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slo-optimize

Analyzes 28-day SLO timeline trends and generates data-backed optimization recommendations.

1|Updated May 25, 2020
Search Tags:#grafana#sre#trend analysis#error budget#slo#burn rate#gcx
One-click install
npx skills add https://github.com/titaneric/dotfiles --skill slo-optimize-titaneric
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: slo-optimize
Source: https://github.com/titaneric/dotfiles/tree/main/dot_agents/skills/slo-optimize
Command: npx skills add https://github.com/titaneric/dotfiles --skill slo-optimize-titaneric

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? SRE teams often run SLOs with unrealistic objectives, missing alerting, or poorly chosen compliance windows, and lack a systematic way to review whether their SLO configuration matches actual service performance. ## Core Features & Use Cases - Trend Analysis: Fetches 28-day SLO timeline data via gcx, computes mean/min/max/std-dev statistics, and classifies patterns such as sustained decline, periodic dips, or sudden drops. - Advisory Recommendations: Produces numbered recommendations for objective tuning, groupByLabels additions, alerting thresholds, and window adjustments, each backed by current and proposed values. - Budget Exhaustion Projection: Calculates days until error budget exhaustion from the current burn rate and flags urgent cases. - Use Case: An SRE asks whether a 99.9% objective is realistic for a service; the skill pulls the timeline, finds the mean SLI is 0.997, and recommends lowering the objective to 0.997 with supporting numbers. ## Quick Start Ask the assistant to analyze and optimize the SLO with a given UUID, or list available SLOs first if you do not know the UUID.

Frequently Asked Questions about slo-optimize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze SLO performance trends in Grafana?▼

Use gcx slo definitions timeline with a UUID and a 28-day range to fetch SLI history, then compute mean, min, max, and standard deviation. Combine this with gcx slo definitions status -o wide for current burn rate and budget remaining.

How to tune an SLO objective based on historical data?▼

Compare the 28-day mean SLI against the current objective. If the mean is more than 0.5 percentage points below the objective, lower the objective to the observed mean rounded down to three decimals; if it is more than 1 point above, tighten toward the mean.

Does this skill modify SLO definitions directly?▼

No, it is advisory only and never changes SLO definitions. When you confirm a recommendation, it routes to the slo-manage skill, which pulls the definition and applies changes with a dry-run first.

What happens when SLO timeline data returns NODATA?▼

The skill falls back to querying raw recording-rule metrics such as grafana_slo_sli_window directly from the destination Prometheus datasource. If raw metrics also return NODATA, it reports the gap and recommends verifying the recording rules.

When should I use a 28-day window instead of 7 days for an SLO?▼

Switch to 28 days when the SLI shows periodic dips, such as weekend traffic patterns, that repeatedly consume budget under a short window. The longer window smooths variability; stable SLIs with low standard deviation do not require a change.

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