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How observability, application security, and AI enhance DevOps and platform engineering maturity

Dynatrace

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.

DevOps 187
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Boost DevOps maturity with observability and a data lakehouse

Dynatrace

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. Cost and capacity constraints for managing this data are becoming a significant burden to overcome.

DevOps 180
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What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

Technology and operations teams work to ensure that applications and digital systems work seamlessly and securely. They handle complex infrastructure, maintain service availability, and respond swiftly to incidents. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data.

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DevOps engineer tools: Deploy, test, evaluate, repeat

Dynatrace

As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows. ” What does a DevOps platform engineer do? A DevOps platform engineer is a more recent term.

DevOps 187
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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

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9 key DevOps metrics for success

Dynatrace

You have set up a DevOps practice. As we look at today’s applications, microservices, and DevOps teams, we see leaders are tasked with supporting complex distributed applications using new technologies spread across systems in multiple locations. DevOps metrics to help you meet your DevOps goals.

DevOps 196
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Path to NoOps part 2: How infrastructure as code makes cloud automation attainable—and repeatable—at scale

Dynatrace

Infrastructure as code is a way to automate infrastructure provisioning and management. In this blog, I explore how Dynatrace has made cloud automation attainable—and repeatable—at scale by embracing the principles of infrastructure as code. And it’s a crucial step toward achieving cloud automation on the path to NoOps.