Pre-pass and post-pass health checks are critical automation patterns used to ensure that satellite ground station operations begin and end in known, safe, and verifiable states. In scheduling automation and control environments, these checks act as guardrails around each satellite contact, validating readiness before execution and confirming system integrity afterward. Without structured health checks, automation risks executing passes on misconfigured, degraded, or unsafe infrastructure. These checks transform pass execution from a best-effort activity into a controlled, repeatable process. They also provide early detection of issues that could otherwise propagate silently across subsequent passes. Automation templates formalize these checks so they are consistent, auditable, and scalable.
Table of contents
- What Are Pre-Pass and Post-Pass Health Checks
- Why Health Checks Are Essential to Automation
- Pre-Pass Health Check Objectives
- Post-Pass Health Check Objectives
- Designing Health Check Automation Templates
- Integration with Schedulers and Control Systems
- Handling Failures and Degraded States
- Scaling Health Checks Across Networks
- Pre- and Post-Pass Health Checks FAQ
- Glossary
What Are Pre-Pass and Post-Pass Health Checks
Pre-pass and post-pass health checks are automated validation steps executed immediately before and after a scheduled satellite pass. Pre-pass checks confirm that all required systems are ready to support the upcoming contact. Post-pass checks verify that systems have returned to a stable and expected state after execution. These checks bookend the operational window, creating a controlled envelope around each pass. They reduce reliance on assumptions about system readiness. Instead, readiness and recovery are verified explicitly.
In automated environments, health checks are not informal observations but structured workflows. Each check evaluates a defined set of conditions and produces a clear outcome. These outcomes directly influence whether automation proceeds, pauses, or escalates. Health checks therefore function as decision points rather than passive monitoring. When implemented consistently, they improve reliability and operational confidence. They are foundational to safe, repeatable automation.
Why Health Checks Are Essential to Automation
Automation assumes that systems behave predictably, but real-world infrastructure degrades, drifts, and fails over time. Health checks compensate for this reality by continuously validating assumptions. Without them, automation may proceed based on outdated or incorrect state information. This increases the risk of failed passes, equipment stress, or safety violations. Health checks reduce these risks by enforcing verification before action.
Health checks also improve fault isolation and recovery. By evaluating system state at known boundaries, operators gain clarity about when and where issues arise. This makes troubleshooting faster and more accurate. In high- throughput environments, small issues can quickly compound. Health checks interrupt this cascade early. They are therefore not overhead but a form of operational insurance.
Pre-Pass Health Check Objectives
The primary objective of pre-pass health checks is to confirm readiness. This includes validating antenna state, control system availability, RF chain configuration, network connectivity, and safety interlocks. Pre-pass checks ensure that prerequisites for execution are satisfied before automation commits resources. They also confirm that no active inhibits or maintenance states conflict with the upcoming pass. Readiness must be explicit, not inferred.
Pre-pass checks also establish a baseline for later comparison. By capturing system state before execution, post-pass analysis becomes more meaningful. This baseline helps distinguish between pre-existing issues and those introduced during the pass. In automated systems, this context is essential for accurate diagnosis. Pre-pass checks therefore serve both operational and analytical purposes. They are the starting point of controlled execution.
Post-Pass Health Check Objectives
Post-pass health checks focus on recovery and validation after execution. They confirm that systems have exited the pass cleanly and returned to expected idle or standby states. This includes verifying antenna positioning, RF shutdown, resource release, and data pipeline stability. Post-pass checks detect latent failures that may not have impacted the just-completed pass but could affect subsequent ones. They close the loop on execution.
These checks also validate automation behavior itself. Unexpected states after a pass may indicate flaws in workflows or integrations. Capturing this information immediately improves observability. Post-pass health checks therefore support continuous improvement of automation logic. They help ensure that each pass leaves the system in a known-good state. This predictability is critical for back-to-back scheduling.
Designing Health Check Automation Templates
Automation templates standardize how health checks are defined and executed. A template specifies what conditions to check, how to evaluate them, and what outcomes mean. This structure ensures consistency across passes, missions, and sites. Templates separate intent from implementation, making them easier to review and evolve. They also reduce the risk of ad hoc or incomplete checks.
Well-designed templates are modular and composable. Common checks can be reused across different workflows, while mission-specific checks can be layered on top. Templates should produce machine-readable results that automation can act on directly. Human-readable summaries support operational awareness. By treating health checks as code, teams gain versioning, testing, and auditability. Templates become part of the automation contract.
Integration with Schedulers and Control Systems
Health checks must be tightly integrated with scheduling and control systems to be effective. Schedulers should invoke pre-pass checks automatically before committing a pass to execution. Control systems must respect the outcomes of these checks and refuse unsafe actions. This integration ensures that health checks are enforced rather than advisory. Automation decisions depend on their results.
Post-pass checks feed information back into the scheduling system. If a resource fails recovery checks, it may be marked unavailable for subsequent passes. This feedback loop enables dynamic adaptation to real conditions. Tight integration prevents known-bad states from being reused. It also supports automated escalation when thresholds are exceeded. Health checks become an active part of scheduling intelligence.
Handling Failures and Degraded States
Not all health check failures require immediate abort. Some conditions may be degraded but acceptable within defined limits. Automation templates should distinguish between hard failures and warnings. This allows systems to make nuanced decisions rather than binary ones. Clear classification prevents unnecessary disruption.
When failures do require stopping automation, escalation paths must be defined. This may involve retrying checks, placing resources into maintenance, or notifying operators. Automation should fail safely and predictably. Silence is never an acceptable response to failed health checks. Explicit handling builds confidence in automated decisions.
Scaling Health Checks Across Networks
In multi-site or networked environments, health check templates must scale consistently. Standardization across sites enables centralized visibility and comparison. Local variations can be accommodated through configuration rather than divergence. This balance supports both flexibility and control. Scalable design prevents fragmentation.
Aggregated health data enables network-wide decision-making. Patterns of recurring issues can be identified and addressed proactively. Scaling health checks also supports lights-out operations by increasing trust in automation. When checks are consistent and reliable, human oversight can be reduced safely. Network-scale health validation is a prerequisite for high automation maturity.
Pre- and Post-Pass Health Checks FAQ
Are health checks the same as monitoring? No, monitoring observes system behavior continuously, while health checks evaluate specific conditions at defined moments. Health checks produce explicit pass or fail outcomes. They are decision points rather than observations. Monitoring informs health checks but does not replace them. Both are necessary for robust automation.
Can health checks slow down operations? Properly designed health checks add minimal overhead compared to the cost of failed passes. Automation executes them quickly and consistently. The time spent validating readiness is usually far less than the time lost to recovery. Health checks improve efficiency by preventing avoidable failures. They are an investment in reliability.
Should health check logic differ by mission? Core infrastructure checks should be consistent across missions, while mission-specific checks can be added as extensions. This layered approach maintains standardization while supporting customization. Clear separation avoids duplication. Templates make this approach practical and maintainable.
Glossary
Pre-Pass Health Check: An automated validation performed before a satellite pass begins.
Post-Pass Health Check: An automated validation performed after a satellite pass completes.
Automation Template: A reusable definition of checks, logic, and outcomes.
Degraded State: A condition where a system operates with reduced capability.
Escalation: Transfer of control or attention to higher-level automation or humans.
Baseline State: The recorded system condition used for comparison and validation.
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