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Microservices vs. monolithic architecture: Understanding the difference

Dynatrace

Increasingly, teams release software features more quickly to accommodate customer needs. As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. Data supports this shift from monolithic architecture to microservices approaches. Easier to develop.

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The Benefits of Software Architecture: Hierarchical Digital Twins

ScaleOut Software

Having just concluded participation in another In-Memory Computing Summit , it has become even more clear to me that the key to mainstream adoption of in-memory computing software platforms is architecture — the root of a platform’s value to applications. These priorities tend to push the architecture to the back burner.

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The Benefits of Software Architecture: Hierarchical Digital Twins

ScaleOut Software

Having just concluded participation in another In-Memory Computing Summit , it has become even more clear to me that the key to mainstream adoption of in-memory computing software platforms is architecture — the root of a platform’s value to applications. These priorities tend to push the architecture to the back burner.

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

Dynatrace

Enterprise data stores grow with the promise of analytics and the use of data to enable behavioral security solutions, cognitive analytics, and monitoring and supervision. Why perform exclusion at two points? The underlying software architecture that supports all this data must be secure, as well.

Design 191
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. In practice, standby replicas demand far more resources.

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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Simplify error analytics.

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Connect Fluentd logs with Dynatrace traces, metrics, and topology data to enhance Kubernetes observability

Dynatrace

Output plugins deliver logs to storage solutions, analytics tools, and observability platforms like Dynatrace. While Fluentd solves the challenges of collecting and normalizing Kubernetes events and logs, Kubernetes performance and availability problems can rarely be solved by investigating logs in isolation. Transaction breakdowns.

Metrics 179