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Technical Astrology: House Meanings for System & Infrastructure Outages

Technical Astrology: House Meanings for System & Infrastructure Outages

These house meanings are used for interpreting event charts related to software, cloud infrastructure, CDNs, security systems, and distributed platforms. They are derived from observed patterns across real-world incidents including CrowdStrike, AWS, and multiple Cloudflare outages.


Client-visible behavior and how failure manifests.

  • Error pages and response codes
  • Fail-open vs fail-closed behavior
  • Whether the system panics or degrades gracefully

System tolerances and guarded boundaries.

  • Memory, file size, and feature limits
  • Parsing buffers and request body size
  • Capacity assumptions and safety thresholds

Internal interpretation and code-by-code decision flow.

  • Conditional execution logic
  • Assumed continuity between code paths
  • Metadata interpretation and internal queries

The structural base the entire system depends on.

  • Kernels and operating systems
  • Core proxy engines and base services
  • Lowest-level architectural assumptions

What the system produces after evaluation.

  • WAF allow/deny decisions
  • Bot scores and classifications
  • Rule evaluation and execution results

Routine work and how changes are rolled out.

  • Scheduled jobs and background processes
  • Deployment systems and rollout methods
  • Health checks, observability, and automation

How external behavior is interpreted.

  • Attack detection vs false attribution
  • DDoS suspicion and threat modeling
  • Security narratives masking internal faults

Hidden coupling beneath the surface.

  • Shared databases and clustered systems
  • Dependency chains and cross-service coupling
  • Cascading or compounding failures

Rules that apply everywhere at once.

  • Global configuration systems
  • Security and enforcement policies
  • Authority over network-wide behavior

How the outage appears externally.

  • Status pages and public communication
  • Duration, flapping, and instability
  • Visibility versus actual technical severity

Large-scale systems and how they subdivide.

  • Microservices and distributed clusters
  • Partial-fleet failures
  • Topology- or configuration-based impact

Unseen conditions waiting to be triggered.

  • Legacy code paths
  • Untested edge cases
  • Bugs that exist for years before activating