Infrastructure

The platform foundation for ingesting, storing, processing, and delivering EO data at mission scale.

What Infrastructure Covers

Infrastructure defines the runtime backbone of an EO data platform: ingestion paths, storage tiers, compute environments, service interfaces, and network placement. It governs how archive ingestion, tasking ingestion, and third-party provider integrations are operationalized as one coherent system.

Why Infrastructure Matters

When infrastructure is strong, teams can onboard new suppliers quickly, scale processing safely, and deliver predictable APIs and downloads. When it is weak, latency rises, provenance breaks, costs spiral, and operations become brittle during peak mission demand.

What Good Looks Like

A mature platform uses clear service boundaries and separates compute for ingestion, processing, and delivery. It maintains raw, normalized, and derived storage layers; publishes searchable metadata; captures lineage at every major transformation point; and supports multi-region or sovereign deployment where data residency requires it.

Minimum Requirements

Support archive ingestion, tasking ingestion, and supplier onboarding through a repeatable integration model.
Implement raw, normalized, and derived storage layers with explicit lifecycle and cost controls.
Maintain metadata cataloging for discoverability and consistent API/download delivery.
Separate runtime workloads for ingestion, processing, and delivery with isolation controls.
Define backup, restore, and recovery objectives and test them regularly.

Core Architecture Components

Ingestion Paths

Design distinct ingestion lanes for historical archives, scheduled tasking returns, and third-party feeds. Capture quality checks, schema validation, and lineage markers at entry points.

Storage Tiers

Use raw landing zones, normalized analysis-ready stores, and derived product layers with lifecycle rules tied to retention and FinOps targets.

Catalog and Index Layer

Run a metadata catalog with searchable spatial, temporal, and product indexes that support discoverability across all suppliers.

Processing Environments

Isolate processing clusters by workload type and sensitivity to prevent noisy-neighbour contention and improve blast-radius control.

Delivery Interfaces

Provide stable APIs and download channels with consistent payloads, access controls, and service-level expectations.

Identity and Access Foundations

Apply centralized identity, scoped service roles, and policy enforcement at service boundaries.

Network and Regional Placement

Plan data residency placement, sovereign-region deployment, and private connectivity for regulated workloads.

Backup and Recovery Foundations

Protect metadata, indexes, and object storage with immutable backups, restore testing, and recovery runbooks.

Data Flow and Processing Topology

Use event-driven flow from ingest to normalization to derivation, with internal service boundaries that keep contracts explicit. Workload isolation should separate high-priority tasking from bulk backfill processing. Lineage capture points should be recorded at ingest, transform, publish, and delivery stages.

Infrastructure Decisions

Single-region vs multi-region and sovereign deployment strategy.
Centralized vs federated catalog architecture.
Supplier onboarding through adapters vs standardized ingestion contracts.
Storage-cost trade-offs between hot, warm, and archive tiers.

Metrics and Health Signals

Ingestion latency by source type (archive, tasking, third-party).
Catalog freshness and discoverability success rates.
Processing queue depth and cross-workload contention indicators.
Delivery latency and API/download success rates.
Restore test pass rates and recovery time achievement.
Storage and compute cost per delivered product.

Anti-Patterns

Combining ingestion, processing, and delivery in one shared runtime.
Skipping lineage capture until after incidents occur.
Adding suppliers through one-off scripts without onboarding standards.
Ignoring residency and sovereign placement requirements until late deployment.

Implementation Checklist

Is ownership clear?
Are minimum controls defined?
Are failure modes addressed?
Are measurable health signals defined?
Are anti-patterns named?
Are dependencies on other domains explicit?
Is there at least one EO-specific implementation example?
Is there a practical implementation checklist?

Example EO Patterns

National archive backfill into raw storage, automated normalization into COG collections, and derived tiling products for web delivery.
Tasking returns routed into a priority ingestion lane with separate processing compute and expedited API publishing.
Third-party SAR provider integrated through a supplier adapter that enforces common metadata contracts before catalog indexing.

Back to all domains