Edward Callahan on reactive microservice deployments

The O’Reilly Podcast: Modify your existing pipeline to embrace failure in isolation.

By Brian Foster
July 20, 2017
Water droplets. Water droplets. (source: Pixabay)

In this podcast episode, I talk about reactive microservice deployments with Edward Callahan, a senior engineer with Lightbend. We discuss the difference between a normal deployment pipeline and one that’s fully reactive, as well as the impact reactive deployments have on software teams.

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Callahan mentioned how a deployment platform must be developer and operator friendly in order to enable the highly productive, iterative development being sought by enterprises undergoing software-led transformations. However, it can be very easy for software teams to get frustrated with the operational tooling generally available. “Integration is often cumbersome on the development process,” he said. “Development and operations teams are demanding more from the operational machinery they depend on for the success of their applications and services.”

For enterprises already developing reactive applications, these development teams are starting to realize their applications should be deployed to an equally reactive deployment platform. “With the complexity of managing state in a distributed deployment being handled reactively, the deployment workflow becomes a simplified and reliable pipeline,” Callahan said. “This frees developers to address business needs instead of the many details of delivering clustered services.”

Callahan said the same core reactive principles that define an application’s design—responsiveness, resiliency, elasticity, and message driven—can also be applied to a reactive deployment pipeline. The following characteristics of such a pipeline include:

  • Developer and operations friendly—The deployment pipeline should support ease of testing, continuous delivery, cluster conveniences, and composability.
  • Application-centric logging, telemetry, and monitoring—Meaningful, actionable data is far more valuable than petabytes of raw telemetry. How many messages are in a given queue and how long it is taking to service those events is far more indicative of the service response times that are tied to your service-level agreements.
  • Application-centric process monitoring—A fundamental aspect of monitoring is that the supervisory system automatically restarts services if they terminate unexpectedly.
  • Elastic and scalable—Scaling the number of instances of a service and scaling the resources of a cluster. Clusters need some amount of spare capacity or headroom.

According to Callahan, the main difference between a normal deployment pipeline and a reactive one is the ability for the system to embrace failure in isolation. “Failure cannot be avoided,” he said. “You must embrace failure and seek to keep your services available despite it, even if this requires operating in a degraded manner. Let it crash! Instead of attempting to repair nodes when they fail, you replace the failing resources with new ones.”

When making the move to a reactive deployment pipeline, software teams need to remain flexible in the face of change. They also must stay mindful of any potential entrapments resulting from vendor lock-in around a new platform. “Standards really do help here,” Callahan said. “Watch for the standards as you move through the journey of building your own reactive deployment pipeline.”

This post is a collaboration between O’Reilly and Lightbend. See our statement of editorial independence.

Post topics: Software Architecture