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by Jeff Fernandez

September 11, 2025

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Why We Published “What’s Autoscaling?” and “Who’s it for?”: Making Autoscaling Click for Everyone

If you read our post about rebuilding the homepage, you know our north star is clarity. These two new pages push that even further, so anyone, not just engineers, can understand what Kedify does and explain the value in under a minute.

The two pages

• What’s Autoscaling?: a plain-English explainer with a no-jargon “30-second definition,” how it works, common pitfalls, and when to use each type (horizontal, vertical, event-driven, HTTP). It even contrasts “Plain English” with “Engineer-speak” side-by-side so teams can align on language fast.

• Who’s it for?: a crisp buyer-and-user map (CFO/FinOps, CTO/VPE, CEO/Founder) plus the hands-on owners (Platform & DevOps, SREs, Developers). It shows where autoscaling pays off first across industries and workloads, with one-liners you can reuse in your next email or board deck.

As a business-first CEO, my job is to make complex tech easy to grasp and easy to champion across the org. These pages do that.

1) Define what we do: in plain English

On What’s Autoscaling?, we describe autoscaling the way I explain it to non-engineers: it’s essentially a “smart light-switch for your compute”. Power turns up when the crowd arrives and down when it leaves. That is the whole idea: stay fast, avoid waste.
The page then shows, at a glance:

• How autoscaling works (signals, decision engine, orchestrator, feedback loop).
• When to use which type (HPA, VPA, event-driven or KEDA, cluster autoscaler) and the tradeoffs for each.
• Why traditional CPU/memory triggers lag real demand, and how event- or HTTP-driven scaling responds instantly.

If you have ever struggled to explain autoscaling outside the engineering channel, this is the explainer to forward.

2) Make the value instantly relatable

And Who’s it for? ties real outcomes to real roles:

• CFO / FinOps: predictable spend, faster approvals, and a path to 30–40% less compute waste.
• CTO / VP Eng: keep P95 green during spikes, eliminate cold-start firefights, and show payback inside 1–2 quarters.
• Platform & DevOps / SREs / Devs: fewer incidents, retiring glue code, preview envs on demand.

It also breaks down common environments with single-sentence talk tracks you can reuse:

• Traffic-heavy APIs: our HTTP scaler holds p95 steady even under a thundering herd.
• AI/GPU inference: predictive warm pods avoid minute-long cold starts.
• Queues and streams (Kafka or Pulsar): scale consumers to lag automatically.
• CI or test farms: scale runners to zero until a build kicks off.

3) Equip non-engineers to support the purchase

Great explanations are necessary; business proof is decisive. Both pages link to the ROI Calculator so finance and leadership can estimate savings in seconds, grounded in current cloud spend and workload mix. Teams often see 30–40% reductions in compute waste, plus 5–10 engineer-hours back per week, which are the kind of numbers that speed up approvals.

If you want the product view behind those outcomes, the Product Overview and Capabilities pages show how Kedify’s agent plus control plane deliver real-time autoscaling across HTTP, gRPC, GPU, and 70+ event sources.

4) Make referrals effortless (steal this)

If you are a business leader who believes your engineering team should look at Kedify, here are copy-ready snippets. Paste into Slack or email:

Next step options:

• Skim: What’s Autoscaling? for the 30-second definition and tradeoffs.
• Match: Who’s it for? to your teams and workloads.
• Quantify: Run the ROI Calculator to estimate savings.
• See it live: Book a 15-minute fit check.

Why this matters for Kedify

Our mission is to align performance with cost, not just “scale more.” That is why our site, docs, and tools aim to be as useful to CFOs as they are to SREs. These two pages continue the work we started with the homepage refresh: clear positioning, real numbers, and a shared language across business and engineering.

If you are running Kubernetes, seeing spiky workloads, or exploring GPU inference at scale, these pages are the fastest way to understand what Kedify delivers, and to help your teammates say “yes” with confidence.