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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 199
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Boost DevOps maturity with observability and a data lakehouse

Dynatrace

That’s especially true of the DevOps teams who must drive digital-fueled sustainable growth. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. From a technical perspective, however, cloud-based analytics can be challenging.

DevOps 192
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What is log analytics? How a modern observability approach provides critical business insight

Dynatrace

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 223
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DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. Though the industry champions observability as a vital component, it’s become clear that teams need more than data on dashboards to overcome persistent DevOps challenges.

DevOps 228
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. With the help of log monitoring software, teams can collect information and trigger alerts if something happens that affects system performance and health.

Analytics 218
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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 260
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Implementing service-level objectives to improve software quality

Dynatrace

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. When organizations implement SLOs, they can improve software development processes and application performance. SLOs improve software quality. SLOs promote automation. SLOs minimize downtime.

Software 272