We have moved beyond simple HTTP calls between containers. The modern microservice landscape is faster, cheaper, and smarter. Here are the latest patterns you need to know.
In the early 2020s, we attached "sidecar" proxies (like Envoy) to every container to handle traffic. This doubled our resource consumption.
The Pattern: Sidecar-less Service Mesh via eBPF.
How it works: Instead of a container in every pod, the service mesh runs at the operating system kernel level using eBPF (Extended Berkeley Packet Filter). It handles networking, security, and observability for all services on the node instantly.
Result: 30-40% reduction in infrastructure overhead and near-zero added latency.
The "Backend for Frontend" (BFF) pattern has evolved into the Supergraph.
The Problem: Front-end teams hated calling 15 different microservices to render one page.
The Solution: We use Federated GraphQL. Each microservice publishes its own small "sub-graph." A gateway automatically stitches these into one unified API.
Result: Front-end developers query a single endpoint, while back-end teams retain full decoupling and ownership of their data.
Docker containers are powerful but can be too heavy for simple tasks.
The Pattern: Cloud-Native WebAssembly (Wasm).
How it works: Wasm modules are tiny, secure binaries that start in microseconds (vs. seconds for containers). They are platform-independent and run anywhere.
Result: Ideal for high-scale, bursty tasks like image resizing, PDF generation, or quick AI inference, often at a fraction of the compute cost of containers.
We have finally learned that synchronous HTTP calls between services create a "distributed monolith."
The Pattern: Event-Carried State Transfer.
How it works: Instead of Service A calling Service B to ask for user details, Service B publishes an event with the full data: UserUpdated: {id: 1, name: "Alice", role: "Admin"}. Service A listens to this and updates its own local cache.
Result: Service A can function 100% of the time, even if Service B is completely offline.
The newest consumer of your API is not a human developer—it's an AI Agent.
The Pattern: Semantic Manifests (MCP).
How it works: Microservices now expose a "Semantic Manifest" (often using the Model Context Protocol). This describes what the service does in natural language, allowing AI agents to dynamically discover and call your tools to solve complex user requests.
Result: Your microservices become "AI-ready" instantly, capable of participating in autonomous agentic workflows.