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Generative AI and Observability Automation - Sajid Mehmood & Michael Gerstenhaber

One of the biggest challenges in observability is separating the signal from the noise. As artificial intelligence (AI) tools become more powerful and accessible, it has generated a lot of buzz around the role of AI with respect to the performance and reliability of our technical systems and the teams that build and operate them. In this fireside chat, Michael Gertenhaber (Datadog VP of Product) and Sajid Mehmood (Datadog VP of Engineering) will sift through the hype to chat about what generative AI and Large Language Models (LLMs) will really mean for the future of observability and how it can benefit your teams today.

Introduction to Klaw

This video goes over a few problems faced by Kafka based projects and how an open source toolkit like Klaw helps in addressing the issues. Klaw is an open source toolkit / a web application designed to automate the process of creating and managing Apache Kafka topics, authorizations, avro schemas and connectors. Useful links: ABOUT AIVEN Aiven’s cloud data platform helps your business reach its highest potential by making your data work for you.

Debugging Android Devices

All hardware devices experience bugs and need debugging. Android devices in specific are exceptionally complex with several hundred gigabytes of source code, dozens of components, and wide range of uses. In this article we will explore the different facilities and tools available to debug Android based devices and produce robust systems that can handle a wide range of applications from smart fridges, to payment terminals, and of course mobile phones.

Behind the Scenes: Mattermost OpenOps AI Mindmeld | August 15, 2023

Tune in for a behind-the-scenes discussion on the advancement of Mattermost's AI tools and how they're being integrated into the team's current projects. In this installment, the team explores the bot's capabilities — including how much it can remember — and evaluated whether they should focus their efforts on improving the AI model or adding more features to the AI plugin, among other things. Summary.

Controlling Our Destiny: Building When Open-Source Is No Longer Open-Source

The dev world was on fire this weekend, as news of yet another major open-source project was revealed to be in the midst of an identity crisis. The unsettling trend is clear: hit a certain adoption threshold, and then swap the licensing in an attempt to turn dedicated fans into revenue streams. With more companies searching for a sustainable business model and attempting to appease shareholders, the only certainty we have is, what was free yesterday, might be paid tomorrow.

eCommerce Load Testing (Step 3): Build the Environment

In this webinar clip from "Ensuring performance: How major retailers leverage user traffic to validate code changes", Speedscale Co-founder, Nate Lee, explains what to consider when building the environment, including backend dependencies and data. He covers how service mocking can help companies test at a higher velocity in today's complex development environments.

4 ways to master employee growth and development with AI

Amid the whirlwind of today's job market and ever-evolving economy, one critical key to an organization's success emerges: empowering employees with growth opportunities that both entice top talent and secure the future of your business. As millennials and Gen Z progressively make up more of the workforce, investing in their career growth has become crucial to the future health of any organization.

Replicating Traffic: Use Cases & Benefits

In this webinar clip from "Ensuring performance: How major retailers leverage user traffic to validate code changes", Speedscale Co-founder, Nate Lee, talks about why traffic-based testing (unlike manually writing script tests) can help companies move faster and test at the speed of development. He covers the top use cases and benefits of leveraging traffic as the new way to test.