Looking into a possible post-cloud world, we see mentions of different computing paradigms, many of them based on decentralised structures to overcome scalability and user control limitations. Among them is blockchain-as-a-service (BCaaS or BaaS), mimicking the platform-as-a-service (PaaS) user experience for both application providers and consumers. In PaaS, providers first sign up and subscribe to the platform, then design and build their applications and deploy them to the platform where it is executing either permanently or upon incoming network requests or other event triggers. Additionally, developers may advertise their apps at technology-specific hubs such as AWS SAR or Helm Hub. Consumers then adhere to the application terms, which might require a sign-up at the provider site, before being able to invoke and make use of the application.
From June 24 to 27, an academic double-conferences has been taking place in Prague: IC2E 2019, the venerable seventh IEEE International Conference on Cloud Engineering, and ICFC 2019, the recently spun off first IEEE International Conference on Fog Computing. The Service Prototyping Lab at Zurich University of Applied Sciences contributed a tutorial on Kubernetes application engineering on the first conference day. The important research-inspired message conveyed is that Kubernetes is a nice container management platform, but not a cloud platform per se, and characterised by a lack of tools to ensure simplicity and quality in applications, and still emerging understanding of how to design applications in a technically and economically optimal way. This blog post reports on some of the conference discussion topics as a service for those who could not attend..
The eternal software circle of life continues to pose non-trivial challenges. Developers write code, run tests, push and/or deploy, perhaps leading to more tests, and finally see their software used in production. Eventually, they might see everything working out correctly or rather not, as indicated by log messages, user complaints and other side channels, and even more eventually, when nothing else gets in the way, they might even attempt to fix the problem at any code location which might have a probability of contributing to the issue.
We are announcing the latest release of the open source Cyclops framework, as part of our ongoing work to advance metering and monetization across cloud platforms, bringing improvements and new capabilities:
meaningful logs, now able to identify errors more effectively and
provide more information on generated records
checkpointing, with the ability to roll coin rules back using git
versioning and re-create affected records
In a previous post, we showed how it’s possible to trigger a Knative service when a database update occurs using the DebeziumKafka Connect plug-in connected to Knative; here, we continue this work by describing how we connected a Nextcloud file storage service to Knative, triggering a Knative service/function when a file is uploaded to Nextcloud.
While hybrid, multi- and cross-cloud applications are on the rise, even for scenarios in which purely public cloud deployments are planned, having an equivalent private cloud stack available is useful in many ways. With the relative portability of popular open source cloud stacks, this is rather trivial to accomplish. For many large cloud providers, there are commercial solutions like Microsoft’s Azure Stack, IBM’s Cloud Private, Oracle’s Cloud Native Framework, Google’s Anthos (née CSP), Alibaba’s Apsara Stack and Amazon’s AWS Outposts (as well as Greengrass for Lambda and other specialised offers). Yet sometimes, these are not an option for technical or business reasons. In this blog post, alternative options are discussed.
The past May 7th one of the multiple AWS Summit of this 2019 was held at IFEMA in Madrid and, of course, we were there to scout for important technological trends which may see adopters in need of research!
The Serverless Application Repository by Amazon Web Services (AWS SAR) is, in simplified terms, a marketplace for Lambda functions. You can speed up application development by building on the functions (or function compositions) provided by it, and you can share your own functions with other cloud application developers. AWS SAR was launched over a year ago. In the Service Prototyping Lab at Zurich University of Applied Sciences, we are investigating better ways of building applications for cloud and post-cloud environments. Consequently, we did a full year observation of AWS SAR to find out what’s in it and what’s going on. Read on for some interesting excerpts and findings and for accessing the study document.
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.
The first four “wild” years of serverless computing, starting with simple Function-as-a-Service (FaaS) launches in 2014, are over, and we are in the fifth year now. All major cloud companies offer FaaS, corresponding Backend-as-a-Service (BaaS), and related “serverless” services such as frameworks for cloud function-based data processing at the edge or in constrained environments. Researchers from universities, research institutes and research divisions in companies have covered this development, and proposed improved systems and frameworks, since 2016 – trailing two years behind industry initially, but with promising designs and prototypes which may give the necessary impetus for a next-generation serverless computing paradigm. We have surveyed 130+ research papers and announce the Serverless Research Output website which makes the results accessible.