reliability
Stop instrumenting everything uniformly. Start prioritizing design, testing, and observability by the risk they actually mitigate — using FMEA-based analysis as a design activity, not a post-incident exercise.
platform
How do you estimate how much bandwidth an entire country needs? By combining users, services, and access technologies into a three-dimensional model — and feeding it with publicly available data instead of expensive traffic captures.
Golden signals dashboard: Latency 42ms p50, Traffic 1.2k requests per second, Error rate 0.03%, Saturation CPU 72%, Memory 58%, Disk 41%, Network 23%.
The four golden signals are the minimum viable observability set for any production service. Instrument these first; everything else is refinement.
SLIs measure what users experience. SLOs set the target. Error budgets quantify how much unreliability remains before the team must stop shipping and focus on reliability.
Availability gauge showing 99.97% 30-day uptime against SLO target of 99.95%. Error budget 62% remaining, allowed downtime 13 minutes per month, burn rate 0.8x.
Incident metrics line chart over 6 months showing MTTR decreasing from 48 to 8 minutes, MTTD decreasing from 36 to 5 minutes, and MTBF increasing from 12 to 72 hours. Target line at 15 minutes.
Incident metrics track how quickly you detect, respond to, and recover from failures — and how long the system runs between them.
Latency percentiles, throughput, and Apdex reveal how users experience your service. Averages lie — percentile distributions show exactly what fraction of users are waiting too long.
Latency histogram showing percentile distribution: p50 42ms, p75 89ms, p90 127ms, p95 158ms, p99 187ms. All percentiles below the 200ms SLO target.
Infrastructure utilization ring gauges: CPU 72% of 4 cores, Memory 58% of 16 GB, Disk 41% of 500 GB, Network 23% of 1 Gbps. All 4 nodes healthy, zero restarts.
Infrastructure metrics track the health of the compute layer — CPU, memory, disk, and network. Saturated resources cause latency spikes before they cause outages.
DORA metrics measure software delivery performance. High-performing teams deploy frequently with low failure rates — speed and stability are not a trade-off.
Deploy frequency bar chart over 12 weeks showing an upward trend from roughly 15 to 35 deploys per week, averaging 4.2 deploys per day. Change failure rate at 4.2%.
Capacity planning horizontal bar chart: Headroom 34%, Cost per request $0.003, Scaling events 12 per month. System is scaling-ready with adequate headroom.
Capacity planning ensures the system handles projected load growth without degradation — and that you're not over-provisioning. The goal is headroom without waste.