Guest post by Adrian Gonzalez Sanchez, Head of AI Customer Success at Peritus.ai
The international and cloud-native context
The evolution of the cloud-native ecosystem has been unstoppable during the last five years. The cohort of companies, experts, and projects is continuously growing, and factors like a) the increasing level of cloud adoption via managed services such as AWS, Azure, or GCP, and b) the role of the Cloud Native Computing Foundation (CNCF) as the vendor-agnostic epicenter of Kubernetes-related projects and technologies are contributing to the organic generation of a very strong and dynamic community.
Additionally, the unique and special circumstances of the 2020-21 period have created a new wave of collaboration within companies and communities around the world. Online interactions via communication and productivity tools, meetings, text-based chat discussions, forums, virtual events, and even new ways of interaction on social networks (e.g., audio discussions, technical experts offering their time and mentorship in exchange for some small donations to NGOs, etc.). These interactions have resulted in a humongous amount of unstructured data that represents a tremendous source of knowledge.
The challenge and the related (data-driven) opportunity
Now, how do we leverage all of this generated knowledge? The problem today is that unstructured information is not being carefully treated and collected in a way that could help to optimize community dynamics. Most of the existing solutions or community projects are focused on the measure of specific metrics (e.g., commits, number of interactions, etc.), but they ignore the nature and content of the technical discussions.
Let’s be honest… we actually see it on a daily basis, every time someone posts a question via Slack and we realize that this is either a recurrent question that could be answered based on past information, or a part of a discussion that we missed during the last hours or days. The granularity of channels, topics and discussions is huge, and the attention span is limited even for the most detailed-oriented individuals. The same applies to forums and other technical communities. How can we enable a higher and more effective sharing of all of this knowledge?
Interactions within the communities and companies can be defined as a combination of three main elements:
- People – The experts who are working on different topics, asking and answering questions, etc. People and their expertise are a crucial portion of the community assets.
- Products/projects – The specific solutions on which the community is working and focusing their efforts, such as commercial or open-source products, new CNCF projects, or company spin-offs based on promising technologies. Our cloud-native ecosystem of technologies is rich, dynamic, and growing.
- Topics – The main areas of discussion for specific communities and companies. This is useful to track the trends over time and to understand the relevant “pieces of knowledge” for the community experts (people).
If we add the time dimension such as specific dates or product releases, we can get a very precise snapshot of the community and its related knowledge. If we also connect the different communities, we can then obtain what we define as THE Cloud-Native Knowledge Network. Then, we can know pretty much everything about this network and leverage it for future discussions, connecting experts and topics, and generating recommendations based on past solutions.
The evolution of the technical communities and how to enable their growth
The reality is that communities are “becoming communities” before they actually turn into one. It sounds weird, but it is easy to explain: the ability of a vendor, service provider, or adopter to become a community depends on very early-stage and critical steps. Concretely, do we understand the reason why very knowledgeable developers will pay attention to our solutions? Are we exploring actionable insights that will allow us to leverage trending topics to engage our audience? Do we have full visibility over our community of experts, not only within our very own forum but also via Stack Overflow and other developer communities? Can we connect problems and people in a timely manner? Are we making informed decisions for activities such as solution support, community management, developer relations, or customer success?
If we focus exclusively on the cloud-native ecosystem, these questions are even more relevant. CNCF’s Technical Oversight Committee decides which projects are achieving a specific status level, ranging from sandboxing (very early-stage initiatives), incubating, or graduating (Kubernetes, Helm, and Harbor are part of this selective group). Community growth happens when the project teams prepare new announcements, share relevant news and technology evolutions, and connect with the technical experts. These activities will bring more people willing to contribute and help organizations and projects, which is critical for them to continue to evolve and grow.
The value for the main superstars: the cloud-native developers
Cloud-native development includes a panoply of roles, including cloud infrastructure engineering, site reliability engineering (SRE), DevOps, and software development. These personas and their skills are sources of knowledge and discussions that help companies and communities build their networks. And those communities are spaces for networking and a way to increase the reputation of the experts.
With all these pieces together, we see 2021 as the year for a more data-driven and dynamic cloud-native community, in which advanced tools will help people to understand where and when the key discussions are happening, even for cases where these discussions are distributed in different places such as Slack, Twitter, Vendor Forums and Stack Overflow, , or for cases where the notion of community is still a work in progress or unclear (e.g., new CNCF projects).
If you want to join The Cloud-Native Knowledge Network, everyone is welcome! See you soon.
About the Author
Adrian Gonzalez Sanchez is an AI technology leader who has deep academic and professional experience. As the head of customer success at Peritus.ai, the AI recommendation engine for support automation, he works closely with customers to help improve technical support for cloud-native technologies. He previously worked at IVADO Labs, a pioneer in AI development, and teaches a number of technology courses on AI and big data at École des dirigeants HEC Montréal and Concordia University.