fix(inference): refine scaling and rerouting rules and action behavior
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d062bfb
- Updated task-2 and task-3 descriptions for clearer scaling and rerouting guidelines
- Modified SCALE_DOWN action to first cancel pending boots before removing active capacity
- Changed parsing of target_node_id and parameter to handle None values correctly
- Allowed NO_OP action to always succeed without target node validation
- Improved SCALE_DOWN implementation to prioritize canceling pending capacity
- Clarified cost tiers to classify pending capacity with justified excess at moderate rate
- Adjusted cost calculation for active and pending capacity to reflect tiered charging accurately
fix(inference): add debugging and error handling for env.step action calls
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b84be63
- Log each action step with compacted action string for better traceability
- Catch and log RuntimeError exceptions during env.step to identify failures
- Re-raise exceptions after logging to maintain original error flow
- Ensure printed debug information flushes stdout immediately for real-time monitoring
feat(reward): add comprehensive AntiAtropos reward function specification
- Provide detailed Markdown documentation explaining reward function design
- Describe multi-scale control signal architecture for Autonomous SRE
- Explain Lyapunov graph energy, reward composition, sigmoid normalization
- Outline layered action-efficiency penalties and episode grading system
- Highlight theoretical guarantees and practical innovation in reward design
fix(environment): correct idle capacity calculation to prevent negative values
- Adjust idle capacity formula to use max(0, ...) to avoid negative idle counts
- Clarify commented explanation to reflect correction for idle capacity calculation
…
perf(environment): improve cost model with three-tier capacity pricing
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92019fc
- Import DEFAULT_CAPACITY constant from simulator module as baseline capacity
- Update Kubernetes deployment replicas from 1 or 2 to 3 for all services in local-laptop and aws manifests
- Increase pod resource quota from 30 to 45 to support higher replica count
- Enhance _compute_cost() method with a three-tier cost calculation
- Define tier 1 as baseline capacity at cheap base rate up to DEFAULT_CAPACITY
- Define tier 2 as needed excess capacity charged at moderate 4× base rate
- Define tier 3 as idle excess capacity charged at high 20× penalty rate
- Provide clear incentives for scaling just enough to meet traffic demand without overprovisioning
refactor(simulator): add feedback on action effects and enforce capacity discipline
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f55f75f
- Extend apply_action() to return boolean indicating if action affected state
- Prevent silent discards by explicitly handling no-op and invalid actions
- Remove artificial max capacity cap; rely on cost function to limit scaling
- Update scaling logic to allow larger max capacity per node (sentinel value)
- Adjust simulator and environment to penalize wasted or rejected actions
- Enhance handling of critical nodes to reject forbidden shed load attempts
- Improve status update logic: scaling up repairs DEGRADED node status
- Update task descriptions and docs to emphasize reactive scaling over proactive
- Tune environment and reward normalization parameters for balance between cost and SLA compliance
better task 3
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74770e8
fixes
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3550e4d
Merge branch 'integrate/k8s-tennodes' of https://github.com/PranavKK1201/Anti-Atropos into integrate/k8s-tennodes
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9dda2d2
reward tuning
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faa8a6b
graph modelling
PranavKK1201
b5e5650
model changes
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9db539d
fixed envs
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4dd5987
fixed
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0cfa2c4
str
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7fa4a6f
fix reqs
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d6496d4
chore(kubernetes): support unbounded max replicas and enhance local setup
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923f89f
- Allow ANTIATROPOS_MAX_REPLICAS to be empty or 'unbounded' for no scale-up limit
- Adjust scaling logic to handle unbounded max replicas correctly
- Update .env.example with local defaults and new Prometheus queries
- Simplify start-grafana.ps1 for local Grafana setup without AWS credentials
- Add kind cluster config with max pods set to 250 for local testing
- Enhance local-laptop.yaml with prometheus metrics exposition and python http server
- Update LOCAL_LAPTOP_FASTAPI_GUIDE.md to document unbounded max replicas and setup changes
deploy
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5a30495
feat: implement Kubernetes executor for automated cluster scaling and infrastructure management
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cf2697b
upgraded to 10 nodes
PranavKK1201
d6439a8
feat(curriculum): add progressive training curriculum management
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52a986a
- Introduce CurriculumStage dataclass to define tasks with step limits, thresholds, temps, and retries
- Define CURRICULUM list with staged tasks of increasing difficulty and parameters
- Implement CurriculumTracker to track current stage, report scores, handle retries, and progress
- Add retry temperature adjustment and automatic skip after max retries for exploration encouragement
inference updated and syntax validation
PranavKK1201
7f70b66
ui and inference changes
PranavKK1201
94aef6f
feat: implement AntiAtroposEnvironment for SRE simulation and add Kubernetes integration tests
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6e9888e
Add reward handling and normalization features to environment
- Introduced raw and normalized reward attributes in ClusterObservation and AntiAtroposEnvironment.
- Implemented reward normalization logic in stability module.
- Updated observability metrics to track raw and normalized rewards.
- Added tests for reward normalization and environment reward behavior.
modified tasks for compatibility and added the inference.py script
PranavKK1201
a693df5
feat: Add observability setup guide and integrate Prometheus and Grafana
- Introduced OBSERVABILITY_SETUP.md for comprehensive observability setup instructions.
- Added docker-compose configuration for Prometheus and Grafana.
- Created Grafana dashboards for AntiAtropos live control plane and Kubernetes overview.
- Updated README.md to reflect Kubernetes integration and observability features.
- Implemented Prometheus metrics endpoint in the AntiAtropos server.
- Enhanced Kubernetes integration with explicit workload mapping and telemetry label mapping.
- Added tests for Kubernetes integration and Prometheus adapter functionality.
basic of grafan, kuber, and prometheus added
PranavKK1201
77ede9e
added VIP nodes, which have a higher weightage
PranavKK1201
4b5c463
fixed task 1, 2, 3
PranavKK1201
3a871a0
feat: implement core SRE simulation environment, Pydantic schemas, and physics models for task-based cluster management
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5144b7e
kinda almost fixed task 1
PranavKK1201
07e80ad
normalized, better grading and env
PranavKK1201
12439fa
tmp
PranavKK1201
279ccf2
update cost model and observation descriptions for clarity and accuracy
