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Documentation

Reclaim unused IP space in production subnet

#6890 opened 5m ago by Platform Team · Draft

Tighten firewall rules on internal services

#523 opened 5m ago by Platform Team · Review required

#523 opened 5m ago by Platform Team · Closed

Updating Auto Scaling Group Launch Template in AWS

#112 opened 1d ago by Platform Team · Review required

#112 by Platform Team was merged just now

Reclaim unused IP space in production subnet

#6890 opened 5m ago by Platform Team · Review required

#6890 opened 5m ago by Platform Team · Draft

Tighten firewall rules on internal services

#523 opened 5m ago by Platform Team · Review required

#523opened 5m ago by Platform Team · Closed

Updating Auto Scaling Group Launch Template in AWS

#112 opened 1d ago by Platform Team · Review required

#112 by Platform Team was merged just now

Shrinking a subnet will starve an autoscaling group

Resizing a production subnet from /22 to /25 cuts available IPs from ~1,000 to 123. The api-workers autoscaling group already runs 97 instances here with a max capacity of 200. At peak traffic, new instances won't be able to launch and the service won't scale.

All risks disproven

We investigated 3 potential risks across 32,190 resources and verified each was safe. See the investigation details below.

Tightening a security group will break monitoring in another VPC

Narrowing the allowed IP range on internal-services looks like a routine security improvement — but a monitoring system in a separate VPC relies on a peering connection to health-check services behind this group. After this change, those health checks will be silently dropped, targets will be marked unhealthy, and monitoring will go dark.

Cascading FailureR

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Two

#112 opened 5m ago by Platform Team · Review required

#112 by Platform Team was merged 5m ago

Why is context the problem?

Blast radius. Risk. Dependencies.

Context is the knowledge that usually lives in someone’s head — which services depend on this change, where failures might cascade, and what could break in production.

Context is rarely documented, and almost never visible in a pull request — and it breaks down as teams grow.

Queue Backlog

Will this break prod?

Queue Backlog

DNS Failure

Did anyone test this?

What's the blast radius?

What else uses this?

Cross-account impact?

Is this documented?

Is there a rollback plan?

This looks too simple

Who owns this?

Platform TL

Looks good! Approved.

The solution

Overmind surfaces context automatically.

Built from how your system actually runs, blast radius, dependencies, and risk become visible where merge decisions happen.

github.com/workspace/pull/112

Add memory limits to reduce cloud costs

#3680

Memory limits will cause constant OOMKills during traffic spikes

Reasoning

Adding a 512Mi memory limit to the api-gateway deployment looks like smart cost optimization — pods typically use 300-400Mi. But during traffic spikes, the JVM heap expands to 600Mi for garbage collection. With the new limit, pods hit OOMKilled status during peak hours, causing cascading failures as the load balancer routes to restarting pods.

What it unlocks.

For the person making the change, and the team responsible for approving it.

Anyone can review infrastructure changes

Reviews don’t depend on deep tribal knowledge. Context makes complex changes understandable to anyone on the team.

Senior engineers aren’t the bottleneck

Critical knowledge is shared automatically, so reviews don’t stall waiting for the one person who “knows the system.”

No surprises after merge

Impact is visible before changes ship, not after something breaks in production.

Ship more, with less risk

When impact is clear, teams move faster — without absorbing unknown risk or increasing incidents.

“We used to hold our breath on every infrastructure deploy. Now we actually know what's going to happen before we merge."

Global Security / Whiskerlabs

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