In previous blog posts – here and here – we showed how to set up OpenWhisk and deploy a sample application on the platform. We also provided a comparison between the two open-source serverless platforms OpenWhisk and Knative in this blog post. In progressing this work, we shifted focus slightly to that other critical component of realistic serverless platforms, the services that they integrate with – so-called Backend-as-a-service – which are (arguably) more important. For this reason, in this blog post we look at how to integrate widely used databases with Knative and potentially OpenWhisk in future.
Our initial thoughts were to leverage database trigger mechanisms and write components which would listen to these events and publish them to a Kafka bus. Indeed, we started to write code that targeted PostgreSQL to do just that, but then we came across the Debezium project which essentially solves the same problem, albeit not in the same context, but with a much more mature codebase and support for multiple database systems. It didn’t make sense to reinvent the wheel so the objective then turned into how to best integrate Debezium with Knative.
In two previous blog posts – here and here – we discussed our experience with deploying OpenWhisk on Kubernetes on OpenStack. As applied researchers at the Service Prototyping Lab, we are investigating potential use cases for such setups and for FaaS-based applications in general. In this blog post, we will therefore describe how we built a sample MQTT-based application that shows OpenWhisk in action for sensor data processing for future Internet of Things and smart dust scenarios.
The basic idea of the application is that it consumes data from an MQTT feed, stores it in a database and provides a means to access the database via a web UI. The architecture of the application is shown in the figure below. The application is based on this blog post.
In a previous blog post, we described our experience with deploying OpenWhisk on Kubernetes on OpenStack. During subsequent testing, we observed some issues with the OpenWhisk deployment wherein some OpenWhisk components – specifically, the controller and the invoker – would fail to restart after rebooting the machines running the Kubernetes nodes for maintenance tasks. To fix this, we had to redeploy OpenWhisk after each failure which resulted in significant data loss and was clearly an unacceptable operational solution.
Serverless applications is one topic that SPLab has been working on for a couple of years now, with, for example, our work on a stand-alone FaaS platform Snafu, work on disaggregating applications into serverless functions, Podilizer and other activities. Having organised ESSCA some weeks ago, we are now again exploring the technical limits and challenges in this space. This blog post reports about our experience of running the combination of OpenWhisk, Kubernetes, Helm and OpenStack.
AWS Cloud Summer School Switzerland was scheduled as a five-day event organized by Amazon. The event took place from September 3 – 7, 2018 in Zurich, Switzerland. From the outline, it appeared worth attending as it offered high-quality educational modules and hands-on labs. The SPLab was thus present at the event and this blog post aims to briefly summarize what took place and what implications can be inferred for the near future of cloud applications. Continue reading
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Submit your articles to the Journal of Cloud Computing
Attend the 12th IEEE/ACM UCC in Auckland NZ
11th IEEE/ACM UCC / 5th IEEE/ACM BDCAT 2018 – Thank you for attending.
European Symposium on Serverless Computing and Applications 2018 – Thank you for attending.