Question 1

What is the difference between SLA, SLO, and SLI?

Accepted Answer

SLI (Service Level Indicator) is a quantitative measurement of service health (e.g., 99.5% of requests succeed). SLO (Service Level Objective) is your internal target. SLA (Service Level Agreement) is a contractual commitment to customers with penalties for violations. SLOs should be stricter than SLAs to provide a buffer.

Question 2

What is an error budget and how do I use it?

Accepted Answer

Error budget is the acceptable amount of downtime within your SLO. For 99.9% monthly uptime, your error budget is 43m 50s. If you burn through it early, slow down feature releases to focus on reliability. If you have budget remaining, you can take more risks with deployments.

Question 3

How do I calculate burn rate?

Accepted Answer

Burn rate measures how quickly you're consuming error budget. Burn rate = (actual error rate) / (maximum allowed error rate). For example: 99.9% SLO allows 0.1% errors. If you're seeing 0.2% errors, burn rate = 2× (burning budget twice as fast as acceptable).

Question 4

What availability target should I choose?

Accepted Answer

99% (3.65 days/year downtime): Internal tools. 99.9% (8.77 hours/year): Most business services. 99.95% (4.38 hours/year): Important customer services. 99.99% (52.6 minutes/year): Mission-critical systems. Higher targets increase costs exponentially.

Question 5

How do I calculate the cost of downtime?

Accepted Answer

Cost = (Revenue per hour × Downtime hours) + (Recovery costs) + (Reputation damage). For e-commerce: Revenue lost during outage + abandoned carts + customer churn. Use this to justify reliability investments (monitoring, redundancy, automation).

Question 6

How do I improve my SLA without over-engineering?

Accepted Answer

Start with the lowest acceptable SLA for your business. Measure current performance over 3-6 months. Identify largest contributors to downtime. Fix highest-impact issues first. Invest in monitoring, gradual rollouts, and redundancy for single points of failure.

Time Period	Allowed Downtime
Hour	3.60 seconds
Day	1.44 minutes
Week	10.08 minutes
Month	43.20 minutes
Quarter	2 hours 9 minutes
Year	8 hours 45 minutes

Availability	Annual Downtime	Monthly Downtime	Common Use Case
90% (One nine)	36 days 12 hours	3 days 1 hour	Non-critical internal tools
95% (One nine five)	18 days 6 hours	1 day 12 hours	Development environments
99% (Two nines)	3 days 15 hours	7 hours 18 minutes	Internal business apps
99.5% (Two nines five)	1 day 19 hours	3 hours 39 minutes	Standard web services
99.9% (Three nines)	8 hours 46 minutes	43.83 minutes	Production web apps, APIs
99.95% (Three nines five)	4 hours 22 minutes	21.92 minutes	High-availability services
99.99% (Four nines)	52.60 minutes	4.38 minutes	Critical business apps, payment systems
99.995% (Four nines five)	26.30 minutes	2.19 minutes	Financial trading systems
99.999% (Five nines)	5.26 minutes	26.30 seconds	Telecom, emergency services
99.9999% (Six nines)	31.56 seconds	2.63 seconds	Ultra-critical infrastructure

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