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WorkOS + MCP: Authorization for AI Agents (Sponsored)
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Wide-open access to every tool on your MCP server is a major security risk. Unchecked access can quickly lead to serious incidents.
Teams need a fast, easy way to lock down access with roles and permissions.
WorkOS AuthKit makes it simple with RBAC — assign roles, enforce permissions, and control exactly who can access critical tools.
Don’t wait for a breach to happen. Secure your server today.
This week’s system design refresher:
System Design Was HARD - Until You Knew the Trade-Offs, Part 2 (Youtube video)
A Cheatsheet on REST API Design Best Practices
Top 30 AWS Services That Are Commonly Used
The Large-Language Model Glossary
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System Design Was HARD - Until You Knew the Trade-Offs, Part 2
A Cheatsheet on REST API Design Best Practices
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Well-designed APIs behave consistently, fair predictably, and grow without friction. Some best practices to keep in mind are as follows:
Resource-oriented paths and proper use of HTTP verbs help APIs align with standard tools.
Use a proper API versioning approach.
Use standard error codes while generating API responses.
APIs should be idempotent. They ensure safe retries by making repeated requests to produce the same result, especially for POST operations.
Idempotency keys allow clients to safely deduplicate operations with side effects.
APIs should support pagination to prevent performance bottlenecks and payload bloat. Some common pagination strategies are offset-based, cursor-based, and keyset-based.
API security is mandatory for well-designed APIs. Use proper authentication and authorization with APIs using API Keys, JWTs, OAuth2, and other mechanisms. HTTPS is also a must-have for APIs running in production.
Over to you: Which other best practices do you follow while designing APIs?
Pgvector vs. Qdrant: Open-Source Vector Database Comparison (Sponsored)
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Looking for an open-source, high-performance vector database for large-scale workloads? We compare Qdrant vs. Postgres + pgvector + pgvectorscale.
Top 30 AWS Services That Are Commonly Used
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We group them by category and understand what they do.
Compute Services
1 - Amazon EC2: Virtual servers in the cloud
2 - AWS Lambda: Serverless functions for event-driven workloads
3 - Amazon ECS: Managed container orchestration
4 - Amazon EKS: Kubernetes cluster management service
5 - AWS Fargate: Serverless compute for containers
Storage Services
6 - Amazon S3: Scalable secure object storage
7 - Amazon EBS: Block storage for EC2 instances
8 - Amazon FSx: Fully managed file storage
9 - AWS Backup: Centralized backup automation
10 - Amazon Glacier: Archival cold storage for backups
Database Services
11 - Amazon RDS: Managed relational database service
12 - Amazon DynamoDB: NoSQL database with low latency
13 - Amazon Aurora: High-performance cloud-native database
14 - Amazon Redshift: Scalable data warehousing solution
15 - Amazon Elasticache: In-memory caching with Redis/Memcached
16 - Amazon DocumentDB: NoSQL document database (MongoDB-compatible)
17 - Amazon Keyspaces: Managed Cassandra database service
Networking & Security
18 - Amazon VPC: Secure cloud networking
19 - AWS CloudFront: Content Delivery Network
20 - AWS Route53: Scalable domain name system (DNS)
21 - AWS WAF: Protects web applications from attacks
22 - AWS Shield: DDoS protection for AWS workloads
AI & Machine Learning
23 - Amazon SageMaker: Build, train, and deploy ML models
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