Synchronous Calls Are Killing Your Availability — Here’s What to Do Instead

Synchronous microservices look great on paper.

Synchronous microservices look great on paper.

They are easy to read, easy to debug, and they map perfectly to how we think: “I send a request, I get a reply.” No surprises, right?

Except when things go wrong. Which in distributed systems is most of the time.

The Hidden Cost of Synchronous Calls

Let’s say you have got five microservices: MS1 through MS5. MS1 calls MS2, MS2 calls MS3, and so on.

If any one of them is down, the whole chain fails. Your user hits “submit” and gets a spinning loader - or worse, a 500 error.

Congratulations: your highly modular microservice architecture just turned into a monolith with single-point-of-failure behavior.

And fixing it? That’s where things get messy.

Engineers start bolting on circuit breakers, retries, backoff strategies, and compensating logic. Suddenly, your clean service is a jungle of resilience code.

All of this just to cope with the fact that one service might be temporarily offline.

You Don’t Need 100% Uptime Everywhere

Most microservices don’t need to be up 100% of the time.

• Maybe it’s fine for your reporting service to catch up later.
• Maybe it’s fine for inventory updates to lag a little.

What you do need is a way to avoid cascading failure.

This is where asynchronous messaging shines.

The Asynchronous Advantage

By decoupling the sender and the receiver, you can:

• Deploy without downtime: just drain the queue
• Scale automatically with competing consumers
• Tolerate crashes without losing messages
• Add new processing logic without touching the sender

Asynchronous messaging gives you loose coupling, which is a fancy way of saying “my stuff keeps working even if yours doesn’t.”

But Wait - What About Delivery Guarantees?

Here is where it gets tricky.

It’s easy to send a message asynchronously.

It’s harder to make sure it gets processed exactly once.

Most brokers don’t do that out of the box. Kafka? RabbitMQ? They really only give you best-effort guarantees.

Which leads right back to the problem you were trying to avoid: lost updates, duplicates, retries.

This is why we advocate for XA-backed messaging, even in modern microservice stacks.

Yes, XA. The thing people love to hate.

The Modern Take on XA: Lightweight, Cloud-Native, and Fast

Atomikos brings XA into the cloud era. It works with Spring Boot, JDBC, JMS, Hibernate — no heavyweight app servers needed.

And with LogCloud, you get decentralized recovery, even in containerized, crash-prone environments.

What does this mean in practice?

• No more phantom messages
• No more missing updates
• No more fragile retries

Just exactly-once delivery, front to back.

TL;DR

• Synchronous calls tie your availability to your weakest service
• Asynchronous messaging gives you flexibility, scale, and resilience
• Most brokers don’t guarantee exactly-once delivery
• Atomikos + XA = exactly-once, cloud-native, no retries

If you are serious about uptime and consistency, it’s time to ditch the synchronous habit.

Get started with Atomikos and modernize your messaging — the reliable way.