Once mission data leaves the ground station, it is rarely delivered as a continuous stream forever. Most missions rely on file-based delivery at some point, whether for payload products, logs, imagery, or archives. How those files move from one system to another has a direct impact on latency, reliability, operational complexity, and failure recovery.
Push, pull, and store-and-forward are the three most common file delivery patterns used in satellite missions. Each pattern represents a different assumption about who controls delivery, how failures are handled, and when data is considered “delivered.” This article explains how these patterns work in practice, where they fit best, and what operators should expect when things go wrong.
Table of contents
- Why File Delivery Patterns Matter
- What File Delivery Means in Missions
- Push-Based File Delivery
- Pull-Based File Delivery
- Store-and-Forward Delivery Model
- Latency, Reliability, and Control Tradeoffs
- Failure Modes and Recovery Behavior
- Choosing the Right Delivery Pattern
- File Delivery Patterns FAQ
- Glossary
Why File Delivery Patterns Matter
File delivery is often treated as an implementation detail, but it directly affects mission performance. A poorly chosen delivery pattern can introduce unexpected latency, create hidden backlogs, or fail silently during outages. Operators may see data “received” at the ground station but unavailable to users for hours without clear explanation.
Delivery patterns also define operational responsibility. They determine who initiates transfers, who detects failures, and who retries. Understanding these roles helps teams design clearer procedures and avoid assumptions that break down during anomalies.
What File Delivery Means in Missions
In mission contexts, file delivery usually involves discrete data products rather than continuous streams. These files may represent payload outputs, telemetry bundles, logs, or derived products generated by processing pipelines.
Unlike real-time streams, file delivery emphasizes completeness and integrity. A file is either delivered successfully or it is not. This binary nature shapes how systems detect errors, retry transfers, and confirm delivery to downstream systems or customers.
Push-Based File Delivery
In a push model, the producing system initiates delivery. Once a file is ready, it is sent automatically to a predefined destination. This pattern is common when low latency is desired and the producer has reliable connectivity to the consumer.
Push delivery simplifies the consumer’s role but increases responsibility on the producer. If the destination is unavailable, the producer must handle retries, queue files, or risk data loss. Operators should ensure that push systems have clear retry logic and visibility into delivery success.
Pull-Based File Delivery
In a pull model, the consumer initiates delivery. The producer makes files available, and downstream systems retrieve them when ready. This approach shifts control and scheduling to the consumer.
Pull delivery is often more resilient to intermittent connectivity. Consumers can retry safely and control load on their systems. However, latency depends on polling frequency and coordination. Without clear conventions, files may sit undelivered even though they are available.
Store-and-Forward Delivery Model
Store-and-forward combines elements of push and pull. Files are first written to intermediate storage, such as a staging server or object store. From there, they are delivered onward to one or more destinations.
This model decouples production from delivery. It improves resilience and supports multiple consumers but adds infrastructure and operational complexity. Operators must monitor storage health, retention, and backlog to avoid hidden delivery delays.
Latency, Reliability, and Control Tradeoffs
Push models favor low latency but are sensitive to destination availability. Pull models favor reliability and consumer control but introduce inherent delay. Store-and-forward prioritizes robustness at the cost of additional steps.
There is no universally correct choice. The right balance depends on mission priorities, network stability, and tolerance for delayed delivery. Understanding these tradeoffs prevents unrealistic expectations during operations.
Failure Modes and Recovery Behavior
Each delivery pattern fails differently. Push systems may fail loudly when destinations are unreachable. Pull systems may fail quietly if polling or credentials break. Store-and-forward systems may hide failures behind growing backlogs.
Operators should know how failures surface. Clear alerts, retry visibility, and delivery confirmation are essential regardless of pattern. A delivery system that “usually works” but provides little insight during failure creates operational risk.
Choosing the Right Delivery Pattern
Choosing a delivery pattern starts with mission intent. Time-critical alerts benefit from push delivery. Bulk data and archives often fit pull or store-and-forward models. Mixed missions may use multiple patterns simultaneously.
Operational maturity matters as well. Teams with strong monitoring and automation can manage more complex models safely. Simpler patterns may be preferable when staffing or tooling is limited.
File Delivery Patterns FAQ
Is push always faster than pull?
Usually, but only when the destination is available and retries are well managed.
Does store-and-forward increase latency?
Yes, but it also improves resilience and decouples system dependencies.
Can multiple patterns be used together?
Yes. Many missions use different patterns for different data types.
Glossary
Push delivery: Producer initiates file transfer to a consumer.
Pull delivery: Consumer retrieves files from a producer.
Store-and-forward: Intermediate storage used before final delivery.
Producer: System that creates mission data files.
Consumer: System or user that receives mission data.
Backlog: Accumulation of undelivered files.
More
