AWS published a tutorial showing how to forward CloudWatch alarms to WhatsApp. It involves a Lambda function, an SNS topic, WhatsApp Business API approval, and several hours of setup. ConvOps does the same thing in 10 minutes — and delivers a diagnosis, not just the raw alarm text.
DIY (AWS tutorial approach)
Setup time: several hours. Ongoing maintenance required.
ConvOps
Setup time: 10 minutes. No maintenance.
DIY approach — raw alarm text
ALARM: prod-api-cpu-high
State: ALARM
Reason: Threshold Crossed: 1 datapoint [94.2] was greater than the threshold [80.0]
Now what?
ConvOps — diagnosis included
⚠️ HIGH — prod-api-cpu-high
CPUUtilization: 94% (threshold 80%)
Root cause
Deploy at 14:32 UTC introduced a tight processing loop in the payment worker. No scaling events triggered. No AWS Health issues.
1 — Force new ECS deployment
2 — Roll back to previous revision
3 — Scale out +1 task
Unlike a simple alarm forwarder, ConvOps runs a full investigation before the message reaches your phone.
CloudWatch Logs
Error and exception lines from the last 45 minutes of the resource's log group.
CloudTrail events
Recent deploys, config changes, and resource modifications in the last 2 hours.
Correlated metrics
Neighbouring metrics on the same resource — CPU + memory + network together, not just the alarming one.
Resource state
ECS task status, RDS connectivity, ALB target health, Lambda concurrency — the actual current state.
AWS Health events
Active service disruptions in your region that could explain the alarm.
Security findings
GuardDuty and Security Hub findings correlated with the alarming resource.
No Lambda. No CloudFormation. No API approval. Free to start.
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