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New integrations announced at AWS re:Invent enhance cloud performance, security, and automation

Dynatrace

This seamless integration accelerates cloud adoption, allowing enterprises to maximize the value of their AWS infrastructure and focus on innovation rather than managing observability configurations. Dynatrace, OneAgent, and the Dynatrace logo are trademarks of the Dynatrace, Inc. group of companies.

AWS 298
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Foundation Model for Personalized Recommendation

The Netflix TechBlog

It facilitates the distribution of these learnings to other models, either through shared model weights for fine tuning or directly through embeddings. In NLP, the trend is moving away from numerous small, specialized models towards a single, large language model that can perform a variety of tasks either directly or with minimal fine-tuning.

Tuning 200
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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

However, this category requires near-immediate access to the current count at low latencies, all while keeping infrastructure costs to a minimum. Eventually Consistent : This category needs accurate and durable counts, and is willing to tolerate a slight delay in accuracy and a slightly higher infrastructure cost as a trade-off.

Latency 251
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Monitoring of Kubernetes Infrastructure for day 2 operations

Dynatrace

One of the promises of container orchestration platforms is to make i t easier for the developers to accelerate the deployment of their app lication s without having to worry about scalability and infrastructure dependencies. In your monitoring strategy, you need to consider a comprehensive , single-pane of glass, approach: ? .

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

This approach provides a few advantages: Low burden on existing systems: Log processing imposes minimal changes to existing infrastructure. Stay tuned for a closer look at the innovation behind thescenes! This allows us to focus on data analysis and problem-solving rather than managing complex systemchanges.

Traffic 172
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

With its exchange feature, RabbitMQ enables advanced routing strategies, making it well-suited for workflows that require controlled message flow and guaranteed delivery. Optimizing RabbitMQ requires clustering, queue management, and resource tuning to maintain stability and efficiency.

Latency 147