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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. Dynatrace Extensions 1.0 Extensions 2.0

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

As an example, many retailers already leverage containerized workloads in-store to enhance customer experiences using video analytics or streamline inventory management using RFID tracking for improved security. ActiveGate acts as a secure proxy and compresses and routes observability signals in an optimized manner to Dynatrace servers.

Retail 257
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Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

Resource consumption: Observing computational resource availability and saturation, whether deployed in cloud-native environments like Kubernetes or CPU-enabled servers. Dynatrace OneAgent® is perfectly capable of automatically injecting and tracing code-level information for many technologies, such as Java,NET, Golang, and NodeJS.

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Mastering MongoDB® Timeout Settings

Scalegrid

On an abstract level, whenever you use MongoClient to connect, send, or receive a request, it internally uses predefined timeout options to decide how long the application will wait for an initial connection establishment or the response from the server for your request.

Java 130
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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. Java applications use a similar mechanism.).

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. Java applications use a similar mechanism.).

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Leverage automated and intelligent observability for OpenTelemetry for Go with Dynatrace PurePath 4

Dynatrace

Such additional telemetry data includes user-behavior analytics, code-level visibility, and metadata (including open-source data). PurePath 4 integrates OpenTelemetry Go data for enterprise-grade collection and contextual AI analytics. TCP Server. // Start TCP server. listener, _ := net.Listen("tcp", ":1234").

Traffic 165