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

Dynatrace

This example shows that the checkout function running in the EU-Central-1 region processes between 20 and 80 invocations per minute. 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. and Python.

Lambda 345
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Dynatrace elevates data security with separated storage and unique encryption keys for each tenant

Dynatrace

Protect data in multi-tenant architectures To bring you the most value by unifying observability and security in one analytics and automation platform powered by AI, Dynatrace SaaS leverages a multitenancy architecture, enabling efficient and scalable data ingestion, querying, and processing on shared infrastructure.

Storage 246
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Dynatrace achieves Google Cloud Ready – Cloud SQL designation

Dynatrace

Dynatrace has announced that it has successfully achieved the Google Cloud Ready – Cloud SQL designation for Cloud SQL, Google Cloud’s fully-managed, relational database service for MySQL, PostgreSQL, and SQL Server. This designation can also save time in evaluating Dynatrace solutions for organizations that are not already using them.

Google 246
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Data privacy by design: How an observability platform protects data security

Dynatrace

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 246
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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. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is Apache Kafka?

Latency 147
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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. Data is then dynamically routed into pipelines for further processing.

Analytics 272
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The End of Programming as We Know It

O'Reilly

It is not the end of programming. It is the end of programming as we know it today. Assembly language programming then put an end to that. Betty Jean Jennings and Frances Bilas (right) program the ENIAC in 1946. There were more programmers, not fewer This was far from the end of programming, though. I dont buy it.