Education· Last updated April 6, 2026

Automate SLA Reporting and Compliance Certificates with DocForge API in Python

Build automated SLA report generation and compliance certificate workflows using DocForge API. Generate branded PDFs from performance data in seconds, not hours.

Automate SLA Reporting and Compliance Certificates with DocForge API in Python

SLA reports and compliance certificates are among the most document-intensive workflows in enterprise software. Customer success teams generate monthly SLA reports for dozens of enterprise accounts. Compliance teams produce quarterly audit certificates for SOC 2, ISO 27001, or industry-specific frameworks. Every report needs the right data, the right branding, and the right formatting — at scale.

Doing this manually in PowerPoint or Word takes hours per report. With the DocForge API, you can generate professional, branded PDF documents from structured data in seconds.

This guide walks through building a complete SLA reporting and compliance certificate automation pipeline in Python.

What We're Building

Two document workflows:

  1. Monthly SLA Report: Pulls uptime, latency, and incident data from your monitoring systems, generates a branded PDF for each enterprise customer
  2. Compliance Certificate: Generates a signed certificate PDF confirming that a service or system met its compliance requirements for a given period

Step 1: Setup

pip install requests python-dotenv
import os
import json
import requests
from datetime import datetime, date
from typing import Any
from dotenv import load_dotenv
 
load_dotenv()
 
DOCFORGE_KEY = os.getenv("YOUR_API_KEY")
DOCFORGE_BASE = "https://apivult.com/api/docforge"
 
HEADERS = {
    "X-RapidAPI-Key": DOCFORGE_KEY,
    "Content-Type": "application/json"
}

Step 2: Define the SLA Report Template

DocForge uses a JSON template format that separates layout from data. Templates can be stored server-side and referenced by ID, or sent inline.

SLA_REPORT_TEMPLATE = {
    "template_id": "sla_monthly_report_v2",
    "document_type": "pdf",
    "page_size": "A4",
    "branding": {
        "logo_url": "https://apivult.com/_static/logo.png",
        "primary_color": "#1e40af",
        "font_family": "Inter"
    },
    "sections": [
        {
            "type": "header",
            "fields": ["report_title", "customer_name", "report_period", "generated_date"]
        },
        {
            "type": "summary_metrics",
            "title": "Service Level Summary",
            "metrics": [
                {"label": "Uptime", "field": "uptime_pct", "format": "percentage", "threshold": 99.9},
                {"label": "Avg Response Time", "field": "avg_latency_ms", "format": "ms"},
                {"label": "P99 Latency", "field": "p99_latency_ms", "format": "ms"},
                {"label": "Incidents", "field": "incident_count", "format": "integer"},
                {"label": "SLA Breaches", "field": "sla_breach_count", "format": "integer"}
            ]
        },
        {
            "type": "table",
            "title": "Incident Summary",
            "columns": ["date", "severity", "duration_minutes", "affected_services", "root_cause"],
            "data_field": "incidents"
        },
        {
            "type": "chart",
            "chart_type": "line",
            "title": "Uptime Trend (Last 30 Days)",
            "data_field": "daily_uptime_data"
        },
        {
            "type": "compliance_statement",
            "field": "sla_compliance_statement"
        },
        {
            "type": "footer",
            "fields": ["generated_by", "document_id", "page_numbers"]
        }
    ]
}

Step 3: Pull SLA Data from Monitoring Systems

def get_sla_metrics(
    customer_id: str,
    start_date: date,
    end_date: date,
    monitoring_api_url: str,
    monitoring_token: str
) -> dict:
    """Fetch SLA metrics for a customer from your monitoring system."""
    resp = requests.get(
        f"{monitoring_api_url}/customers/{customer_id}/metrics",
        params={
            "start": start_date.isoformat(),
            "end": end_date.isoformat(),
            "metrics": "uptime,latency,incidents"
        },
        headers={"Authorization": f"Bearer {monitoring_token}"}
    )
    resp.raise_for_status()
    return resp.json()
 
 
def build_sla_report_data(
    customer: dict,
    metrics: dict,
    report_period: str
) -> dict:
    """Structure SLA data for the DocForge template."""
    uptime_pct = metrics["uptime_percentage"]
    sla_target = customer.get("sla_target_pct", 99.9)
    breach_count = sum(
        1 for day in metrics.get("daily_uptime", [])
        if day["uptime_pct"] < sla_target
    )
 
