cloud-design-patterns
Helps your agent design robust and efficient distributed systems. It's useful when creating or reviewing the architecture of complex systems to ensure reliability and performance.
What it does
This resource provides a guide to design patterns for cloud-based distributed systems. It helps in building more reliable, secure, and efficient applications.
When to use it
- ✓When designing the architecture for a new cloud system.
- ✓When reviewing or improving an existing system.
- ✓When trying to solve common challenges in distributed systems.
Example of what to ask your AI
“What design patterns can I use to make my system more resilient to failures?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It lists and categorizes various tested solutions (patterns) for common challenges in distributed systems. You choose the pattern that best fits your problem.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill cloud-design-patternsOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/cloud-design-patterns/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Cloud Design Patterns
Architects design workloads by integrating platform services, functionality, and code to meet both functional and nonfunctional requirements. To design effective workloads, you must understand these requirements and select topologies and methodologies that address the challenges of your workload's constraints. Cloud design patterns provide solutions to many common challenges.
System design heavily relies on established design patterns. You can design infrastructure, code, and distributed systems by using a combination of these patterns. These patterns are crucial for building reliable, highly secure, cost-optimized, operationally efficient, and high-performing applications in the cloud.
The following cloud design patterns are technology-agnostic, which makes them suitable for any distributed system. You can apply these patterns across Azure, other cloud platforms, on-premises setups, and hybrid environments.
How Cloud Design Patterns Enhance the Design Process
Cloud workloads are vulnerable to the fallacies of distributed computing, which are common but incorrect assumptions about how distributed systems operate. Examples of these fallacies include:
- The network is reliable.
- Latency is zero.
- Bandwidth is infinite.
- The network is secure.
- Topology doesn't change.
- There's one administrator.
- Component versioning is simple.
- Observability implementation can be delayed.
These misconceptions can result in flawed workload designs. Design patterns don't eliminate these misconceptions but help raise awareness, provide compensation strategies, and provide mitigations. Each cloud design pattern has trade-offs. Focus on why you should choose a specific pattern instead of how to implement it.
References
| Reference | When to load |
|---|---|
| Reliability & Resilience Patterns | Ambassador, Bulkhead, Circuit Breaker, Compensating Transaction, Retry, Health Endpoint Monitoring, Leader Election, Saga, Sequential Convoy |
| Performance Patterns | Async Request-Reply, Cache-Aside, CQRS, Index Table, Materialized View, Priority Queue, Queue-Based Load Leveling, Rate Limiting, Sharding, Throttling |
| Messaging & Integration Patterns | Choreography, Claim Check, Competing Consumers, Messaging Bridge, Pipes and Filters, Publisher-Subscriber, Scheduler Agent Supervisor |
| Architecture & Design Patterns | Anti-Corruption Layer, Backends for Frontends, Gateway Aggregation/Offloading/Routing, Sidecar, Strangler Fig |
| Deployment & Operational Patterns | Compute Resource Consolidation, Deployment Stamps, External Configuration Store, Geode, Static Content Hosting |
| Security Patterns | Federated Identity, Quarantine, Valet Key |
| Event-Driven Architecture Patterns | Event Sourcing |
| Best Practices & Pattern Selection | Selecting appropriate patterns, Well-Architected Framework alignment, documentation, monitoring |
| Azure Service Mappings | Common Azure services for each pattern category |
Pattern Categories at a Glance
| Category | Patterns | Focus |
|---|---|---|
| Reliability & Resilience | 9 patterns | Fault tolerance, self-healing, graceful degradation |
| Performance | 10 patterns | Caching, scaling, load management, data optimization |
| Messaging & Integration | 7 patterns | Decoupling, event-driven communication, workflow coordination |
| Architecture & Design | 7 patterns | System boundaries, API gateways, migration strategies |
| Deployment & Operational | 5 patterns | Infrastructure management, geo-distribution, configuration |
| Security | 3 patterns | Identity, access control, content validation |
| Event-Driven Architecture | 1 pattern | Event sourcing and audit trails |
External Links
FAQ
What are the 'fallacies of distributed computing'?
These are common incorrect assumptions about how networked systems work, such as 'the network is always reliable' or 'latency is zero'.
Do these patterns only work on Azure?
No, they are technology-agnostic and work on any cloud (Azure, AWS, GCP), on-premises systems, or hybrid environments.
Do I need to know how to implement each pattern?
The main focus is understanding why to choose a specific pattern, rather than diving deep into the detailed technical implementation.
Details
Original description by the author
Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5051
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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