SLIs, SLOs, and Error Budgets: The Foundation of SRE

When I first transitioned into Site Reliability Engineering, the concepts of SLIs, SLOs, and Error Budgets seemed abstract. But after implementing them across multiple systems, I've learned they're not just metrics. They're a framework for making engineering decisions based on user impact rather than gut feelings.

Why SLIs and SLOs Matter

Traditional monitoring often focuses on system metrics: CPU usage, memory, disk space. While these are important, they don't directly translate to user experience. SRE flips this approach by starting with what users actually care about.

Instead of asking "Is our server healthy?" we ask "Are our users having a good experience?"

Choosing the Right SLIs

Service Level Indicators are the metrics that matter most to your users. After working with various systems, I've found these patterns work well:

Request/Response Services

• Availability: Percentage of requests that return successfully
• Latency: Time to process requests (typically 95th or 99th percentile)
• Quality: Correctness of responses (harder to measure but critical)

Data Processing Systems

• Freshness: How current the processed data is
• Coverage: Percentage of data successfully processed
• Correctness: Accuracy of processing results

Storage Systems

• Durability: Data isn't lost
• Availability: Data can be retrieved when needed
• Performance: Speed of read/write operations

The key is picking 2-4 SLIs that best represent user experience. More isn't better. It dilutes focus.

Setting Meaningful SLOs

Service Level Objectives are targets for your SLIs. Here's what I've learned about setting them:

Start with Current Performance

Look at your historical data. If you're currently achieving 99.5% availability, don't set an SLO of 99.99%. Start with something achievable like 99.0% and improve from there.

Consider User Expectations

Different services have different tolerance levels:

• A search feature might tolerate occasional failures
• A payment system needs near-perfect reliability
• Real-time alerts need low latency
• Batch reports can handle higher latency

Make Them Meaningful

An SLO should represent the minimum level of service that keeps users happy. If violating it doesn't matter to users or business, it's not a good SLO.

Error Budgets: Balancing Reliability and Innovation

Error budgets are the secret sauce of SRE. They turn reliability from a binary "always up" goal into a resource that can be spent wisely.

How Error Budgets Work

If your SLO is 99.9% availability, your error budget is 0.1%. This translates to:

• 43.8 minutes of downtime per month
• 8.77 hours per year

This budget can be "spent" on:

• Planned maintenance
• Failed deployments
• Infrastructure changes
• New feature releases

Decision Making with Error Budgets

• Budget remaining: Focus on feature velocity, take calculated risks
• Budget exhausted: Focus on reliability, slow down releases, investigate root causes
• Budget consistently unused: Consider loosening SLOs or taking more risks

Real-World Implementation

Here's how I implemented this at a previous company for a critical API service:

SLIs We Chose

Availability: (successful_requests) / (total_requests) > 99.5%
Latency: 95th percentile response time < 200ms
Error Rate: (5xx errors) / (total_requests) < 0.1%

Tools and Monitoring

• Prometheus for metrics collection
• Grafana for visualization and alerting
• Custom dashboards showing error budget burn rate
• Weekly reports to engineering and product teams

The Results

Within six months:

• Reduced mean time to detection by 40%
• Improved cross-team communication about reliability
• Made data-driven decisions about release timing
• Decreased customer-impacting incidents by 60%

Common Pitfalls to Avoid

Too Many SLIs

I've seen teams try to track 10+ SLIs. It's overwhelming and nothing gets the focus it needs. Start small.

Perfect SLOs

Setting 100% availability as an SLO is counterproductive. It creates unrealistic expectations and discourages innovation.

Ignoring Error Budget

If you define error budgets but don't use them for decision-making, they're just vanity metrics.

Focusing on Internal Metrics

Your database CPU might be fine, but if users can't log in, your SLIs should reflect that reality.

Getting Started

1. Pick one critical service to start with
2. Choose 2-3 SLIs based on user experience
3. Set conservative SLOs based on current performance
4. Implement basic monitoring for your SLIs
5. Track error budgets and make them visible to your team
6. Iterate and improve based on what you learn

The beauty of this approach is that it grounds reliability discussions in user impact and business value. Instead of arguing about whether 99.9% or 99.95% availability is "better," you can discuss what level of service your users actually need and what you're willing to invest to achieve it.

SLIs, SLOs, and Error Budgets aren't just SRE tools. They're a framework for building services that reliably deliver value to users while maintaining engineering velocity. Once you start thinking this way, you'll never go back to flying blind on reliability.