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Kubernetes in the wild report 2023

Dynatrace

Modern, cloud-native computing is impossible to separate from containers and Kubernetes adoption. As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes moved to the cloud in 2022. Kubernetes moved to the cloud in 2022.

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Black Friday traffic exposes gaps in observability strategies

Dynatrace

If the mantra in sales is “Always be closing,” the mantra for online retail storefronts is “Always be online.”. Peak loads can overload and crash retailer websites and derail customer interactions. Customer experience has become paramount for retailers, as visitors demand instant responses — especially during times of high volume.

Traffic 197
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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 193
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The value of business events: How IT can increase business agility

Dynatrace

Consider the following business revenue use case: A retail chain wants to boost the average checkout transaction value by encouraging customers to add additional items to their purchase. The Business Analytics documentation covers configuration steps in detail; here we’ll provide an overview. Configuration overview.

Analytics 232
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What is real user monitoring (RUM)?

Dynatrace

Some examples include: Monitoring a retailer’s online catalog to detect any increase in page load times. For example, RUM is often used to measure latency, and the relationship between longer latencies and user disengagement is well documented. Examples of real user monitoring. Measure RUM for mobile and web-based apps.

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Quality Begins Where the User Journey Ends

Apica

In today’s distributed cloud application environments, no matter how many front-end tests an organization runs, there are still infinite ways something could go wrong in front of users. Driving real production-like user behaviors at cloud scale through the system can detect more defects before they can appear in front of customers.

Retail 52
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A case for ELT

Abhishek Tiwari

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. You can also use cloud and SaaS services such as Google BigQuery, Amazon Redshift Spectrum, Amazon Athena, Qubole to implement ELT approach.