Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ancoleman/ai-design-components --skill load-balancing-patternsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ancoleman/ai-design-components/load-balancing-patterns)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/load-balancing-patterns"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/load-balancing-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/load-balancing-patterns"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/load-balancing-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.03429 |
| Opus 5.5 | $0.00020 | $0.01372 |
| Sonnet 5.5 | $0.00010 | $0.00686 |
| Haiku 4.5 | $0.00005 | $0.00343 |
Grade A, and why
load-balancing-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 442 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load Balancing Patterns
Distribute traffic across infrastructure using the appropriate load balancing approach, from simple round-robin to global multi-region failover.
When to Use This Skill
Use load-balancing-patterns when:
- Distributing traffic across multiple application servers
- Implementing high availability and failover
- Routing traffic based on URLs, headers, or geographic location
- Managing session persistence across stateless backends
- Deploying applications to Kubernetes clusters
- Configuring global traffic management across regions
- Implementing zero-downtime deployments (blue-green, canary)
- Selecting between cloud-managed and self-managed load balancers
Core Load Balancing Concepts
Layer 4 vs Layer 7
Layer 4 (L4) - Transport Layer:
- Routes based on IP address and port (TCP/UDP packets)
- No application data inspection, lower latency, higher throughput
- Protocol agnostic, preserves client IP addresses
- Use for: Database connections, video streaming, gaming, financial transactions, non-HTTP protocols
Layer 7 (L7) - Application Layer:
- Routes based on HTTP URLs, headers, cookies, request body
- Full application data visibility, SSL/TLS termination, caching, WAF integration
- Content-based routing capabilities
- Use for: Web applications, REST APIs, microservices, GraphQL endpoints, complex routing logic
For detailed comparison including performance benchmarks and hybrid approaches, see references/l4-vs-l7-comparison.md.
Load Balancing Algorithms
| Algorithm | Distribution Method | Use Case |
|---|---|---|
| Round Robin | Sequential | Stateless, similar servers |
| Weighted Round Robin | Capacity-based | Different server specs |
| Least Connections | Fewest active connections | Long-lived connections |
| Least Response Time | Fastest server | Performance-sensitive |
| IP Hash | Client IP-based | Session persistence |
| Resource-Based | CPU/memory metrics | Varying workloads |
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/aws/alb-terraform.tf 5.0 KB
- examples/aws/nlb-terraform.tf 12 KB
- examples/envoy/basic-lb.yaml 4.8 KB
- examples/haproxy/http-lb.cfg 8.2 KB
- examples/kubernetes/gateway-api.yaml 12 KB
- examples/kubernetes/nginx-ingress.yaml 6.0 KB
- examples/kubernetes/traefik-ingress.yaml 9.0 KB
- examples/nginx/http-load-balancing.conf 5.5 KB
- examples/traefik/kubernetes-ingress.yaml 11 KB
- outputs.yaml 6.9 KB
- references/cloud-load-balancers.md 5.2 KB
- references/envoy-patterns.md 4.9 KB
- references/global-load-balancing.md 4.6 KB
- references/haproxy-patterns.md 5.3 KB
- references/health-check-strategies.md 14 KB
- references/kubernetes-ingress.md 3.3 KB
- references/l4-vs-l7-comparison.md 11 KB
- references/nginx-patterns.md 5.6 KB
- references/session-persistence.md 4.6 KB
- references/traefik-patterns.md 3.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 442 lines · 51 tokens per session scan A ce2cb71d4c97
load-balancing-patterns is a skill published in the GitHub repository ancoleman/ai-design-components (524 stars, last pushed 10mo ago), licensed MIT. It adds 51 tokens to every session and 3,429 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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