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[UPCOMING WEBINAR]: Happier Customers with Serverless and Observability. Save Your Spot! 🎬

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It has been 2 weeks after Re:Invent. Last week, as I recovered from the Las Vegas-to-Turkey trip jet lag, I took some time to evaluate what we learned from the event, made some adjustments to the Thundra roadmap, and got back into the daily work routine. Now, I finally have some time to share my thoughts from the event with this recap blog.

First, the AWS team does a great job putting on the conference. Previously, I followed Re:Invent via live streams but this was my first in Vegas and I really admired the quality of work by the team to manage, educate, and entertain tens of thousands of attendees.

I was often on duty at our Thundra booth, giving demos to visitors curious about AWS Lambda, Thundra, or simply just curious. Traffic was non-stop, giving me the opportunity to validate assumptions and clarify some open questions I had gathered before coming to Re:Invent. I want to thank the +1300 visitors who stopped by our booth and shared their experiences and needs regarding serverless, monitoring or both.

 

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First, heads to all our beta customers. In order to see data in the Thundra Web Console and take advantage of our GA features, you need to update your existing agents. Currently, all beta agents send data to “beta.thundra.io”. However, this platform will be discontinued by November 1st. We recommend that you immediately update your agents to the latest versions, which will allow you to receive data in console.thundra.io. 

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Whatever monitoring tool you use for AWS Lambda, privacy of the monitoring data is always a headache. It is very normal and common that monitoring data can include sensitive data or clues about sensitive data. To solve this, it is better to keep the monitoring data as a secret at your own instance(s). But, how will I visualize and extract insights from the data? Will I allocate time to query this data yourself? The queries will take too much, which fields will I index?

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Our customers love Thundra’s trace charts because the charts help identify which parts are problematic in an AWS Lambda invocation. In one of our previous blog posts, we walked through how to detect a real life invocation problem with the Thundra trace charts.

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