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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. We designed experimental scenarios inspired by chaos engineering.

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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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Unlock the Power of DevSecOps with Newly Released Kubernetes Experience for Platform Engineering

Dynatrace

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Automation, automation, automation.

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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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How to leverage mobile analytics to ensure crash-free, five-star mobile applications

Dynatrace

Mobile analytics can help organizations optimize their mobile application performance, earning customer accolades and increasing revenue in the process. Learn how one Dynatrace customer leveraged mobile analytics to ensure a crash-free, five-star mobile application. Add instrumentation and validate incoming mobile analytics data.

Mobile 217
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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Check back here throughout the event for the latest news, insights, and announcements.

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Autonomous Cloud Enablement aka Scaling NoOps via Self-Service

Dynatrace

At Dynatrace, we have been very proud and vocal about our own DevOps transformation story that we started when we incubated what is now known as the Dynatrace Software Intelligence Platform (formerly Ruxit). Over the years we have seen three major waves of evolution for us: Speed, Stability and Scale. Autonomous Cloud with Dynatrace.

Cloud 184