Stop letting non-deterministic LLM agents hallucinate tool parameters. nulltrace provides deterministic Python orchestration to scrub telemetry, correlate ServiceNow alerts with logs, and generate root-cause hypotheses reliably.
ServiceNow, Elastic, Dynatrace, CloudWatch
Zero-Trust Python PII & JWT Masking
OpenAI, Bedrock, Anthropic, Ollama
Structured Workflows & ServiceNow Updates
Test how nulltrace orchestrates multi-tool telemetry ingestion, applies deterministic PII scrubbing, and performs multi-model root-cause correlation.
Why nulltrace over Raw MCP or Custom Scripts?
Unlike MCP tools where the LLM decides workflow paths non-deterministically, nulltrace uses DAGs to guarantee execution sequence.
Scrubs sensitive JWT tokens, SSH keys, passwords, and PII in Python memory before logs hit external LLM provider context windows.
Built-in resilience. Automatically failover from Claude 3.5 Sonnet to GPT-4o or local Ollama if an API rate limit or outage occurs during P1 alerts.
Normalizes disparate Elastic logs, Dynatrace metrics, and CloudWatch alarms into standardized Pydantic schemas automatically.
Clean, intuitive syntax designed for production engineers and SRE teams.
from nulltrace.connectors import ServiceNowConnector, ElasticConnector, DynatraceConnector
from nulltrace.llm import LLMRouter
from nulltrace.engine import TriageEngine
# 1. Initialize Telemetry Connectors
servicenow = ServiceNowConnector(instance_url="https://dev1234.service-now.com")
elastic = ElasticConnector(hosts=["http://localhost:9200"])
dynatrace = DynatraceConnector(tenant_id="abc12345")
# 2. Configure Resilient Provider-Agnostic LLM Router
router = LLMRouter(
primary_provider="anthropic/claude-3-5-sonnet",
fallback_providers=["openai/gpt-4o", "bedrock/anthropic.claude-v2"]
)
# 3. Instantiate Engine with In-Memory Security Policies
engine = TriageEngine(
incident_source=servicenow,
telemetry=[elastic, dynatrace],
llm_router=router,
enable_pii_masking=True
)
# 4. Orchestrate Automated Incident Triage Workflow
result = engine.run_triage(incident_id="INC009412")
print(result.root_cause_hypothesis)