Reliability & Availability
SRE, observability and SLOs that turn availability into a measurable economic advantage.
$9,000
per minute
Average downtime cost
99.99%
availability
Elite performers target
<1h
MTTR
Recovery time
Why this matters
What executives need to know
Downtime has a line in the P&L
According to Gartner, the average cost of downtime is $9,000/min. In e-commerce during peak demand, it can exceed $500,000/min. The cost is never just technical.
Availability is not SLA. It is revenue protection.
88% of consumers do not return after a bad experience. Each incident erodes trust, opens space for competitors, and has a calculable cost.
SLOs give technology a business language
Service Level Objectives translate technical metrics into business terms, creating accountability and a shared basis for prioritization between engineering and leadership.
Prevention costs less than response
Mature reliability organizations invest 80% in prevention and 20% in response. Most operate in reverse. The P&L reflects the difference.
Proven Results
Measurable business impact
Real metrics from organizations that evolved this capability.
99.95%
Availability
98.5%→+1.45pp
<15min
MTTR
4+ hours→-94%
-70%
P1 Incidents
12/month→3/month
$2.4M
Protected Revenue
Avoided downtime→/year
The Challenge
Your operation depends on systems you cannot afford to lose
Unavailability is not a technical problem. It is direct revenue loss, reputation damage, and advantage handed to competitors. Every minute counts.
1
Rising downtime cost
Every minute offline reduces revenue, lowers NPS, and erodes customer trust that took months to build.
2
Recurring incidents
Repeated failures signal accumulated technical debt and processes that treat symptoms, not causes.
3
Slow recovery
High MTTR extends impact time per incident. Recovery speed is as important as prevention.
4
No predictability
Without clear SLOs, there is no shared baseline for anticipating or preventing problems.
Our Approach
What we implement
01
SLO-based Alerting
Alerts triggered by error budget consumption, not arbitrary thresholds. Reduces alert fatigue and directs effort where impact is real.
02
Unified Observability
Metrics, logs, and traces correlated in a single view for fast diagnosis. Less war room, more signal.
03
Incident Management
Structured response with runbooks and postmortems that produce learning, not blame.
04
Chaos Engineering
Proactive resilience testing that finds failures before customers do. Risk controlled, not avoided.
05
Sustainable On-Call
Rotation designed to reduce toil. Engineers who rest respond better. Burnout is an operational risk.
06
Capacity Planning
Capacity projection based on growth models, not guesswork. Avoids both over-provisioning and degradation under load.
Frequently Asked Questions
Common questions about this topic
What is the difference between SLA, SLO, and SLI?
SLI is the measured metric, such as latency. SLO is the internal objective, such as 99.9% of requests under 200ms. SLA is the contractual commitment. SLOs must be stricter than SLAs to preserve the margin for error.
Where to start with SRE?
Define SLOs for the most critical services. Then implement observability in three layers: metrics, logs, and traces. Incident management comes before chaos engineering.
What is the typical investment in observability?
Companies typically invest 3 to 5% of their infrastructure budget on observability. The return is direct: every minute of avoided downtime pays for itself many times over.
What happens when the error budget runs out?
New features stop. The team focuses on stability. This is not a punishment; it is a governance mechanism that creates natural incentive to maintain quality over time.
Ready to evolve Reliability & Availability?
Start with a maturity diagnostic. In 47 days, you'll have clarity about where you are, where to go, and how long it will take.