Introduction to Datadog

Datadog is a SaaS product which offers products in infrastructure monitoring, application performance monitoring and logging. Datadog's main purpose is to collect metrics and alert when something goes wrong. With all of the products working in unison, its easy to get down to the root cause analysis of any outages as well as prevent outages before they happen.

My Role

At Datadog I was employed as a Product Manager on the container integrations team. The container integrations team is responsible for the collection of container level metrics of multiple run-times such as Docker, cri-o and containerd. As well, the team is responsible deployment of the Datadog agent on various platforms such as self hosted Kubernetes, GKE, AKS, EKS and Fargate to name a few. The containers team was composed of five engineers, a team lead, three support engineers and myself.

Job Duties

Throughout my term, I learned more and more about containerized environments and their orchestration technologies. Previously to this internship, I have never touched Docker or Kubernetes, so throughout this entire term I was always self-learning the different concepts and how engineers use these technologies in production. One of the first contributions I added was a go to market strategy for the Kubernetes control plane integrations we released. This included creating customer facing default dashboards which showcased the different metrics that I believed were important for engineers to view. As well, I wrote a technical blog post explaining the curated list of metrics as well as information emphasizing the importance of the control plane components. Secondly, another larger project I contributed to was improvements to the containers page. To begin this project I interviewed over 30+ customers about their Kubernetes usage and gathered their requirements as well as empathized with their struggles to create user stories. Eventually I transitioned these user stories into a full product specification and eventually coordinated with multiple teams to plan the engineering scope. I provided input to multiple designers across multiple teams, which eventually produced a mock up I was satisfied with presenting in front of customers. I continued to now interview customers with the mockup and iterating off their feedback. Once I was satisfied with the version 1.0 of this project, I wrote a PRFAQ to present in front of the product team to gather feedback and coordinate work between teams.

Conclusions

In conclusion, Datadog was a great learning experience and a huge step in my career development. This being my first product manager role, I can with confidence say that I do want to continue down this path. I want to thank my manager Michael Gerstenhaber for doing a great job of constantly providing feedback to improve my soft skills, technical skills and business knowledge.