An SRE That Fixes,
Not Just Alerts
They watch every deployment, pipeline, and cluster, then triage, find root cause, fix what is safe, and hand on-call a written RCA - not a 3 a.m. pager.
30+
Happy Clients
$2M +
Cloud Costs Saved
10+
SOC 2 & HIPAA Ready
10+
Countries Served
Why Production Breaks and Stays Broken
Observability tells you something is wrong. It still takes a tired human to work out what, why, and how to fix it.
Alert Fatigue
Hundreds of alerts a week, most of them noise. The one that matters gets acknowledged and forgotten.
Slow Root Cause Analysis
Hours of log-diving across services to find the change that broke production - then a postmortem nobody writes.
Bad Deploys Reach Users
Canaries run, dashboards drift, and the rollback decision waits for a human to notice.
Broken Pipelines
Flaky tests, expired credentials and failed builds that block every team until someone digs in.
Manual Scaling
Capacity set by guesswork: over-provisioned all week, under-provisioned during the launch.
Model Drift & Silent Failures
Models degrade as data shifts, pipelines break upstream, and nobody is alerted until a customer is.
Alerts Don't Fix Outages. Engineers Do. Now Agents Do Too.
Monitoring stops at the alert. Our agents do the triage, the diagnosis and the safe fixes first.
Traditional SRE
Dashboards, alerts and an on-call rota
Skybyte AI SRE
Autonomous agents, human-approved
First responder
Traditional SRE
Whoever is on call - woken up and context-free.
Skybyte AI SRE
An agent that already has topology, deploys and logs in context.
Triage
Traditional SRE
Ack the alert, guess the service, start grepping logs.
Skybyte AI SRE
Correlate alerts, metrics and the last change set in seconds.
Root cause
Traditional SRE
Hours across Slack threads and Grafana tabs.
Skybyte AI SRE
Traced to the commit, config or data shift - with evidence.
Remediation
Traditional SRE
Manual rollback or hotfix, when someone is confident.
Skybyte AI SRE
Known-safe fixes run automatically; novel ones wait for you.
Deploys & pipelines
Traditional SRE
A red pipeline blocks the team until an engineer digs in.
Skybyte AI SRE
Agents watch every canary and CI run, then open the PR.
Learning
Traditional SRE
Postmortem template, half filled, never revisited.
Skybyte AI SRE
RCA drafted within the hour; runbooks and thresholds updated.
Toil removed · Share of on-call work handled before a human is paged
Monitoring stops at the alert. Agents carry the incident to resolution.
How much of each on-call task is finished before a human is paged.
Alert triage
ack only
correlated + ranked
Root cause analysis
manual
change-linked
Rollbacks & restarts
scripted
auto, SLO-verified
Pipeline failures
retry button
fixed or PR opened
Capacity & scaling
static HPA
forecast-driven
Postmortems & runbooks
template
drafted in the hour
Alerts + on-call human
Skybyte agents
Measurable Impact on Reliability
The first responder is an agent that already knows the system.
Minutes to Root Cause, Not Hours
On-call gets a diagnosed incident, not a raw alert.
Deployment Frequency
From monthly releases to many a day.
Uptime Held While Shipping Faster
Canary watching and instant rollbacks protect the error budget.
One Reliable Production
Each agent owns a slice of reliability and reports to the same approval queue. Anything risky waits for a human.
Incident & RCA Agent
First responder on every alert: correlates signals, finds the change that caused it, and writes the RCA.
Change-linked root cause
RCA drafted in minutes
Deployment Health Agent
Watches every canary and rollout against SLOs, and rolls back regressions automatically.
SLO-gated promotion
Automatic rollback
CI/CD Pipeline Agent
Keeps pipelines green: fixes flaky tests, expired credentials and broken runners.
Flaky-test quarantine
Fix PRs for real breaks
Capacity & Scaling Agent
Forecasts demand and scales clusters, node pools and replicas ahead of it - and back down after.
Forecast-driven scaling
Launch-day pre-warming
How Our SRE Agents Work
The same loop for every alert, every deploy and every pipeline run - at 3 p.m. and at 3 a.m.
Detect
Agents ingest alerts, metrics, logs, traces, deploy events and pipeline runs across every cluster and cloud.
Diagnose
Correlate the signal with what changed - commits, configs, data - and rank the likely root cause.
Human gate
Remediate
Known-safe fixes run inside guardrails. Novel or high-blast-radius actions wait for your approval.
Verify & Learn
Confirm the fix against the SLO, then draft the RCA and update runbooks, thresholds and regression tests.
Tools We Use
Leveraging the latest tools and technologies to build efficient, scalable, and future-ready solutions.
Datadog
Grafana
Prometheus
OpenTelemetry tracing
Kubernetes
Argo CD
Flux
AWS CodePipeline
Jenkins
GitHub Actions
MLflow
Evidently AI
Amazon Bedrock / SageMaker
Vertex AI
Azure AI Foundry / Azure ML
Claude (Anthropic)
Model Context Protocol (MCP)
LangGraphWork that ships and scales
How we've helped teams put AI and cloud to work in production.
AWS
EKS / KUBERNETES
MICROSERVICES
FINOPS
DEVSECOPS
86+ Services Migrated to AWS EKS in 8 Weeks - Zero Downtime, Zero Incidents
GCP
SOC 2 TYPE 1
GKE
TERRAFORM
DEVSECOPS
SOC 2 Type 1 in 30 Days - Multi-Region AI Product on GCP, 50+ Services Hardened
AZURE
FINOPS
AKS
COSMOS DB
COST OPTIMIZATION
55% Azure Cost Reduction in 11 Weeks - $137K/Month Saved on a $250K/Month SaaS Spend
Ready to build AI-first?
Join the teams shipping production AI with Skybyte - from first prototype to reliable, governed scale.