Agentic Interface to the Cloud

SREs spend hours digging through logs, metrics, and cloud consoles trying to find the root cause of incidents. Aurora gives you instant answers.
What caused this production incident at 3 AM?
Why did our API response times suddenly spike?
What's the root cause of this service degradation?
Why are we seeing intermittent timeout errors?
Which infrastructure change broke our deployment?
What triggered this security alert in our cloud environment?
Why is our database experiencing connection pool exhaustion?
How can we prevent this incident from happening again?
Why did our Kubernetes pods crash during the deployment?
What's causing the memory leak in our application?
Why is our cache hit rate dropping suddenly?
What's causing these sporadic 503 errors?
Aurora sits between incident alerts and your postmortems — transforming hours of manual investigation into instant root cause analysis.
Production
issue detected
PagerDuty,
DataDog, Grafana
Automatically investigate incidents
Query logs and metrics
Identify root causes instantly
Postmortem
& prevention
Most SRE teams have great monitoring platforms and solid postmortem processes. But between the alert firing and understanding what happened, there's a critical gap of manual investigation. That's where Aurora lives.
Watch how Aurora investigates infrastructure issues automatically, querying your cloud providers and analyzing logs in real-time.
I'll investigate the app-server-prod-01 VM for you. Let me start by checking its current status and configuration.
gcloud compute instances describe app-server-prod-01 --zone us-central1-aNow let me check the firewall rules that might be affecting this instance:
gcloud compute firewall-rules list --filter="targetTags:web-server OR name~web"Let me also check if there are any Cloud Logging errors for this instance:
gcloud logging read "resource.type=gce_instance AND resource.labels.instance_id=5428493216708587129" --limit 20 --format="table(timestamp,severity,textPayload)"Let me test connectivity to the instance:
timeout 5 curl -v http://34.122.18.110 2>&1 | head -30I've identified three major problems with app-server-prod-01:
Problem: A deny firewall rule is actively blocking all web access to your server.
Details:
Evidence: Connection timeout when testing http://34.122.18.110 - the firewall is dropping packets before they reach the VM.
Impact: Your application is completely unreachable from the internet.
Problem: The startup script contains multiple errors that prevent proper application startup.
Script errors: apt-get install -y nonexistent-package-xyz (Package doesn't exist - install will fail) systemctl start application-service (Service doesn't exist - will fail) echo "Application started" > /root/app.log (May have permission issues) python3 -m http.server 80 (Requires root, conflicts with other services)
Impact: Application fails to start properly on boot. Even if the firewall was open, nothing would be listening.
Problem: VM is too small for production workloads.
Current Specs:
Impact: Performance degradation, potential out-of-memory crashes, disk space constraints for a production frontend server.
Would you like me to fix these issues? I can:
Which would you like me to tackle first, or should I fix all three?
Aurora automatically investigates incidents, queries cloud providers, and provides root cause analysis in seconds.
Ask Aurora about incidents across AWS, Azure, and GCP in natural language. Get instant answers without switching between provider consoles.

Aurora automatically investigates incidents across your infrastructure, giving you instant answers when things go wrong.
Debug pods, check logs, and analyze resource usage across all your clusters with natural language commands.
kubectl describe pod app-deployment-xyz --namespace productionkubectl top pods --namespace productionMemory limit set to 128Mi but application requires minimum 512Mi. OOMKilled events detected in last 3 hours.
Recommendation: Update deployment to use at least 512Mi memory limit.
Securely execute commands on any server through SSH. Aurora manages credentials and runs commands in isolated environments.
ssh user@prod-server-01 'df -h'ssh user@prod-server-01 'sudo rm -rf /var/log/*.old && sudo systemctl restart nginx'Disk usage at 94% on /var partition. Cleared old logs (freed 12GB). Nginx restarted successfully.
Status: Service is now running normally.
Query AWS, Azure, and GCP simultaneously. Aurora correlates data across providers to give you the complete picture.
aws elbv2 describe-target-health --target-group-arn arn:aws:elasticloadbalancing:us-east-1:123456789:targetgroup/prod-api/abc123az network lb show --resource-group production-rg --name prod-api-lb --query 'backendAddressPools[0].backendIPConfigurations[*].id' -o tableaz network nic show-effective-nsg --resource-group production-rg --name prod-vm-1-nicYour AWS Application Load Balancer is healthy, but the Azure backend pool has no healthy instances.
Azure VM Details:
Impact: 50% of traffic routed to Azure is failing, causing intermittent 502 errors for users.
Ask Aurora about any incident in natural language. It automatically queries logs, checks metrics, and correlates events to find root causes across AWS, Azure, and GCP.
We provision secure, sandboxed Kubernetes environments on-demand to execute operations with complete isolation. Network policies block internal cluster access, and all pods run with dropped capabilities.
Commands run in isolated Kubernetes pods with gVisor sandboxing
Every user operates with isolated credentials in ephemeral infrastructure
Strict network policies block internal cluster access from user pods













