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Dynatrace elevates data security with separated storage and unique encryption keys for each tenant

Dynatrace

Enhancing data separation by partitioning each customer’s data on the storage level and encrypting it with a unique encryption key adds an additional layer of protection against unauthorized data access. Such infrastructures must implement additional controls to securely separate each customer’s data.

Storage 246
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New continuous compliance requirements drive the need to converge observability and security

Dynatrace

In dynamic and distributed cloud environments, the process of identifying incidents and understanding the material impact is beyond human ability to manage efficiently. Configuration and Compliance , adding the configuration layer security to both applications and infrastructure and connecting it to compliance.

Analytics 289
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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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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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Dynatrace Cost & Carbon Optimization certified for accuracy and transparency

Dynatrace

This is partly due to the complexity of instrumenting and analyzing emissions across diverse cloud and on-premises infrastructures. Integration with existing systems and processes : Integration with existing IT infrastructure, observability solutions, and workflows often requires significant investment and customization.

Energy 223
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OpenPipeline: Simplify access to critical business data

Dynatrace

Track business metrics, key performance indicators (KPIs), and service level objectives (SLOs) — automatically and in context with IT infrastructure and services — to promote collaboration between business and IT teams. Reduced storage and query overhead for business use cases. Simplified and enhanced analytics efficiency.

Analytics 241
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

Kafka scales efficiently for large data workloads, while RabbitMQ provides strong message durability and precise control over message delivery. Message brokers handle validation, routing, storage, and delivery, ensuring efficient and reliable communication. What is RabbitMQ?

Latency 147