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SLAs, SLOs, and SLIs

Turning Reliability Engineering Discipline

Site Reliability Engineering | Service Level Management

Modern digital services live or die by reliability. Users don’t care how complex your backend is or how advanced your architecture looks on paper—they only care whether the service works when they need it.

Table of Contents

1. Why Service-Level Metrics Matter

Every service—internal or external—makes implicit promises to its users:
  • The application will be available when needed
  • Requests will complete within acceptable time
  • Failures will be rare and recoverable
Without measurable signals, these promises remain vague opinions. Service-level metrics convert expectations into numbers, thresholds, and decisions.

What Service-Level Metrics Enable

Business Alignment

Bridge the gap between business promises and engineering capabilities

Incident Response

Reduce emotional firefighting with data-driven decisions

Resource Planning

Justify infrastructure investments with concrete metrics

Customer Trust

Build credibility through transparent, measurable commitments

2. The Three Layers of Service Reliability

To manage the gap between user expectations and system reality, engineering organizations rely on three tightly connected concepts that form a powerful reliability framework:
External Promise

SLA

Service Level Agreement What you legally or commercially promise to customers
Internal Target

SLO

Service Level Objective What you aim to deliver internally within your engineering organization
Actual Measurement

SLI

Service Level Indicator What actually happens in production—the ground truth

Each Layer Answers a Different Question

Metric Question Purpose
SLI What happened? Objective measurement of system behavior
SLO Was it good enough? Internal reliability target for engineering
SLA Are there consequences? Contractual commitment with penalties

3. SLA – Service Level Agreement

Definition

An SLA (Service Level Agreement) is a formal, customer-facing commitment that defines the minimum acceptable level of service—and what happens if that level is not met.

Typical SLA Components

  • Availability Commitments: Uptime guarantees (e.g., 99.5% monthly availability)
  • Incident Response Times: Time to acknowledge and resolve incidents
  • Support Coverage: Support hours, channels, and response SLAs
  • Financial Penalties: Service credits or refunds for SLA breaches
  • Exclusions: Planned maintenance, force majeure, user misuse
Critical Understanding: SLAs are business contracts, not engineering specs. They must be conservative and precise because they carry legal and financial consequences.

Common SLA Pitfall

The most frequent mistake is setting targets that sound impressive but are operationally unrealistic. Unrealistic SLAs often ignore:
  • Third-party dependencies (cloud providers, payment gateways, APIs)
  • Planned maintenance windows and upgrade cycles
  • Network and regional failures beyond your control
  • Cost and operational trade-offs of extreme reliability
Best Practice: A strong SLA reflects what the system can consistently sustain over time, not what marketing wants to advertise.

SLA Calculation Example

Downtime Calculation for 99.5% Monthly SLA

Total time in month = 30 days × 24 hours × 60 minutes = 43,200 minutes SLA availability = 99.5% Allowed downtime = (100% – 99.5%) × 43,200 minutes = 0.5% × 43,200 = 216 minutes = 3.6 hours Result: If downtime exceeds 216 minutes in a month, the SLA is breached.

SLA Availability Tiers

SLA Level Uptime Downtime/Month Downtime/Year Use Case
Basic 99.0% 7.2 hours 3.65 days Internal tools, dev environments
Standard 99.5% 3.6 hours 1.83 days Business applications
Production 99.9% 43.2 minutes 8.76 hours Customer-facing services
Mission-Critical 99.95% 21.6 minutes 4.38 hours Financial services, healthcare
Extreme 99.99% 4.32 minutes 52.6 minutes Payment systems, critical infrastructure

4. SLO – Service Level Objective

Definition

An SLO (Service Level Objective) is an internal reliability goal set by engineering teams. It defines how well the service should perform under normal conditions.

If the SLA is the promise, the SLO is the safety buffer.

Why SLOs Exist

Engineering teams rarely aim to operate at the SLA boundary. Instead, they set stricter internal goals so that:
  • Prevent SLA Breaches: Minor incidents don’t immediately cause contractual violations
  • Early Detection: Teams have time to detect and fix issues before customers are impacted
  • Proactive Operations: Reliability decisions are proactive, not reactive
  • Error Budget Management: Enables calculated risk-taking in feature development

SLO Safety Margin Example

Customer-Facing SLA: 99.5% monthly availability Internal Engineering SLO: 99.9% monthly availability Safety Margin = 0.4% This 0.4% difference is your error budget and incident response buffer.

SLO Error Budget Calculation

Error Budget for 99.9% SLO

Total minutes per month = 43,200 minutes SLO = 99.9% availability Allowed downtime = (100% – 99.9%) × 43,200 = 0.1% × 43,200 = 43.2 minutes per month Error Budget = 43.2 minutes If downtime crosses 43.2 minutes, engineers must act—before customers are impacted.

Using Error Budgets

Feature Velocity

When error budget is healthy, push features aggressively

Stability Focus

When error budget is depleted, freeze features and focus on reliability

Risk Assessment

Use error budget to quantify risk of deployments

Team Alignment

Objective metric for balancing innovation vs stability
Error Budget Policy: When error budget is exhausted, stop all non-critical deployments until reliability is restored. This prevents cascading failures and SLA breaches.

5. SLI – Service Level Indicator

Definition

An SLI (Service Level Indicator) is the actual measured value of system behavior. It answers one simple question: What did the system really do?

Common SLIs in Production Systems

SLI Type Measurement Example User Experience
Availability % of successful requests 99.92% Can users access the service?
Latency P95/P99 response time P95 < 200ms How fast do requests complete?
Error Rate % of failed requests 0.08% How often do requests fail?
Throughput Requests per second 5,000 req/s Can the system handle load?
Correctness % of correct responses 99.99% Are responses accurate?

SLI Calculation: Availability Example

Availability SLI Formula

SLI (Availability) = (Successful Requests / Total Requests) × 100 Real-World Example: Total requests in the last hour: 10,000,000 Failed requests (5xx errors): 8,000 Successful requests: 9,992,000 Availability SLI = (9,992,000 / 10,000,000) × 100 = 99.92% Interpretation: ✓ Meets SLO of 99.9% ✓ Safe from SLA threshold of 99.5% ✓ Error budget still available

6. How SLAs, SLOs, and SLIs Work Together

These three metrics form a layered defense system for service reliability:

The Reliability Stack

1
SLI Measures Reality – Monitoring systems continuously measure actual service performance
2
SLO Evaluates Performance – Compare SLI against internal reliability targets
3
SLA Determines Business Impact – Assess whether customer commitments are at risk

11. Best Practices and Key Takeaways

Strategic Guidelines

  • Start Simple: Begin with 3-5 key SLIs, not 50. Add more only when needed.
  • User-Centric SLIs: Measure what users experience, not internal system metrics.
  • Realistic SLAs: Set commitments you can consistently deliver, not aspirational targets.
  • Safety Margins: Always set SLOs stricter than SLAs to provide operational buffer.
  • Error Budget Discipline: When error budget is depleted, freeze features and fix reliability.
You’ve implemented service-level metrics correctly when:
  • ✓ Customers know exactly what to expect from your service
  • ✓ Engineers know what to optimize and when to stop feature work
  • ✓ Businesses know where to invest in infrastructure
  • ✓ Incidents trigger data-driven responses, not emotional reactions
SLAs, SLOs, and SLIs