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Dynatrace launches automatic end-to-end observability via traces for AWS Lambda (Preview program)

Dynatrace

This additional insight enables you to design strategies for handling the effects of cold starts, like warming up your functions or configuring provisioned concurrency for your functions. Before you begin, be sure to sign-up for the Preview program. Once you’ve received your invitation to the Preview program you need to: 1.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

Part 3: System Strategies and Architecture By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques This blog post is a continuation of Part 2 , where we cleared the ambiguity around title launch observability at Netflix.

Traffic 180
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Elasticsearch Indexing Strategy in Asset Management Platform (AMP)

The Netflix TechBlog

No matter whether you use in-house deployments or hosted solutions, you can quickly stand up an Elasticsearch cluster, and start integrating it from your application using one of the clients provided based on your programming language (Elasticsearch has a rich set of languages it supports; Java, Python, .Net, Net, Ruby, Perl etc.).

Strategy 264
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Panel Recap: How is your performance and reliability strategy aligned with your customer experience?

Dynatrace

I recently joined two industry veterans and Dynatrace partners, Syed Husain of Orasi and Paul Bruce of Neotys as panelists to discuss how performance engineering and test strategies have evolved as it pertains to customer experience. Then, using a design thinking process , ideate on the future and establish the business vision.

Strategy 245
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Real World Programming with ChatGPT

O'Reilly

This post is a brief commentary on Martin Fowler’s post, An Example of LLM Prompting for Programming. There’s a lot of excitement about how the GPT models and their successors will change programming. First, note the overall strategy Xu Hao uses to write this code. He is using a strategy called “Knowledge Generation.”

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Its design prioritizes high availability and efficient data transfer with minimal overhead, making it a practical choice for handling real-time data pipelines and distributed event processing.

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Where programming languages are headed in 2020

O'Reilly

As we enter a new decade, we asked programming experts?—including Will the incremental strategy of delivering pattern matching and algebraic data types ( Project Amber ) pay off? We checked in with Jim Blandy , coauthor of Programming Rust , to see how his vision of Rust’s progress changed over the course of 2019.