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Driving your FinOps strategy with observability best practices

Dynatrace

In response, many organizations are adopting a FinOps strategy. Following FinOps practices, engineering, finance, and business teams take responsibility for their cloud usage, making data-driven spending decisions in a scalable and sustainable manner.

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The top four log analytics and log management best practices

Dynatrace

By following key log analytics and log management best practices, teams can get more business value from their data. Challenges driving the need for log analytics and log management best practices As organizations undergo digital transformation and adopt more cloud computing techniques, data volume is proliferating.

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MySQL Backups: Methods & Best Practices

Scalegrid

Key Takeaways Understanding the range of MySQL backup types and strategies is essential for optimal data security and efficiency, including full, incremental, differential, and partial backups, each with its advantages and use cases. Choosing the right backup strategy for your MySQL databases will depend on your needs and resources.

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Best Practices in Cloud Security Monitoring

Scalegrid

This article strips away the complexities, walking you through best practices, top tools, and strategies you’ll need for a well-defended cloud infrastructure. Get ready for actionable insights that balance technical depth with practical advice.

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Pivoting to a total experience strategy: A necessity for governments today

Dynatrace

Citizens need seamless digital experiences, which is why the concept of a total experience (TX) strategy is gaining traction among government institutions. A TX strategy is an innovative approach that seeks to overhaul the traditional paradigms of public service delivery. Everything impacts and influences each other.

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Offline Data Pipeline Best Practices Part 1:Optimizing Airflow Job Parameters for Apache Hive

DZone

Welcome to the first post in our exciting series on mastering offline data pipeline's best practices, focusing on the potent combination of Apache Airflow and data processing engines like Hive and Spark. However, they can become a source of increased costs and inefficiencies without the right optimization strategies.

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Why growing AI adoption requires an AI observability strategy

Dynatrace

As organizations turn to artificial intelligence for operational efficiency and product innovation in multicloud environments, they have to balance the benefits with skyrocketing costs associated with AI. An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance.

Strategy 221