Data Engineering Podcast Honeycomb Data Infrastructure with Sam Stokes - Episode 20
Feb 26, 2018
41:33
Summary
One of the sources of data that often gets overlooked is the systems that we use to run our businesses. This data is not used to directly provide value to customers or understand the functioning of the business, but it is still a critical component of a successful system. Sam Stokes is an engineer at Honeycomb where he helps to build a platform that is able to capture all of the events and context that occur in our production environments and use them to answer all of your questions about what is happening in your system right now. In this episode he discusses the challenges inherent in capturing and analyzing event data, the tools that his team is using to make it possible, and how this type of knowledge can be used to improve your critical infrastructure.
Preamble
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- Your host is Tobias Macey and today I’m interviewing Sam Stokes about his work at Honeycomb, a modern platform for observability of software systems
Interview
- Introduction
- How did you get involved in the area of data management?
- What is Honeycomb and how did you get started at the company?
- Can you start by giving an overview of your data infrastructure and the path that an event takes from ingest to graph?
- What are the characteristics of the event data that you are dealing with and what challenges does it pose in terms of processing it at scale?
- In addition to the complexities of ingesting and storing data with a high degree of cardinality, being able to quickly analyze it for customer reporting poses a number of difficulties. Can you explain how you have built your systems to facilitate highly interactive usage patterns?
- A high degree of visibility into a running system is desirable for developers and systems adminstrators, but they are not always willing or able to invest the effort to fully instrument the code or servers that they want to track. What have you found to be the most difficult aspects of data collection, and do you have any tooling to simplify the implementation for user?
- How does Honeycomb compare to other systems that are available off the shelf or as a service, and when is it not the right tool?
- What have been some of the most challenging aspects of building, scaling, and marketing Honeycomb?
Contact Info
- @samstokes on Twitter
- Blog
- samstokes on GitHub
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
- Honeycomb
- Retriever
- Monitoring and Observability
- Kafka
- Column Oriented Storage
- Elasticsearch
- Elastic Stack
- Django
- Ruby on Rails
- Heroku
- Kubernetes
- Launch Darkly
- Splunk
- Datadog
- Cynefin Framework
- Go-Lang
- Terraform
- AWS
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA