WFGY/ProblemMap/GlobalFixMap/Cloud_Serverless/serverless_ci_cd.md

Serverless CI/CD Guardrails

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Think of this page as a desk within a ward.
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Serverless platforms simplify infrastructure but often hide deployment complexity behind CI/CD pipelines.
When build steps, environment configuration, and rollout order are not carefully controlled, deployments can appear successful while services fail at runtime.

This page provides guardrails to make serverless CI/CD pipelines predictable, observable, and safe to roll out across regions.

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When to use this page

• Deployments succeed but the first requests fail.
• New releases break environment variables or secrets.
• Serverless functions deploy but cannot reach dependencies.
• CI pipelines run migrations and application rollout simultaneously.
• Canary deployment passes but full rollout causes failures.

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Open these first

• Boot order and deploy sequencing:
  Bootstrap Ordering

• Circular dependency in rollout pipelines:
  Deployment Deadlock

• First call failure after deploy:
  Pre-Deploy Collapse

• Schema and payload contracts:
  Data Contracts

• Live monitoring and rollback:
  Debug Playbook

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Acceptance targets

• CI pipeline completes without manual intervention.
• Deployment artifacts reproducible across environments.
• No increase in error rate after rollout.
• Environment variables and secrets consistent across revisions.
• Canary deployment accurately predicts full rollout behavior.

For RAG pipelines:

• ΔS(question, retrieved) drift ≤ 0.03 after deploy.
• Index versions identical across environments before traffic.

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Fix in 60 seconds

1. Separate build, migration, and deploy stages

   CI pipelines must isolate artifact build, schema migration, and application rollout.

2. Version artifacts explicitly

   Every deploy should carry:

   • release_id
   • schema_rev
   • index_hash

3. Use canary deployments

   Roll out to a small percentage of traffic before global rollout.

4. Gate deploy on health probes

   Services should not receive traffic until environment variables, secrets, and dependencies verify successfully.

5. Enable automated rollback

   If error rate or latency spikes, pipeline must revert automatically.

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Patterns that work

• Immutable build artifacts

  Build once and promote the same artifact across staging and production.

• Pipeline stage contracts

  Each stage verifies artifacts, migrations, and health before continuing.

• Canary plus gradual rollout

  Deploy first to a small subset of users or a single region.

• Deployment freeze windows

  Prevent simultaneous deploys across services that share dependencies.

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Typical breakpoints → exact fix

• Deploy succeeds but service crashes immediately

  Environment variables missing or incompatible.

  Open:
  Pre-Deploy Collapse

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• Pipeline deadlocks waiting for services

  Deploy order incorrect or circular dependency exists.

  Open:
  Deployment Deadlock

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• Migration and deploy run simultaneously

  Application reads partially migrated schema.

  Open:
  Bootstrap Ordering

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• Canary passes but full rollout fails

  Canary environment differs from production configuration.

  Open:
  Data Contracts

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Minimal recipes you can copy

A) CI pipeline stages

Pipeline stages

1. Build artifact
2. Run tests
3. Execute migrations
4. Deploy canary revision
5. Verify health probes
6. Gradual rollout
7. Promote release

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B) Deployment contract

Deployment metadata

release_id = r2025-08-30
schema_rev = sc-21
index_hash = a1b2c3

Services start only if versions match expected values.

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C) Rollback rule

Rollback trigger

If error_rate > baseline + 2%
or latency > SLO threshold

Then:
- revert to previous revision
- pause pipeline
- alert operator

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Observability you must add

• Deployment success and rollback metrics.
• Error rate by revision.
• Environment variable mismatch detection.
• CI pipeline duration and stage failure counts.
• Canary vs production performance comparison.

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Verification

• Deployment completes with no service restarts.
• Canary and full rollout metrics match expected behavior.
• Environment variables consistent across revisions.
• No schema mismatches or runtime configuration errors.

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When to escalate

• CI pipeline repeatedly fails in the same stage.
• Deployments succeed but services remain unhealthy.
• Canary behavior diverges significantly from production.
• Rollback fails or leaves system in inconsistent state.

Investigate environment configuration, pipeline orchestration, and dependency readiness before retrying deploy.

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🔗 Quick-Start Downloads (60 sec)

Tool	Link	3-Step Setup
WFGY 1.0 PDF	Engine Paper	1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + ”
TXT OS (plain-text OS)	TXTOS.txt	1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

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Explore More

Layer	Page	What it’s for
⭐ Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
⚙️ Engine	WFGY 1.0	Original PDF tension engine and early logic sketch
⚙️ Engine	WFGY 2.0	Production tension kernel for RAG and agent systems
⚙️ Engine	WFGY 3.0	TXT based Singularity tension engine
🗺️ Map	Problem Map 1.0	Flagship 16 problem RAG failure taxonomy
🗺️ Map	Problem Map 2.0	Global Debug Card
🗺️ Map	Problem Map 3.0	AI troubleshooting atlas
🧰 App	TXT OS	.txt semantic OS
🧰 App	Blah Blah Blah	Abstract Q&A
🧰 App	Blur Blur Blur	Text-to-image generation
🏡 Onboarding	Starter Village	Guided entry

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