🧭 SLIs as Code in DevSecOps – A Comprehensive Guide

Posted on June 24, 2025June 24, 2025 | by priteshgeek

📌 1. Introduction & Overview

What is SLIs as Code?

SLIs as Code refers to the practice of defining and managing Service Level Indicators (SLIs) in a declarative, version-controlled, and automated way, similar to Infrastructure as Code (IaC). SLIs measure the performance, reliability, and correctness of systems from the user’s perspective.

Think of it as codifying your system’s performance expectations and metrics using configuration files that can be audited, versioned, and tested.

History & Background

Born from SRE (Site Reliability Engineering) practices at Google.
Initially implemented as dashboards or documentation.
With the rise of GitOps, IaC, and DevSecOps, SLI definitions have evolved to live in source code repositories.
Modern platforms like Prometheus, OpenTelemetry, Datadog, New Relic now support SLI integrations via code.

Why It’s Relevant in DevSecOps

Security-first mindset: Detect reliability & performance regressions early.
Auditability & Compliance: Code-based definitions are reviewable and traceable.
Automation: Integrate SLIs with CI/CD pipelines and incident response tools.
Consistency: Reduce human error via codified logic and thresholds.

📚 2. Core Concepts & Terminology

Term	Definition
SLI (Service Level Indicator)	A precise measurement of service behavior (e.g., request latency, error rate).
SLO (Service Level Objective)	A target value or threshold for an SLI (e.g., 99.9% availability).
SLA (Service Level Agreement)	A formal agreement based on SLOs, often with legal or financial implications.
SLIs as Code	A methodology to define, store, and deploy SLIs using code.

Integration with the DevSecOps Lifecycle

Stage	SLI Role
Plan	Define service goals and performance indicators.
Develop	Write SLI definitions alongside app code.
Build	Validate SLI syntax/config using CI tools.
Test	Simulate traffic to test thresholds and alerts.
Release	Deploy SLIs to monitoring systems.
Operate	Observe live SLIs and react to violations.
Monitor	Automate alerting and root cause analysis.

🏗️ 3. Architecture & How It Works

Components

SLI Definition Files
YAML, JSON, or HCL files defining metrics, labels, queries, and thresholds.
Metrics Backend
Systems like Prometheus, Datadog, or New Relic collect and store metrics.
Code Repositories
Git-based storage for SLI files, enabling versioning and PR reviews.
CI/CD Integrations
Validate and deploy SLI definitions automatically.
SLI Evaluation Engine
Tools like Nobl9, Sloth, or OpenSLO that read code and calculate SLI/SLO status.

Architecture Diagram (Textual Description)

[Git Repository] --> [CI/CD Tool (e.g., GitHub Actions)]
                          |
                          v
                [SLI Parsing Tool (e.g., Sloth)]
                          |
                          v
                [Monitoring Platform (e.g., Prometheus)]
                          |
                          v
               [Dashboards / Alert Manager / PagerDuty]

Integration Points

CI/CD: Validate SLI syntax on pull request.
Monitoring: Prometheus or Datadog as data source.
Cloud: Terraform integration to define SLIs as part of IaC.
Security: Integrate alerting with SIEM/SOAR tools for incident handling.

🚀 4. Installation & Getting Started

Prerequisites

Git and GitHub
Prometheus installed or cloud monitoring (e.g., GCP Monitoring, Datadog)
Go or Docker (for Sloth or Nobl9)
Basic knowledge of YAML/JSON

Step-by-Step Guide using Sloth (Open Source)

🔹 Step 1: Install Sloth

go install github.com/slok/sloth/cmd/sloth@latest

or use Docker

docker pull ghcr.io/slok/sloth:latest

🔹 Step 2: Define SLI in YAML

service: my-api-service
labels:
  team: backend
slos:
  - name: "High availability"
    objective: 99.9
    sli:
      events:
        error_query: sum(rate(http_requests_total{job="api",code=~"5.."}[5m]))
        total_query: sum(rate(http_requests_total{job="api"}[5m]))
    alerting:
      name: HighAvailability
      page_alert:
        threshold: 98.0

🔹 Step 3: Generate Prometheus Rules

sloth generate -i slo.yaml -o prometheus-rules.yaml

🔹 Step 4: Deploy to Prometheus

Add the generated prometheus-rules.yaml to your Prometheus configuration directory and reload the config.

🔹 Step 5: Automate with GitHub Actions

name: SLI Check

on: [push]

jobs:
  validate:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Validate SLI
        run: |
          sloth generate -i slo.yaml -o output.yaml

💼 5. Real-World Use Cases

1. E-commerce Platform (Checkout API)

SLI: 99.95% availability for /checkout endpoint
Benefit: Avoid downtime penalties during high traffic (Black Friday)

2. Banking App (Transaction latency)

SLI: <500ms for 95% of requests
Security use: Detect delays caused by fraud-detection services

3. Healthcare SaaS (Data pipeline integrity)

SLI: <0.1% data processing failures
Benefit: Avoid HIPAA compliance issues

4. Media Streaming Service (Buffer rate)

SLI: Buffering rate < 2% across 95th percentile
DevSecOps Focus: Optimize CDN and edge security rules

✅ 6. Benefits & Limitations

✔️ Key Advantages

🔐 Secure, testable definitions
🔁 Repeatability across environments
📜 Version-controlled and auditable
🔔 Tight integration with alerting tools
🤝 Alignment with DevSecOps shift-left mindset

❌ Limitations

Challenge	Details
Complex Syntax	YAML/JSON can get verbose for nested metrics
Tooling Diversity	Different formats for Datadog vs Prometheus vs New Relic
Metrics Accuracy	Poorly defined SLIs lead to alert fatigue or blind spots
Adoption Resistance	Teams unfamiliar with SLO/SLI culture may push back

🔐 7. Best Practices & Recommendations

✅ Store SLIs in version-controlled Git repositories
🔍 Review SLIs like code (PRs, reviews, changelogs)
📊 Use visual dashboards for SLI compliance tracking
🛡️ Integrate with security alerts (SIEM, PagerDuty)
📅 Audit regularly for SLA alignment
🧪 Test SLIs in staging with load generators
⛓️ Use as part of release gates in CI/CD

🔄 8. Comparison with Alternatives

Method	SLIs as Code	Manual Monitoring	Dashboard-Only SLIs
Auditability	✅ High	❌ Low	⚠️ Medium
Automation Ready	✅ Yes	❌ No	⚠️ Partial
CI/CD Friendly	✅ Yes	❌ No	⚠️ No
Security Compliant	✅ Yes	❌ No	⚠️ Manual effort
Scaling with Teams	✅ Easy	❌ Difficult	⚠️ Medium

When to Choose SLIs as Code

When compliance, security, and automation are priorities.
When your org practices GitOps, IaC, or DevSecOps.
When you need repeatable and testable monitoring standards.

🔚 9. Conclusion

SLIs as Code is a foundational practice in modern DevSecOps and SRE teams. It enforces measurable, automatable, and secure observability of services while aligning with best practices like version control, CI/CD, and security integration.

By shifting observability left, SLIs as Code bridges the gap between development, operations, and security — enabling resilient, compliant, and performance-optimized software delivery.