    # Build compliance statement
    if uptime_pct >= sla_target:
        compliance = (
            f"This report confirms that {customer['company_name']} achieved "
            f"{uptime_pct:.3f}% uptime during {report_period}, meeting the "
            f"contracted SLA target of {sla_target}%."
        )
    else:
        shortfall = sla_target - uptime_pct
        compliance = (
            f"Service availability during {report_period} was {uptime_pct:.3f}%, "
            f"which fell {shortfall:.3f}% below the contracted SLA target of "
            f"{sla_target}%. Service credits have been applied per Section 4.2 "
            f"of the Master Service Agreement."
        )
 
    return {
        "report_title": f"Monthly Service Level Report — {report_period}",
        "customer_name": customer["company_name"],
        "customer_id": customer["id"],
        "report_period": report_period,
        "generated_date": datetime.utcnow().strftime("%B %d, %Y"),
        "uptime_pct": uptime_pct,
        "avg_latency_ms": metrics["avg_latency_ms"],
        "p99_latency_ms": metrics["p99_latency_ms"],
        "incident_count": len(metrics.get("incidents", [])),
        "sla_breach_count": breach_count,
        "incidents": metrics.get("incidents", []),
        "daily_uptime_data": metrics.get("daily_uptime", []),
        "sla_compliance_statement": compliance,
        "generated_by": "APIVult Automated Reporting System",
        "document_id": f"SLA-{customer['id']}-{report_period.replace(' ', '-')}"
    }

Step 4: Generate SLA Report PDF

def generate_sla_report_pdf(report_data: dict) -> bytes:
    """Generate a PDF SLA report via DocForge API."""
    payload = {
        "template": SLA_REPORT_TEMPLATE,
        "data": report_data,
        "options": {
            "watermark": None,  # Set to "DRAFT" for previews
            "digital_signature": False,
            "compress": True
        }
    }
 
    resp = requests.post(
        f"{DOCFORGE_BASE}/generate",
        json=payload,
        headers=HEADERS
    )
    resp.raise_for_status()
    result = resp.json()
 
    if not result["success"]:
        raise ValueError(f"Document generation failed: {result['error']}")
 
    # DocForge returns base64-encoded PDF
    import base64
    return base64.b64decode(result["data"]["document_base64"])

Step 5: Generate Compliance Certificates

COMPLIANCE_CERT_TEMPLATE = {
    "template_id": "compliance_certificate_v1",
    "document_type": "pdf",
    "page_size": "A4",
    "orientation": "landscape",
    "branding": {
        "logo_url": "https://apivult.com/_static/logo.png",
        "primary_color": "#1e40af",
        "style": "formal_certificate"
    },
    "sections": [
        {
            "type": "certificate_header",
            "title": "Certificate of Compliance"
        },
        {
            "type": "certificate_body",
            "fields": [
                "entity_name", "framework", "audit_period",
                "compliance_scope", "certification_statement"
            ]
        },
        {
            "type": "certificate_signatures",
            "signatories": ["issued_by", "reviewed_by"],
            "date_field": "issue_date"
        },
        {
            "type": "certificate_footer",
            "fields": ["certificate_id", "valid_until", "verification_url"]
        }
    ]
}
 
 
def generate_compliance_certificate(
    entity_name: str,
    framework: str,
    audit_period: str,
    scope_items: list[str],
    issued_by: str,
    cert_id: str
) -> bytes:
    """Generate a compliance certificate PDF."""
    cert_data = {
        "entity_name": entity_name,
        "framework": framework,
        "audit_period": audit_period,
        "compliance_scope": scope_items,
        "certification_statement": (
            f"This certifies that {entity_name} has demonstrated compliance with "
            f"all applicable requirements of {framework} for the audit period "
            f"{audit_period}. All controls were assessed and found to be operating "
            f"effectively as of the audit completion date."
        ),
        "issued_by": issued_by,
        "reviewed_by": "Independent Compliance Reviewer",
        "issue_date": datetime.utcnow().strftime("%B %d, %Y"),
        "certificate_id": cert_id,
        "valid_until": "12 months from issue date",
        "verification_url": f"https://apivult.com/verify/{cert_id}"
    }
 
    payload = {
        "template": COMPLIANCE_CERT_TEMPLATE,
        "data": cert_data,
        "options": {
            "watermark": None,
            "digital_signature": True,
            "compress": True
        }
    }
 
    resp = requests.post(
        f"{DOCFORGE_BASE}/generate",
        json=payload,
        headers=HEADERS
    )
    resp.raise_for_status()
    result = resp.json()
 
    if not result["success"]:
        raise ValueError(f"Certificate generation failed: {result['error']}")
 
    import base64
    return base64.b64decode(result["data"]["document_base64"])

Step 6: Batch Report Generation

def generate_monthly_sla_reports(
    customers: list[dict],
    report_month: str,
    monitoring_api_url: str,
    monitoring_token: str,
    output_dir: str = "reports"
) -> list[str]:
    """Generate SLA reports for all enterprise customers."""
    import os
    os.makedirs(output_dir, exist_ok=True)
 
    generated = []
    failed = []
 
    for customer in customers:
        try:
            # Parse date range for the report month
            from dateutil.relativedelta import relativedelta
            from dateutil.parser import parse as parse_date
            month_start = parse_date(f"{report_month}-01").date()
            month_end = (month_start + relativedelta(months=1, days=-1))
 
            metrics = get_sla_metrics(
                customer["id"], month_start, month_end,
                monitoring_api_url, monitoring_token
            )
            report_data = build_sla_report_data(customer, metrics, report_month)
            pdf_bytes = generate_sla_report_pdf(report_data)
 
            filename = f"{output_dir}/SLA-{customer['id']}-{report_month}.pdf"
            with open(filename, "wb") as f:
                f.write(pdf_bytes)
 
            generated.append(filename)
            print(f"  ✅ Generated: {filename}")
 
        except Exception as e:
            failed.append({"customer_id": customer["id"], "error": str(e)})
            print(f"  ❌ Failed for {customer['id']}: {e}")
 
    print(f"\nGenerated {len(generated)} reports, {len(failed)} failed")
    return generated
 
 
if __name__ == "__main__":
    customers = [
        {"id": "ENT-001", "company_name": "Acme Corp", "sla_target_pct": 99.9},
        {"id": "ENT-002", "company_name": "Globex Industries", "sla_target_pct": 99.5},
        {"id": "ENT-003", "company_name": "Initech Systems", "sla_target_pct": 99.95}
    ]
 
    generate_monthly_sla_reports(
        customers=customers,
        report_month="2026-03",
        monitoring_api_url="https://internal-monitoring-api",
        monitoring_token=os.getenv("MONITORING_API_TOKEN"),
        output_dir="reports/2026-03"
    )

Business Impact

Teams that automate SLA and compliance document generation with DocForge report:

  • 90% reduction in time spent on report production (from 2–4 hours per report to under 30 seconds)
  • Zero formatting errors — templates enforce brand consistency every time
  • Same-day delivery of monthly reports instead of week-long production cycles
  • Audit-ready artifacts with document IDs and generation timestamps built in

For a customer success team managing 50 enterprise accounts, automated SLA reporting saves 100–200 hours per month.


Start generating professional SLA reports and compliance certificates automatically. Try DocForge API free — up to 50 documents per month at no cost.