Rootconf Pune edition

Kubernetes has dramatically changed the way we deploy and manage the cloud native applications, but at the same time, it has also added new challenges for day-to-day tasks like monitoring - alerting - troubleshooting workflow, gaining more visibility into services, etc.

BotKube is a Kubernetes monitoring tool which can be integrated as a Slack app or a Mattermost app to get real-time notifications about Kubernetes resource events.
This talk will provide an overview of how BotKube uses Kubernetes APIs to monitor resources and how BotKube helps in troubleshooting the failed deployments. With BotKube, it is possible to write a filter to enforce custom policies on Kubernetes resource specs and get custom recommendations like - to avoid “latest” image tags for container images.

Key takeaways:

• Debugging Kubernetes deployments via messaging platforms like Slack
• Learn how Kubernetes APIs can be used to monitor resources
• Writing a BotKube filter to apply custom policy and get recommendations

The intended audience:

• DevOps Engineers
• Kubernetes practitioners
• SREs
• Anyone having an interest in developing tools around Kubernetes

Outline

• What are we trying to solve
• How BotKube helps
• Demo
• BotKube backend architecture
• How to write a custom filter
• Q/A

Requirements

Basic knowledge of Kubernetes required

Speaker bio

Prasad works as a Software Engineer at infracloud.io. His main areas of interest are Kubernetes, Linux and Open source. He is the creator and maintainer of botkube.io, an ex-GSOCer and has contributed to several open source projects including GCC, Kubernetes and Gobot. He likes listening to music and hiking in his free time.
You can reach him through https://twitter.com/PrasadGhangal

• github: https://github.com/PrasadG193
• linkedin: https://www.linkedin.com/in/prasadghangal

Links

• www.botkube.io
• https://github.com/infracloudio/botkube
• https://slack.com/apps/AF5DZLHPC-botkube
• https://integrations.mattermost.com/botkube/
• https://youtu.be/hD-CCAuXu6Y?t=16m37s
• https://github.com/PrasadG193
• https://www.linkedin.com/in/prasadghangal