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API Rate Limiting & Throttling
Distributed Quotas, Kubernetes Protection, Tenant Fairness, and Go Middleware
Another Production Field Manual: protect APIs before overload becomes an outage with rate limiting, throttling, and tenant fairness.
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About
About the Book
API rate limiting is often treated as a small middleware feature.
In production, it is much more than that: it is the contract that decides who may consume shared capacity, how fast they may consume it, and what happens when demand exceeds what the system can safely serve.
This is the second book in the Production Field Manuals series. The series is written for systems that must survive real production traffic, incidents, budget pressure, and operational handoff.
This volume is a practical guide for engineers, architects, SREs, and technical leaders who need APIs to survive bursty traffic, noisy tenants, retry storms, slow dependencies, Kubernetes autoscaling delays, and cost pressure.
The book explains the business case for rate limiting, the architecture behind local and distributed quota enforcement, and the trade-offs between token bucket, fixed window, sliding window, and leaky bucket algorithms.
It shows how to choose a fairness key, where to place limiter state, how to protect downstream dependencies before they fail, and why a good limiter must become cheaper under overload.
You will also find a production-ready Go implementation shape, HTTP middleware behaviour, cancellation handling, metrics, Prometheus alert templates, rollout checklists, incident runbooks, team drills, FinOps reasoning, and a hands-on lab backed by companion source code.
The goal is not to make every request succeed. The goal is to keep the system useful when too many requests arrive.
If you build or operate multi-tenant APIs, public platforms, internal services, Kubernetes workloads, or expensive dependency paths, this manual gives you the vocabulary, design rules, and operational templates to turn overload from an incident into a controlled response.
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About the Author
Luca Sepe
I help CTOs and platform teams design, build, and hand over Kubernetes-based platforms that can be understood, operated, and evolved by the teams that own them.
My work sits at the intersection of Go, Kubernetes API machinery, control-plane design, platform engineering, infrastructure automation, and distributed systems.
I am most useful when a team is not only deploying workloads to Kubernetes, but building a product, platform, or control plane on top of it. That is where API shape, controller behaviour, ownership boundaries, and automation design become long-term architecture.
I work through focused architecture discovery, hands-on implementation, design review, documentation, and structured handover.
The objective is to leave behind clearer technical decisions, production-oriented software, explicit ownership boundaries, useful documentation, and a team able to continue without me.
Typical problems I help with:
- Kubernetes APIs, CRDs, and resource lifecycle design
- controllers, reconciliation behaviour, and failure handling
- custom API servers and control-plane components
- Go infrastructure software and automation tooling
- platform architecture that must remain connected to code
- review and simplification of existing platform codebases
- documentation and handover for internal teams.
I also write practical technical material on Kubernetes controllers, client-go, Go services on Kubernetes, SRE workflows, AI platform engineering, and operational context for humans, tools, and AI agents.
Available for selected consulting, fractional, contract, and staff-level engagements.
The best first conversation starts from the engineering problem: what you are building, why it is difficult now, what decisions are hard to reverse, and what the internal team needs to own after the work is done.
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