Awazos / SRE · reliability engineering
AwazosCLOUD-NATIVE INFRASTRUCTURE
online service · 04/04 module · sre
Awazos
CLOUD-NATIVE INFRASTRUCTURE
service 04 / 04 · sre
module · reliability
indicators · sli · slo · eb
on-call · 24/24

The 3am incident ·
downgraded to non-event.

the problem

Your team is on-call but nobody knows what's an SLO violation vs. background noise. The post-mortem ends with "be more careful next time." Reliability is wishful thinking.

our approach

SRE combines software engineering, automation, monitoring, incident management and operational best practice. We help teams define reliability goals, improve observability, and reduce incidents.

the outcome

SLOs your team owns. Incident response that's a script, not improvisation. Production readiness reviews that catch problems before launch. Reliability as a discipline.

01 · capabilities

what we engineer.

scope · production
delivery · embedded SRE
handoff · runbooks + practice

SRE is software engineering applied to operations. We write code that makes production boring.

We provide Site Reliability Engineering services to help organizations build and operate reliable, scalable, production-ready systems. Our SRE approach combines software engineering, automation, monitoring and incident management.

You get a working reliability framework: SLIs that predict customer pain, SLOs that protect them, error budgets that drive prioritization — and an on-call rotation that doesn't burn engineers out.

module · awazos/sre ● live
disciplinereliability
engagement12–24 weeks typical
team size2–3 SREs
deliverablerunbooks + SLOs + rotation
avg uptime99.94%
avg mttr drop−62%
  • /01
    SRE strategy & operating model
    How reliability work fits into your org chart. Who owns what. What gets escalated. The boring documents that prevent chaos.
  • /02
    SLI · SLO · error budget design
    Indicators that predict customer pain, objectives that protect them, budgets that drive priorities. Not generic templates — your services.
  • /03
    Observability architecture
    Metrics, logs, traces, alerts — as one coherent system, not four silos that contradict each other.
  • /04
    Incident response process
    Structured response, fewer war-room hours. Blameless postmortems that result in code changes, not finger-pointing.
  • /05
    On-call readiness & runbooks
    Every alert leads to a runbook. Every runbook is tested. The page at 3am is recoverable, not chaotic.
  • /06
    Reliability testing & failure analysis
    Chaos engineering with a purpose. Game days that find the real failure modes before customers do.
  • /07
    Kubernetes & OpenShift reliability
    Self-healing where it makes sense. Pod disruption budgets, HPA tuning, leader election, graceful shutdown.
  • /08
    Capacity planning & performance
    Predict before you provision. Provision before you panic. Load testing that reflects real traffic patterns.
  • /09
    Automation · incident response
    Codified responses for known failure patterns. The 3am page that fixes itself before you wake up.
  • /10
    Production readiness reviews
    The pre-launch checklist that catches the things that always break new services. Nothing ships without it.
02 · outcomes

reliability in metrics.

source · client SLOs
period · 6 months
verified · yes
avg uptime
99.94%
Production availability across active clients
mttr drop
−62%
Mean time to recovery after SRE adoption
incidents
−74%
High-severity incidents per quarter
on-call pages
−81%
Pages per engineer per week after observability work
03 · process

how we actually work.

phases · 4
typical · 8–16 weeks
style · embedded
01

Measure what matters.

Define SLIs and SLOs with your team. Not 47 SLOs — three to five per service. The ones that predict actual customer pain.

SLISLOerror budgets
02

Build the response framework.

On-call rotation, escalation paths, paging strategy, runbook structure. Tested, documented, owned.

on-callrunbookspaging
03

Engineer for resilience.

Chaos engineering, load testing, capacity planning, automation. Find the failure modes in staging, not prod.

chaosload testingautomation
04

Embed · review · hand off.

Production readiness reviews become standard. Postmortems result in code changes. Your team owns reliability — we just teach the discipline.

PRRpostmortemshandoff
04 · stack

reliability tools we actually use.

policy · open-source first
vendor lock-in · avoided
slo tracking
Error budgets
nobl9slothpyrra
incident response
Paging
pagerdutyincident.ioopsgenie
chaos eng
Failure testing
chaos meshlitmusgremlin
load testing
Performance
k6locustgatling
observability
Three pillars
prometheusgrafanatempoloki
apm
Trace correlation
otelhoneycombdatadog
postmortems
Documentation
linearnotionjeli
k8s reliability
Self-healing
HPAPDBvelerokarpenter
05 · engage

let's build it right.

response · < 24h
kickoff · 2 weeks
first value · 30 days

ready to sleep through the night?

One call. We'll review your current reliability posture, identify the three biggest risks, and tell you what to engineer first.

AWAZOS.EXE · DISCOVERY-FORM · v1.0
► COM1 · 9600 BAUD · 8N1 · ENCRYPTED READY
awazos system v1.0 (build 2026.05.13)
copyright (c) 2010-2026 awazos · all rights reserved
loading discovery module ........... [ ok ]
connecting to ops-team@awazos.io ... [ ok ]
awaiting operator input ............ [ ready ]
 
init --form=discovery --service=sre
 
step 01 / identity
who is filing this request?
step 02 / channel
how do we reach you?
step 03 / org
what is your organization?
step 04 / service
what brings you here today?
step 05 / scale
org size and current stack
step 06 / problem
describe the biggest pain in your own words
step 07 / schedule
preferred call window · europe/athens · select multiple
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► transmission complete

request received · ticket #AW-2026-0847
response within 24h to your inbox

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