack. Delivered key features, fixed critical issues, and improved release readiness, enabling faster, safer deployments with reduced operational toil.
Sept 2025 monthly summary for silogen/cluster-forge focusing on security, reliability, and deployment automation across the stack. Delivered key features, fixed critical issues, and improved release readiness, enabling faster, safer deployments with reduced operational toil.
In August 2025, silogen/cluster-forge delivered two high-impact features for AIRM that enhance observability and deployment reliability, with measurable improvements to deployment velocity and system resilience. OpenTelemetry collector enhancements expanded Prometheus scraping for airm-api and airm-custom-metrics, added missing airm metrics, separated the otel collector, and cleaned up manifests to remove duplicates, improving observability accuracy and operational clarity. AIRM deployment and gateway modernization overhauled the deployment workflow: new system configuration, deploy steps, configmaps, and hooks, plus gateway enhancements including WebSocket support and the removal of the outdated initial bootstrap job, enabling real-time data flows and more robust gateway behavior. These efforts were complemented by targeted cleanups and refactors (script corrections, modular config via dedicated configmaps, and a specialized configure Docker image) that reduced configuration drift and streamlined maintenance.
In August 2025, silogen/cluster-forge delivered two high-impact features for AIRM that enhance observability and deployment reliability, with measurable improvements to deployment velocity and system resilience. OpenTelemetry collector enhancements expanded Prometheus scraping for airm-api and airm-custom-metrics, added missing airm metrics, separated the otel collector, and cleaned up manifests to remove duplicates, improving observability accuracy and operational clarity. AIRM deployment and gateway modernization overhauled the deployment workflow: new system configuration, deploy steps, configmaps, and hooks, plus gateway enhancements including WebSocket support and the removal of the outdated initial bootstrap job, enabling real-time data flows and more robust gateway behavior. These efforts were complemented by targeted cleanups and refactors (script corrections, modular config via dedicated configmaps, and a specialized configure Docker image) that reduced configuration drift and streamlined maintenance.
July 2025 monthly summary for silogen/cluster-forge. Key outcomes include automated AIRM onboarding and security/privacy hardening that reduce manual steps, improve security posture, and enable more predictable cluster provisioning.
July 2025 monthly summary for silogen/cluster-forge. Key outcomes include automated AIRM onboarding and security/privacy hardening that reduce manual steps, improve security posture, and enable more predictable cluster provisioning.
June 2025 (silogen/cluster-forge): Monthly summary focused on delivering observable reliability, streamlined releases, and maintainable configurations. Key features delivered: - Enhanced metrics collection and exporter reliability: Updated metrics exporter image to the latest stable version, set imagePullPolicy to IfNotPresent, and granted metrics exporter ClusterRole permissions to watch, get, and list pods; extended GPU metrics labeling with ExtraPodLabels and CustomLabels for detailed pod identification. Commits associated with this work include f574d61d1330438a77bcd3ef8a5550e292a9b5f5 (Fixing metrics image settings) and 231aa640ebe96a76db4e5973edfc2ec1f4b2dbe6 (Fixing the default configmap for GPU metrics). - OpenTelemetry collector cleanup: removal of Mimir exporter and related configuration from the collector manifests (basicauth/mimir-tenant extension and otlphttp/ops-mimir exporter). Commits include 1bef629779b806fe217d457c98376b9fd327e889 (Getting rid of mimir exporter) and 40eb032811588a1a6a8a93e3620daf2c4468f1bd (minor fix). - Release workflow cleanup: streamlining the release process by removing an unnecessary flag from the configuration. Commit: 41587f15bf1572746258e13077038e28b05d190d (Minor fix). Major bugs fixed: - Resolved metrics image configuration issues and GPU metrics configmap defaults to ensure reliable metrics collection and accurate GPU pod attribution. - Cleaned up stale Mimir-exporter related configuration to prevent misconfigurations in the OpenTelemetry pipeline. Overall impact and accomplishments: - Improved observability reliability and accuracy through robust metrics collection and GPU labeling, enabling faster MTTR and better capacity planning. - Reduced maintenance overhead and risk by eliminating unnecessary Mimir exporter and simplifying release configurations, leading to smoother deployments and faster cycles. - Demonstrated end-to-end capability to adjust instrumentations, RBAC permissions, and release automation with minimal churn. Technologies/skills demonstrated: - Kubernetes RBAC and metrics exporters (image management, imagePullPolicy, ClusterRole permissions) - OpenTelemetry collector configuration and cleanup - YAML manifest maintenance and idempotent change management - Release process automation and configuration cleanup - Commit hygiene and traceability (mapping commits to features)
June 2025 (silogen/cluster-forge): Monthly summary focused on delivering observable reliability, streamlined releases, and maintainable configurations. Key features delivered: - Enhanced metrics collection and exporter reliability: Updated metrics exporter image to the latest stable version, set imagePullPolicy to IfNotPresent, and granted metrics exporter ClusterRole permissions to watch, get, and list pods; extended GPU metrics labeling with ExtraPodLabels and CustomLabels for detailed pod identification. Commits associated with this work include f574d61d1330438a77bcd3ef8a5550e292a9b5f5 (Fixing metrics image settings) and 231aa640ebe96a76db4e5973edfc2ec1f4b2dbe6 (Fixing the default configmap for GPU metrics). - OpenTelemetry collector cleanup: removal of Mimir exporter and related configuration from the collector manifests (basicauth/mimir-tenant extension and otlphttp/ops-mimir exporter). Commits include 1bef629779b806fe217d457c98376b9fd327e889 (Getting rid of mimir exporter) and 40eb032811588a1a6a8a93e3620daf2c4468f1bd (minor fix). - Release workflow cleanup: streamlining the release process by removing an unnecessary flag from the configuration. Commit: 41587f15bf1572746258e13077038e28b05d190d (Minor fix). Major bugs fixed: - Resolved metrics image configuration issues and GPU metrics configmap defaults to ensure reliable metrics collection and accurate GPU pod attribution. - Cleaned up stale Mimir-exporter related configuration to prevent misconfigurations in the OpenTelemetry pipeline. Overall impact and accomplishments: - Improved observability reliability and accuracy through robust metrics collection and GPU labeling, enabling faster MTTR and better capacity planning. - Reduced maintenance overhead and risk by eliminating unnecessary Mimir exporter and simplifying release configurations, leading to smoother deployments and faster cycles. - Demonstrated end-to-end capability to adjust instrumentations, RBAC permissions, and release automation with minimal churn. Technologies/skills demonstrated: - Kubernetes RBAC and metrics exporters (image management, imagePullPolicy, ClusterRole permissions) - OpenTelemetry collector configuration and cleanup - YAML manifest maintenance and idempotent change management - Release process automation and configuration cleanup - Commit hygiene and traceability (mapping commits to features)
May 2025 monthly summary for silogen/cluster-forge focused on delivering enhanced GPU observability and business value through Grafana-based monitoring. Implemented comprehensive GPU alerts and an updated metrics dashboard to enable multi-cluster visibility, faster issue detection, and data-driven capacity planning.
May 2025 monthly summary for silogen/cluster-forge focused on delivering enhanced GPU observability and business value through Grafana-based monitoring. Implemented comprehensive GPU alerts and an updated metrics dashboard to enable multi-cluster visibility, faster issue detection, and data-driven capacity planning.
February 2025 monthly summary for silogen/cluster-forge focused on expanding GPU observability. Delivered a new ConfigMap for the AMD GPU metrics exporter and updated the device configuration example to reference the new ConfigMap, enabling detailed GPU metrics collection and monitoring across clusters. No major bugs fixed in this period; maintenance work prioritized stability and config correctness. The changes streamline GPU metrics onboarding and align with our monitoring strategy, setting the stage for scalable GPU health dashboards and alerting.
February 2025 monthly summary for silogen/cluster-forge focused on expanding GPU observability. Delivered a new ConfigMap for the AMD GPU metrics exporter and updated the device configuration example to reference the new ConfigMap, enabling detailed GPU metrics collection and monitoring across clusters. No major bugs fixed in this period; maintenance work prioritized stability and config correctness. The changes streamline GPU metrics onboarding and align with our monitoring strategy, setting the stage for scalable GPU health dashboards and alerting.
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