shiftscope 0.1.0

Migration intelligence framework for cloud-native infrastructure API transitions

ShiftScope

Migration intelligence for cloud-native infrastructure.

ShiftScope is a pluggable framework for building migration intelligence analyzers for Kubernetes infrastructure API transitions. Unlike API version detectors (Pluto, kubent) that only flag deprecated apiVersion strings, or format converters (ingress2gateway) that only transform YAML, ShiftScope provides semantic risk analysis, implementation matching, and structured migration findings through a pluggable analyzer SDK.

Why ShiftScope?

Tool	Detection	Conversion	Risk Analysis	MCP	Pluggable SDK
Pluto / kubent	apiVersion only	-	-	-	-
ingress2gateway	-	YAML transform	-	-	-
Konveyor AI	app code	app code	app-layer	partial	-
ShiftScope	semantic	-	annotations, TLS, feature gates	native	yes

Quick Start

# Install
pip install shiftscope[cli]

# List available analyzers
shiftscope list

# Analyze an Ingress manifest for Gateway API migration
shiftscope analyze gateway-api manifests/ingress.yaml --output markdown

# Analyze a NetworkIntent for DRA migration
shiftscope analyze dra-network intent.json --output json

# Analyze a Helm chart for v4 readiness
shiftscope analyze helm4-readiness charts/my-app/ --output markdown

Built-in Analyzers

Gateway API (gateway-api)

Ingress NGINX → Gateway API migration intelligence.

• 5 annotation portability rules (CORS, backend-protocol, auth-tls-secret, server-snippet, ssl-redirect)
• 3 TLS risk rules (wildcard TLS, frontend mTLS/coalescing, backend protocol)
• 1 unknown annotation catcher
• 6 implementation profiles (Envoy Gateway, NGINX Gateway Fabric, Cilium, Kong, Contour, Traefik)

DRA Networking (dra-network)

Device Plugin → Dynamic Resource Allocation migration intelligence.

• Alpha feature gate detection (extended_resource_mapping, consumable_capacity, partitionable_devices)
• RDMA/bandwidth requirements analysis
• Legacy bridge (SR-IOV/Multus) migration path detection
• Topology alignment (NUMA/PCI) requirements
• Workload kind validation

Helm 4 Readiness (helm4-readiness)

Helm 3 → Helm 4 / Charts v3 readiness analysis.

• Chart API v2 detection with v3 migration guidance
• Go template complexity analysis
• Resource sequencing needs (HIP-0025)
• .helmignore parity review
• Values parent/subchart transform detection

Architecture

┌──────────────────────────────────────────────────┐
│                 ShiftScope SDK                    │
│                                                  │
│  Core Models ─── Renderers ─── Eval Harness      │
│  (Pydantic)      (JSON/MD)    (golden-file)      │
│                                                  │
│  Rule ABC ────── Analyzer ABC ── Registry        │
│  (applies_to     (run_rules)    (entry_points    │
│   + evaluate)                    discovery)       │
│                                                  │
│  CLI ─────────── MCP Bridge                      │
│  (Typer,          (FastMCP,                      │
│   auto-gen)        auto-gen)                     │
└──────────────────────────────────────────────────┘
        │              │              │
   Gateway API    DRA Network    Helm 4
   Analyzer       Analyzer       Analyzer

Writing a Custom Analyzer

from shiftscope import Analyzer, Rule, Finding, Severity, Report

class MyRule(Rule):
    rule_id = "my-check"
    severity = Severity.WARNING

    def applies_to(self, context):
        return "config" in context

    def evaluate(self, context):
        if context["config"].get("deprecated_field"):
            return Finding(
                rule_id=self.rule_id,
                severity=self.severity,
                title="Deprecated field detected",
                detail="This field is removed in the next version.",
                evidence=f"deprecated_field={context['config']['deprecated_field']}",
                recommendation="Migrate to the new field.",
            )
        return None

class MyAnalyzer(Analyzer):
    name = "my-analyzer"
    version = "0.1.0"
    description = "Custom migration analyzer"

    def __init__(self):
        self._rules = [MyRule()]

    def analyze(self, input_path, **kwargs):
        context = {"config": load_config(input_path)}
        return Report(
            analyzer_name=self.name,
            analyzer_version=self.version,
            source=input_path,
            findings=self.run_rules(context),
        )

    def list_rules(self):
        return list(self._rules)

Register via entry points in your pyproject.toml:

[project.entry-points."shiftscope.analyzers"]
my-analyzer = "my_package:MyAnalyzer"

MCP Integration

ShiftScope exposes all analyzers as MCP tools for AI agent consumption:

from shiftscope.mcp.bridge import create_mcp_server
from shiftscope.core.analyzer import AnalyzerRegistry

registry = AnalyzerRegistry()
registry.discover()
server = create_mcp_server(registry)
server.run()  # Exposes analyze_gateway_api, analyze_dra_network, etc.

Development

git clone https://github.com/thc1006/shiftscope.git
cd shiftscope
make bootstrap    # requires uv
make test         # 124 tests
make lint         # ruff check
make verify       # lint + test + compileall

Roadmap

See ADR-001 for the full architectural decision record, cross-validation results, and phase-by-phase roadmap.

Phase	Status	Scope
1: Core SDK + Reference Analyzer	Done	Models, Rule/Analyzer ABC, renderers, CLI, MCP bridge, Gateway API analyzer
2: Multi-Analyzer + CI	Done	DRA + Helm 4 analyzers, GitHub Actions CI, CodeQL
3: AI Augmentation	Next	Telco + agent readiness analyzers, PydanticAI, A2A
4: CNCF Sandbox	Planned	Landscape listing, TAG presentation, Sandbox proposal
5: Ecosystem	Planned	GitHub Action, Argo Workflows, KubeCon NA 2026

License

Apache License 2.0