AEGIS
The Operational Decision & Governance Layer
for Cloud Platforms
Platform Reliability Engineering Control Plane
From Observability to Operational Decisions
Reduce incidents
Govern every change
Improve reliability automatically
Brahmora Technologies
The Reality Every Platform Team Faces
Modern cloud operations are fragmented
Your team likely uses:
📊
Datadog / Grafana
Monitoring
🚨
PagerDuty / OpsGenie
Incidents
🎫
Jira / ServiceNow
Tickets
🚀
CI/CD Pipelines
Deployments
☁️
AWS / Azure / GCP
Infrastructure
But when something goes wrong, nobody knows:
| Question | Answer today |
|---|---|
| What caused it? | Check 5 tools |
| What to do? | Depends who's on-call |
| Whether to release? | "I think it's fine" |
| Who should approve? | Whoever's in Slack |
| What risk exists? | Nobody knows |
Tools provide visibility, not decisions.
The Hidden Cost of Tool Sprawl
The problem isn't visibility. The problem is decisions.
🔔
500+ alerts
Nobody can prioritise
💥
Failed releases
Unknown dependencies
💬
Manual Slack approvals
No audit trail
🚫
No change governance
Anyone can deploy anything
🧠
No operational memory
Same incidents repeat
⏱️
Hours to investigate
Manual correlation
Result: Operational risk increases while teams believe reliability is improving.
This is the gap Platform Reliability Engineering must solve.
What Teams Actually Need
A missing layer exists in the cloud stack
| Layer | Tool | Status |
|---|---|---|
| Infrastructure | AWS / Azure / GCP | Exists |
| Observability | Datadog / Grafana | Exists |
| Automation | CI/CD pipelines | Exists |
| Ticketing | Jira / ServiceNow | Exists |
| Decision Layer | ??? | Missing |
A system that answers:
- Should we release?
- What is the risk?
- What services are affected?
- Should this be approved?
- What is the blast radius?
This is where AEGIS fits.
The Platform Reliability Engineering control plane.
Business Impact
AEGIS improves key reliability outcomes
30-60%
MTTR Reduction
40%
Fewer Failed Releases
50%
Less Investigation Time
Significant
Risk Exposure Reduction
Reliability Maturity
L1 → L3+ progression
Change Safety
Every deploy risk-assessed
Engineering Productivity
Less firefighting
Governance Compliance
Evidence-backed
Outcome: Measurable Platform Reliability Engineering improvement.
Introducing AEGIS
The Platform Reliability Engineering decision layer
AEGIS connects your tools and provides:
- Risk-aware operational decisions
- Governance workflows
- Reliability intelligence
- Release safety controls
- Operational memory
Instead of dashboards:
AEGIS tells you what to do.
Instead of reactive operations:
AEGIS enables proactive PRE.
The PRE Lifecycle
See
→
Understand
→
Decide
→
Govern
→
Improve
What AEGIS Actually Does
4 core PRE capabilities
👁️
Foundation
Unified Visibility
See everything in one place across all accounts and clouds
🔍
Operations
Incident Intelligence
Understand what happened, why, and how to fix it
🛡️
Control
Governance Workflows
Decide and govern every change with policy and evidence
🧠
Intelligence
Risk Prediction
Predict risk, automate decisions, improve continuously
The PRE Lifecycle
See → Understand → Decide → Govern → Improve
Use Case: Safe Deployments
Without AEGIS:
Deploy → Hope → Incident → Investigation → Firefighting
With AEGIS:
Deploy requestReceived
↓
Risk analysis6 factors
↓
Policy validation14 gates
↓
Approval workflowSLA enforced
↓
Safe executionEvidence
AEGIS evaluates:
- Dependencies
- Service health
- Past incidents
- Blast radius
- SLO impact
Then provides:
GO
Low risk
HOLD
Review
NO-GO
Fix first
PRE applied to change management.
Use Case: Incident Intelligence
Instead of engineers manually checking:
✗ Logs
✗ Metrics
✗ Traces
✗ Deployments
✗ Alerts
AEGIS automatically correlates:
✓ Changes → with failures
✓ Services → with dependencies
✓ Signals → with root cause
✓ Timeline → with blast radius
Probable root cause in minutes
Reduced MTTR through PRE intelligence
Use Case: Governance Automation
Governed platform operations without slowing engineering
Most organisations lack:
- Approval enforcement
- Audit trail
- Change governance
- Risk policies
AEGIS provides:
| Policy verdict engine | Evaluate every change against rules |
| Approval workflows | Route to right authority with SLA |
| Execution controls | Time-bounded, signed, scoped |
| Evidence bundles | Tamper-evident proof of every decision |
| Audit history | Hash-chained, immutable, exportable |
Core PRE principle:
Reliability with governance.
How AEGIS Works
Platform Reliability Engineering architecture
Integrations Layer
AWS, Azure, GCP, K8s, CI/CD, Observability
↓
Data Correlation Engine
Signals, changes, incidents, dependencies, cost
↓
Decision Engine
Risk scoring, policy evaluation, blast radius
↓
Governance Workflows
Approval SLA, escalation, execution tokens
↓
Execution Controls
Safe operations, evidence, audit trail
AEGIS integrates with:
Kubernetes
EKS, AKS, GKE
Cloud
AWS, Azure, GCP
Observability
OTLP, Prometheus
CI/CD
GitHub, Jenkins, Argo
Incidents
PagerDuty, OpsGenie
Ticketing
Jira, ServiceNow
No rip-and-replace required
AEGIS becomes your PRE control plane
Differentiation
Why AEGIS vs other tools
| Category | What they do | What AEGIS does differently |
|---|---|---|
| Observability tools | Show problems | Helps decide actions |
| Automation tools | Execute actions | Governs execution |
| AIOps platforms | Predict issues | Controls operational decisions |
| ITSM tools | Track tickets | Evidence-backed governance |
| Security tools | Detect vulnerabilities | Integrates security into decisions |
Category
Platform Reliability Engineering Control Plane
AEGIS creates a new layer: Operational Decision Infrastructure
Who AEGIS Is For
Ideal teams:
🏗️
Platform Engineering
⚙️
DevOps
📊
Site Reliability Engineering
☁️
Cloud Operations
Companies with:
50+
Services
Multi
Cloud environments
K8s
Kubernetes platforms
High
Change velocity
Sweet spot: Mid-size to enterprise.
Especially organisations moving toward PRE maturity.
ROI & Business Value
Measurable Platform Reliability Engineering ROI
Cost Savings:
| Reduced investigation time | 30-50% hours saved |
| Fewer failed releases | Reduced rollback costs |
| Tool optimisation | Less overlapping spend |
| Reduced downtime | Lower SLA risk |
Example (50-100 engineers):
10 hrs/week saved per team
~500 hrs/year saved
£50K-£100K
productivity gain
ROI Summary:
Engineering productivity20-40% gain
Incident reduction25-50%
Change failure reduction30-50%
Operational efficiencySignificant
Engineering shift:
From firefighting → to reliability engineering
Deployment Model
Flexible deployment options
🏢
Customer Hosted
Secure environments, your infrastructure
Available now
☁️
SaaS
Fully managed
Future roadmap
🔄
Hybrid
Control plane hosted, data on-premise
Available
Integration timeline:
| Foundation setup | 1-2 weeks |
| Initial value visible | Within first month |
| PRE maturity improvement | Begins immediately |
No disruption to existing tooling.
AEGIS integrates into your platform rather than replacing it.
Let's Improve Your Platform Reliability
Brahmora Technologies
"Move fast. Break nothing. Prove it."