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Automatic and intelligent end-to-end observability for OpenTelemetry Java

Dynatrace

Oftentimes, this involves the integration of OpenTelemetry data that’s used during development into production workflows. Today, Dynatrace is happy to announce OneAgent support for discovering and automatically capturing OpenTelemetry trace data for Java. Dynatrace and OpenTelemetry work better together. Nano HTTPD ?(instead

Java 159
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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

already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. and focusing on a much-improved version 2.0 Extensions 2.0

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Mastering MongoDB® Timeout Settings

Scalegrid

How the MongoDB timeout is set up can significantly affect your application’s performance, no matter if you are an experienced MongoDB user or just starting with NoSQL databases. Typical applications are interacting with different database servers based on the business logic. x+ in Java).

Java 130
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RSA Guide 2023: Cloud application security remains core challenge for organizations

Dynatrace

The focus on bringing various organizational teams together—such as development, business, and security teams — makes sense as observability data, security data, and business event data coalesce in these cloud-native environments. As organizations develop new applications, vulnerabilities will continue to emerge.

Cloud 192
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Scalable Annotation Service?—?Marken

The Netflix TechBlog

All data should be also available for offline analytics in Hive/Iceberg. A data model in Marken can be described using schema — just like how we create schemas for database tables etc. Unlike Java, we support multiple inheritance as well. The databases we pick should be able to scale horizontally.

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Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

Production Use Cases Real-Time APIs (backed by the Cassandra database) for asset metadata access don’t fit analytics use cases by data science or machine learning teams. For fast processing of the events, we use different settings of Kafka consumer and Java executor thread pool.

Media 237
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Our tactical approach was to use Netflix-specific libraries for collecting traces from Java-based streaming services until open source tracer libraries matured. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment.