My Apple M1 MacBook: lots of cores, memory and crashing containers

multi-architecture docker images   docker  

Recently, I was excited to buy an Apple M1 MacBook: lots of cores and memory. I couldn’t wait to start using it for development so I tried running the Eventuate Tram Customers and Orders example application, which illustrates how to use the Sagas and CQRS patterns to implement operations that span multiple services. Sadly, running this application on my shiny new MacBook wasn’t straightforward due to problems running Docker containers.

This is the first of series of posts that describe what I needed to do to run the application successfully. The other articles in this series are:

Not all Docker images run (well) on the M1 MacBook

It turns out that Apple M1 ARM-based architecture is a double edged sword. On the one hand, it is an energy efficient, high-performance architecture. But on the other hand, it’s a new entrant into the world of server-side development, which has been traditionally been dominated by Intel.

The problem is that Docker images are not inherently portable across multiple architectures. Many Docker images including those used by the example application are Intel specific. Docker Desktop for Mac uses QEMU to run Intel-based images on ARM. But sadly, the emulation is less than perfect. The documentation even describes it as ‘running Intel-based containers on Arm-based machines should be regarded as “best effort” only.’ While some containers run without problems, others crash or have poor performance.

Some Intel-based pre-built Docker container images fail

The Customer and Order applications runs several infrastructure services using the following pre-built Docker container images, which are all Intel-based:

  • eventuateio/eventuate-mysql - fails to start with runtime: failed to create new OS thread (have 2 already; errno=22)
  • eventuateio/eventuate-cdc-service - frequently hangs or crashes
  • confluentinc/cp-kafka:5.2.4 and confluentinc/cp-zookeeper:5.2.4 - seem unreliable
  • openzipkin/zipkin:2.21 - seems fine although it might run slowly
  • mongo:3.6 - seems fine

Poor performance of locally built Docker images

These pre-built container images aren’t the only images used by the Customer and Orders application. The application also packages its three services as Docker images. Those images are built using the eventuateio/eventuate-examples-docker-images-java-example-base-image base image, which is an Intel-based image. Despite being built locally, these images are also Intel and either crash or run extremely slowly - appearing to take 4x longer to startup.

The solution is to use multi-architecture Docker images

The solution is to change the application to use multi-architecture Docker images that support both the Intel and ARM architectures. Hopefully, I can simply find newer multi-architecture versions of the Confluent platform and Zipkin images on Docker Hub. It also requires changing the Eventuate platform to build multi-architecture eventuate-mysql, eventuate-cdc and eventuate-examples-docker-images-java-example-base-image container images.

In later articles starting with Building multi-architecture Docker images for Intel and ARM, I describe the changes to application and the Eventuate platform that are needed to run this application on my MacBook. 00


multi-architecture docker images   docker  


Copyright © 2024 Chris Richardson • All rights reserved • Supported by Kong.

About Microservices.io

Microservices.io is brought to you by Chris Richardson. Experienced software architect, author of POJOs in Action, the creator of the original CloudFoundry.com, and the author of Microservices patterns.

New workshop: Architecting for fast, sustainable flow

Enabling DevOps and Team Topologies thru architecture

DevOps and Team topologies are vital for delivering the fast flow of changes that modern businesses need.

But they are insufficient. You also need an application architecture that supports fast, sustainable flow.

Learn more and register for my June 2024 online workshops....

NEED HELP?

I help organizations improve agility and competitiveness through better software architecture.

Learn more about my consulting engagements, and training workshops.

LEARN about microservices

Chris offers numerous other resources for learning the microservice architecture.

Get the book: Microservices Patterns

Read Chris Richardson's book:

Example microservices applications

Want to see an example? Check out Chris Richardson's example applications. See code

Virtual bootcamp: Distributed data patterns in a microservice architecture

My virtual bootcamp, distributed data patterns in a microservice architecture, is now open for enrollment!

It covers the key distributed data management patterns including Saga, API Composition, and CQRS.

It consists of video lectures, code labs, and a weekly ask-me-anything video conference repeated in multiple timezones.

The regular price is $395/person but use coupon ILFJODYS to sign up for $95 (valid until April 12, 2024). There are deeper discounts for buying multiple seats.

Learn more

Learn how to create a service template and microservice chassis

Take a look at my Manning LiveProject that teaches you how to develop a service template and microservice chassis.

Signup for the newsletter


BUILD microservices

Ready to start using the microservice architecture?

Consulting services

Engage Chris to create a microservices adoption roadmap and help you define your microservice architecture,


The Eventuate platform

Use the Eventuate.io platform to tackle distributed data management challenges in your microservices architecture.

Eventuate is Chris's latest startup. It makes it easy to use the Saga pattern to manage transactions and the CQRS pattern to implement queries.


Join the microservices google group