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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. Recovery time of the throughput metric.

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Up your quality and agility factor – using automation to build “performance-as-a-self-service”

Dynatrace

For software engineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. One way to apply improvements is transforming the way application performance engineering and testing is done. Here is a shortlist to get you started.

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Forming an Architecture Modernization Enabling Team (AMET)

Strategic Tech

They need a more loosely coupled architecture and empowered teams. The Warehousing Modernization Enabling Team (an AMET) has been established to guide modernization in the Warehousing domain, which consists of 100+ software engineers and a monolithic codebase. As we all know, roadmaps can be controversial.

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Organise your engineering teams around the work by reteaming

Abhishek Tiwari

For instance, if you are fast-growing VC funded e-commerce startup and your number one business priority is multiplying current growth and performing exceptionally well on key financial metrics charted out by your investors. In this model, software architecture and code ownership is a reflection of the organisational model.