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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 latency p90.

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Site Reliability Engineering

DZone

Originating from the complex operational challenges faced by large internet companies, SRE incorporates aspects of software engineering and applies them to infrastructure and operations problems.

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Software engineering for machine learning: a case study

The Morning Paper

Software engineering for machine learning: a case study Amershi et al., More specifically, we’ll be looking at the results of an internal study with over 500 participants designed to figure out how product development and software engineering is changing at Microsoft with the rise of AI and ML. ICSE’19.

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Auto-adaptive thresholds for AI-driven quality gating

Dynatrace

Build an umbrella for Development and Operations In modern software engineering, the discipline of platform engineering delivers DevSecOps practices to developers to bridge the gaps between development, security, and operations and enhance the developer experience.

Metrics 219
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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can come join us.

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Automated observability, security, and reliability at scale

Dynatrace

While infrastructure has historically been treated as a bottleneck where proper scaling and compute power are applied to improve performance, these aspects are now typically addressed by hyperscalers that offer cloud-based infrastructure and infrastructure as a service.

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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. They enable IT teams to identify and address the precise cause of application and infrastructure issues.

Analytics 177