Google has recently announced that Google Cloud Workflows, the service to orchestrate Google Cloud and HTTP-based API services with serverless workflows, is now generally available. Workflows Connectors are also now in public preview.
Google Cloud Workflows requires no infrastructure management. The platform also scales on demand, including scaling down to zero if no requests are processed. This product can be used to develop complex serverless applications, building on workflows that connect a series of serverless tasks together in a predetermined order, and work with other managed services like Google Cloud's APIs, Cloud Functions or Cloud Run.
Among the features of the new service are: error handling with configurable retry policies; a reliable workflow execution targeted to enterprise and line-of-business applications; and the ability to pass information between steps using JSON parsing and expression-based variable manipulations. Workflows publishes connectors to make it easier to access other Google Cloud APIs within a workflow.
Mete Atamel, senior developer advocate at Google, explains why he thinks the new service can help developers:
Connecting services is one of those things that "should be easy" but in reality, it takes a lot of time and effort. You need to figure out a common connection format for services to use, make the connection, parse the results, and pass the results on. I am not even mentioning error handling, retries and all those production readiness type features that you ultimately need to do.
Among the use cases that can benefit from workflows, inventory management processes, e-commerce transactions and other services that require an orchestration layer. Filip Knapik, product manager at GCP, wrote an article before the GA that covers examples for Workflows such as processing files uploaded to a storage bucket, tagging the files based on the extension. He explains:
To oversimplify, if you want to manage your data processing, ETL or machine learning pipelines and integrate with data products like BigQuery or Dataflow — Cloud Composer is the way to go. However, if you want to process events or chain APIs in a serverless way, with bursty traffic patterns, high execution volumes or low latency, you likely need to look at Workflows first (..) Workflows scales out automatically with no "cold start" effect and with a fast transition between the steps. This makes Workflows a good fit for latency-sensitive applications.
GCP is not the only cloud provider offering managed workflows. Microsoft has Azure Logic Apps and Amazon introduced AWS Step Function over four years ago. Tim Bray, formerly VP/distinguished engineer at AWS, wrote a detailed comparison between the AWS and GCP services. But regardless of which features they offer and the maturity of the different services, he concludes that choosing the workflow service is a platform choice:
Which workflow service should you use? That’s dead easy. You should use a declaratively-specified fully-managed cloud-native service that can call out to a variety of workers, and which combines retrying and exception handling to achieve high reliability. And, you should use the one that’s native to whatever public cloud you’re in!
Google Cloud Workflows has a pay-per-use pricing model based on the number of steps and the number of external HTTP calls, with the first 5000 steps and 2000 HTTP calls free every month.
