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Site reliability done right: 5 SRE best practices that deliver on business objectives

Dynatrace

How site reliability engineering affects organizations’ bottom line SRE applies the disciplines of software engineering to infrastructure management, both on-premises and in the cloud. However, cloud complexity has made software delivery challenging.

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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

These challenges make AWS observability a key practice for building and monitoring cloud-native applications. Let’s take a closer look at what observability in dynamic AWS environments means, why it’s so important, and some AWS monitoring best practices. What is AWS observability? And why it matters.

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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. Adoption of GitOps practices enables platform provisioning at scale.

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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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The State of DevOps Automation assessment: How automated are you?

Dynatrace

In response to the scale and complexity of modern cloud-native technology, organizations are increasingly reliant on automation to properly manage their infrastructure and workflows. It addresses the extent to which an organization prioritizes automation efforts, including budgets, ROI models, standardized best practices, and more.

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Application observability meets developer observability: Unlock a 360º view of your environment

Dynatrace

Cloud complexity and data proliferation are two of the most significant challenges that IT teams are facing today. Modern cloud complexity is becoming nearly impossible for human beings to manage without AI and automation. The challenges that developers face with modern cloud environments are myriad.

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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.