Horizontally scale tested deployment models to improve performance

Horizontal scaling involves increasing the number of replicas (pods or virtual machines) for a given service. Similar to vertical scaling, this approach is useful for high resource utilization or workload scaling.

Benefits of horizontal scaling
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  • Improved availability: Distributes load across more instances to reduce the impact of a single slow or failing node.
  • Redundancy: Provides extra capacity, allowing individual service nodes to recover or cool-off without impacting overall availability.
  • Increased authentication capacity: Scaling the platform gateway directly increases the platform’s authentication throughput, because each platform gateway pod includes its own authentication service.
  • Repeatable scaling procedure: After the instance size and configuration are verified for your environment, deploy identical instances to scale.

Drawbacks and other considerations for horizontal scaling
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  • Database limitations: Scaling the application increases the maximum potential number of database connections from worker processes. This also increases the overall memory, I/O, and CPU utilization of the PostgreSQL instance. When you scale past the tested deployment models, deploy separate PostgreSQL instances per component (platform gateway, Event-Driven Ansible, automation controller, automation hub).
  • Health Check Overhead: In a mesh architecture, each Envoy proxy sends health checks to every other cluster member. Horizontal scaling increases this baseline traffic, adding to system usage.