ScaleGuide
ScaleGuide — Kubernetes Autoscaling, Explained Visually.
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Complex topics. One platform.

Topics that docs, Google & AI can't explain well.

Some Kubernetes topics are too complex for official docs, too nuanced for a Google search, and too hands-on for AI to explain in words. We give you real-world failure & success stories, interactive playgrounds, and an AI that actually understands the trade-offs.

Explore AutoscalingExplore Deployments
Autoscaling

Watch Hotstar handle 25M cricket viewers with HPA + Cluster Autoscaler

Deployments
v1
v1
v2
v2

See how Netflix does 36-hour canary rollouts with zero user impact

Hot Topic

Kubernetes Autoscaling

Official docs tell you what each autoscaler does. We show you when Hotstar handled 25M cricket viewers, when Netflix evening traffic doubles, and why choosing wrong costs real money.

Horizontal Pod Autoscaler

pod level

Adds or removes pod replicas based on CPU, memory, or custom metrics.

Stateless web appsREST/GraphQL APIsMicroservices

Vertical Pod Autoscaler

pod level

Automatically adjusts CPU and memory requests for containers based on usage patterns.

Databases (PostgreSQL, MySQL)MonolithsStateful singletons

Cluster Autoscaler

node level

Adds or removes nodes in the cluster when pods can't be scheduled or nodes are underutilized.

Infrastructure elasticitySupporting HPA/KEDA scale-upsSeasonal traffic spikes

KEDA

pod level

Event-driven autoscaling based on external sources like queues, streams, and cron schedules. Supports scale-to-zero.

Queue consumers (RabbitMQ, SQS, Kafka)Event-driven workloadsBatch processing
Hot Topic

Deployment Strategies

Everyone knows "blue-green" and "canary" as buzzwords. We show you the $2.3M failure when Shopify skipped business metrics, and how Delta validated pricing models for 3 weeks with zero user risk.

Blue-Green Deployment

medium complexity

Two identical environments with instant traffic switch. Zero-downtime with instant rollback.

Zero-downtime requirementsFinancial services

Canary Deployment

high complexity

Route 1-10% of traffic to the new version, gradually increase if metrics look healthy.

High-traffic production servicesServices requiring gradual validation

Rolling Update

low complexity

Replace old pods with new pods one at a time. The Kubernetes default deployment strategy.

Stateless microservicesCI/CD pipelines

Recreate Deployment

low complexity

Kill all old pods, then start all new pods. Simple but causes brief downtime.

GPU workloadsLegacy monoliths
AB

A/B Testing Deployment

high complexity

Route specific user segments to different versions to measure business impact.

Measuring business metricsUI/UX experiments

Shadow (Dark) Deployment

high complexity

Mirror production traffic to the new version. Responses are discarded. Zero risk to users.

ML model validationSearch algorithm changes

Why ScaleGuide?

Because some topics need more than docs and Stack Overflow.

Real-World War Stories

Every topic includes failure and success scenarios from companies like Netflix, Uber, Target, and Delta Airlines. Not theory -- what actually happened.

Interactive Playgrounds

Watch deployments and scaling happen step by step. Trigger failures, see cascading errors, then replay the success path. Learn by seeing, not reading.

AI That Knows Trade-offs

Describe your workload, industry, and constraints. Our assistant recommends the right approach with specific warnings about what can go wrong.