Lead Image © Juri Samsonov, Fotolia.com

Mocking and emulating AWS and GCP services

Unstopped

Article from ADMIN 82/2024

By Ankur Kumar

Mock and emulate AWS services locally and use official Google Cloud Platform service emulators to unblock development and operations – all without paying a dime.

Modern software-as-a-service (SaaS) offerings are highly dependent on external cloud providers to run and work reliably, but nothing comes without conditions or comes free, especially public cloud services. Nowadays, public cloud services are company cost centers, with strict measures in place to control costs.

Like all modern distributed systems, all major cloud service providers go through major downtime now and then. Both cost-control measures and downtime hamper internal development, quality assurance (QA), and other dependent stakeholders by blocking productivity. These reasons are enough to consider emulating the required cloud services to unblock internal teams, keep them working on their goals with full control, and avoid any resistance or other unnecessary blocking requirements such as money, access policies, and so on. Cloud providers also started realizing these needs and started providing users the capabilities to launch or mock important services locally.

Local GCP with Emulators

Google Cloud Platform (GCP) provides libraries and tools to interact with their products and services through the Cloud software development kit (SDK). Pub/Sub, Spanner, Bigtable, Datastore, and Firestore cloud services have official emulators, exposed through the Google Cloud command-line interface (gcloud CLI) by Cloud SDK.

These emulators could be run natively on your laptop if the required dependencies are installed first, but I find that Docker containers are the best way to run these emulators out of the box because GCP provides various flavors of the official cloud-sdk base image. Therefore, you'll see various code snippets in the next sections to run various GCP cloud service emulators and their respective quick test routines in Docker containers.