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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 180
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AI techniques enhance and accelerate exploratory data analytics

Dynatrace

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 198
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Stream logs to Dynatrace with Amazon Data Firehose to boost your cloud-native journey

Dynatrace

Real-time streaming needs real-time analytics As enterprises move their workloads to cloud service providers like Amazon Web Services, the complexity of observing their workloads increases. Log data—the most verbose form of observability data, complementing other standardized signals like metrics and traces—is especially critical.

Cloud 240
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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. The pair showed how to track factors including developer velocity, platform adoption, DevOps research and assessment metrics, security, and operational costs.

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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.

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

Dynatrace

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. By analyzing patterns and trends, predictive analytics helps identify potential issues or opportunities, enabling proactive actions to prevent problems or capitalize on advantageous situations.

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Exploratory analytics and collaborative analytics capabilities democratize insights across teams

Dynatrace

Drowning under endless data? Having access to large data sets can be helpful, but only if organizations are able to leverage insights from the information. These analytics can help teams understand the stories hidden within the data and share valuable insights. and only they have access.” and only they have access.”

Analytics 189