In his GA announcement, Emrah outlined the newest features in our GA product, including rich support for Node.js applications. Here, I want to go into our support for manual and automated instrumentation and show you how to add this to your Node.js applications. But, first, let’s talk about why instrumentation is useful in serverless environments...
We believe that your data should not exist in a silo and you should be able to view, manipulate, and analyze it in the way best suited for your business, using your favorite platforms. With this goal in mind, we feel integrations with popular data platforms are an important part of Thundra’s offering to the serverless monitoring and observability space.
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.
Greetings everyone! I’ve been looking forward to this moment for a long time now. After a year of development work, I am very excited to announce that Thundra is taking flight out of beta.
If your AWS Lambda application is experiencing terrible latencies and delivering a frustrating user experience, you may target high CPU loads as the main problem to solve.
How to debug and identify parts of the code that cause a bottleneck effect in a serverless application can be a difficult question to tackle. For a regular application, you have many debugging and monitoring tools that enable you to observe your application while it is running, hence making it easier to identify any faulty and inefficient parts of your application. However, as you may already know, serverless is a brand new technology and, therefore, it lacks such tools that provide debugging and tracing capabilities. As first-hand users of AWS Lambda functions, we understand the agony that comes with not being able to trace and debug your functions, especially when there are errors or there is unexpected behavior. Considering how rapidly popularity of serverless is growing it is imperative for the programmers to have means of unimpeded, smooth development. This is where Thundra comes in, “Full Observability for AWS Lambda”, which aims to give, as the slogan suggests, full visibility of what is going on in your application to ease the programmer’s life.
Alexa is Amazon’s virtual assistant and the brain behind tens of millions of Echo devices like the Echo Show and Echo Spot. Alexa provides capabilities, (called skills), that enable customers to experience more personalized service. The Alexa Skills Store currently has more than 45,000 published skills and this number is increasing rapidly.
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?
First, let me introduce myself: My name is Christina Wong and I joined Thundra in May 2018 as VP of Marketing. My background includes roles in mechanical engineering, sales, product marketing, and partnerships across a variety of different sized organizations (from startup to large companies) and in several different industries (automotive, defense, software). I love working in the space where business and complex technical topics intersect and I am especially fascinated by new software challenges and adoption of new application paradigms of all sorts. This includes cloud, microservices, containers, devops, and, now, serverless. In my spare time, I am a mechanic and race car driver on a team called The Cosmonaughts.