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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 227
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 179
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Reimagining Experimentation Analysis at Netflix

The Netflix TechBlog

After recreating the dataset, you can plot the raw numbers and perform custom analyses to understand the distribution of the data across test cells. With our new platform for experimentation analysis, it’s easy for scientists to perfectly recreate analyses on their laptops in a notebook.

Metrics 215
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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

Software automation enables digital supply chain stakeholders — such as digital operations, DevSecOps, ITOps, and CloudOps teams — to orchestrate resources across the software development lifecycle to bring innovative, high-quality products and services to market faster. What is software analytics? The post What is software automation?

Software 180
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Path to NoOps part 1: How modern AIOps brings NoOps within reach

Dynatrace

The need for developers and innovation is now even greater. Organizations would still need a skeletal staff that can focus on innovation and oversee exception-based operations. By greatly reducing the effort required by the operations side of the equation, teams have more time to innovate and optimize processes.

DevOps 210
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Seven benefits of AIOps to transform your business operations

Dynatrace

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

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Applying real-world AIOps use cases to your operations

Dynatrace

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. This second solution picks up at data collection, aggregation, and analysis, preparing it for execution. Deterministic AI.

DevOps 189