Last week, on 6 Dec 2022, I was invited to share my experiences on the Data Protection Gumbo podcast with its host Demetrius Malbrough and we had a nice chat about my journey into cloud native observability (o11y) since joining Chronosphere.
The title of episode 171 is, Your First Steps in Cloud Native Observability and we covered a bunch of questions around the series of articles I've been writing called the O11y Guide. It's taking you along for the journey in my learnings as I go from an application development background into the world of cloud native o11y.
Below is a list of the topics we covered in the 20+ minutes of the podcast, which you can find on all major platforms to listen / subscribe to.
A podcast is always interesting, as you join a virtual call on video, then record the session. In this case the video was used for a small clip to promote the episode going live and was shared on social media channels.
Without giving a full transcript of the episode, I thought it might be nice to preview some of the questions that were asked. I'll leave it up to you the reader to then jump over to the podcast for a listen!
We started off with a look at what cloud native observability means to the listeners and I gave a bit of background of how I was sharing my journey from application development to observability. This is the foundation of my O11y Guide series you can find on this blog.
Next, the transition is made by asking what are the 3 pillars of observability and are they really relevant to modern cloud native observability. I spent some time talking about how you can't just hold on to the technology views in monitoring and expect to be able to massively scale in a cloud native world. This requires a business view of how to achieve your goals without focusing on the technology used. We cover the 3 phases of cloud native observability; know, triage, and understand which involves the process used by observability teams across the globe to solve problems in their cloud native environment and focuses on outcomes rather than underlying data formats (logs, traces, metrics).
Demetrius then asks what data has to do with cloud native observability and I share some thoughts on the massive data being generated in cloud native platforms at scale and how that's becoming the biggest roadblock to organizations succeeding in the cloud. My answer to this question pointed out a very shocking fact, that organizations are paying more for their observability data than for their income generating business application and customer generated data.
Next we covered what a sample application in a cloud native environment would generate as an observability tooling target. This led to a discussion on average data retention rates and the cost of unused data that's being collected and stored in the cloud.
He then asked me if companies are paying to retain all their observability data and if so, what can be done to reduce some of those costs? I share an architectural overview of how you can use Chronosphere's product which includes a control plane to give users the ability to control the amount of data after ingestion, but before storage to save on unused data collection. I mention that our customers are saving around 50% on their data storage using this control plane.
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Finally, we dive into the books I'm reading, so tune in to find out!
Also worth mentioning, if you have something interesting to talk about in the data world, reach out to Demetrius and he might have a slot for you to join his podcast!