# landerox.com > Fernando Landero, Senior Consultant & Engineer in Cloud, Data & AI Platforms on Google Cloud, AWS and private cloud. Fernando Landero is an independent Senior Consultant & Engineer in Cloud, Data & AI Platforms, with over 15 years in technology (the last 7 on cloud and data platforms). He designs architectures, writes production code and automates platforms on Google Cloud (GCP), AWS and private cloud: Terraform and policy-checked infrastructure, GKE/Kubernetes, batch and streaming pipelines with Apache Spark, BigQuery, dbt and Airflow, and AI workflows with RAG retrieval, agent orchestration and observability (OpenTelemetry, Langfuse). Recent work: banking and finance, retail and energy. Bilingual site: English at https://landerox.com/, Spanish at https://landerox.com/es/. Every page listed below is also published as Markdown at the linked address. Contact: contacto@landerox.com, meetings at https://calendly.com/landerox/30min, https://github.com/landerox and https://www.linkedin.com/in/landerox/. ## Profile - [Home](): Introduction, proof, core expertise and contact - [About](): Profile, focus areas and experience - [Tech Stack](): Production tools and research candidates - [Collaboration & Contact](): Typical requests, engagements, time zones and scheduling ## Projects - [Overview](): Open-source software, production blueprints, research labs, the tech radar and interactive tools - [Open Source](): ZDX, an MIT-licensed Zsh toolkit for searchable development workflows with reviewable changes (https://github.com/landerox/zdx-suite), and this site's build pipeline and UX principles - [Production Blueprints](): Upstream foundations, workload fit, shared operations responsibilities and production readiness gates - [Research Labs](): Internal project status, evaluation contracts and research baselines - [Tech Radar](): Dated upstream research and adoption conditions, not published internal benchmark results - [Interactive Tools](): Four local worksheets: retry policies during an outage, table files and compaction, agent crash recovery and evaluation statistics; no model or remote execution ## Blog - [Overview](): Technology comparisons with dated editorial 1–5 ratings, the rating method and primary sources - [Object Storage](): Open-source servers and gateways by workload, release status, S3 limits and recovery - [Table Formats & Catalogs](): Iceberg, Delta, Hudi and DuckLake; table, catalog and engine boundaries - [Workflow Orchestrators](): Airflow, Dagster and alternatives by execution model, licensing and recovery - [Transformation & Modeling](): dbt Core, SQLMesh, Dataform and Bruin by model lifecycle and deployment responsibility - [OLAP](): Distributed, embedded and PostgreSQL options, including AGPL candidates - [Vector](): Qdrant and alternatives by filtered retrieval, license, deployment and evaluation - [Graph](): Neo4j Community, AGE and alternatives by graph model, edition, deployment and recovery - [BI & Visualization](): Superset, Metabase and alternatives by reader workflow and permissions - [Signals & Tools](): Metrics, logs, traces, profiles, collectors and dashboards compared by architectural role ## Reference - [Technical glossary](): Authored bilingual definitions with stable anchors, examples, caveats, related terms and primary sources