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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 214
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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 181
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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 187
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Perform 2023 Guide: Organizations mine efficiencies with automation, causal AI

Dynatrace

In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

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Fueling the next wave of IT operations: Modernization with generative AI

Dynatrace

Teams require innovative approaches to manage vast amounts of data and complex infrastructure as well as the need for real-time decisions. Grail, alongside Dynatrace Davis AI, enables organizations to move beyond simple event correlation and to identify the root cause of problems in their applications and infrastructure.

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

Dynatrace

‘Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Causal AI is critical to feed quality data inputs to the algorithms that underpin generative AI.

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RSA Guide 2023: Cloud application security remains core challenge for organizations

Dynatrace

Observability is critical for monitoring application performance, infrastructure, and user behavior within hybrid, microservices-based environments. This includes collecting metrics, logs, and traces from all applications and infrastructure components.

Cloud 186