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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.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.

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How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. Platform engineering: Build for self-service Self-service deployment is a key attribute of platform engineering. “It makes them more productive.

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Enhancing Kubernetes cluster management key to platform engineering success

Dynatrace

Five of the most common include cluster instability, resource and cost management, security, observability, and stress on engineering teams. Engineering teams are overwhelmed with stuff to do.” The post Enhancing Kubernetes cluster management key to platform engineering success appeared first on Dynatrace news.

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Automating Success: Building a better developer experience with platform engineering

Dynatrace

When it comes to platform engineering, not only does observability play a vital role in the success of organizations’ transformation journeys—it’s key to successful platform engineering initiatives. The various presenters in this session aligned platform engineering use cases with the software development lifecycle.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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Perform 2023 Guide: Organizations mine efficiencies with automation, causal AI

Dynatrace

They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. Further, automation has become a core strategy as organizations migrate to and operate in the cloud. What is a data lakehouse?