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Visualizing IoT Data With MQTT, QuestDB, and Grafana

DZone

Monitoring Time-Series IoT Device Data Time-series data is crucial for IoT device monitoring and data visualization in industries such as agriculture, renewable energy, and meteorology. It enables trend analysis, anomaly detection, and predictive analytics, empowering businesses to optimize performance and make data-driven decisions.

IoT 241
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Sustainable IT: Optimize your hybrid-cloud carbon footprint

Dynatrace

A structured approach Reducing carbon emissions involves a combination of technology, practice, and planning. If you’re running your own data center, you can start powering it with green energy purchased through your utility company. The complication with this approach is that your energy bill will likely increase. A PUE of 1.0

Cloud 205
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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

Companies now recognize that technologies such as AI and cloud services have become mandatory to compete successfully. AI-enabled chatbots can help service teams triage customer issues more efficiently. As organizations adopt more AI technologies, the associated costs are skyrocketing. What is explainable AI?

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Microsoft Ignite 2023 guide: AI transformation and Microsoft Azure

Dynatrace

Indeed, AI is revolutionizing our world, driving rapid innovation, and transforming how we engage with technology personally and professionally. To keep up, organizations are making significant investments to harness this technology and unlock new opportunities to thrive in the era of AI with Microsoft Azure and adjacent technologies.

Azure 130
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Implementing AWS well-architected pillars with automated workflows

Dynatrace

This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

AWS 243
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. But energy consumption isn’t limited to training models—their usage contributes significantly more. Building LLMs consumes vast amounts of electricity and generates substantial heat.

Cache 201
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Observations on the Importance of Cloud-based Analytics

All Things Distributed

AWS is enabling innovations in areas such as healthcare, automotive, life sciences, retail, media, energy, robotics that it is mind boggling and humbling. Many of these innovations will have a significant analytics component or may even be completely driven by it. Cloud analytics are everywhere.

Analytics 135