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Extend business observability: Extract business events from online databases (Part 2)

Dynatrace

In part 2, we’ll show you how to retrieve business data from a database, analyze that data using dashboards and ad hoc queries, and then use a Davis analyzer to predict metric behavior and detect behavioral anomalies. Similar to the tutorial extension, we created an extension that performs queries against databases.

Database 277
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Why Choose a Third-Party Database Migration Service

Percona

Sure, database migration is complex, particularly when you’re looking to migrate from a proprietary database to an open source one. Database migration is almost always time-consuming, tedious, and full of potential pitfalls. Database migration is complex Let’s start here. What’s your documentation plan?

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JSON and Relational Databases – Part One

Percona

JSON data and relational databases have traditionally been diametric opposites. So many folks were surprised when relational databases started adding a JSON data type to their products. In this multi-part blog series, we will start with an overview of using JSON in a relational database. JSON is popular. Very popular.

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Mastering Kubernetes deployments with Keptn: a comprehensive guide to enhanced visibility

Dynatrace

In this article, we’ll explore these challenges in detail and introduce Keptn, an open source project that addresses these issues, enhancing Kubernetes observability for smoother and more efficient deployments. External dependencies Many applications rely on external services, such as databases, APIs, or third-party services.

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The right person at the right time makes all the difference: Best practices for ownership information

Dynatrace

As teams and their structure and metadata are often maintained in a dedicated database, such as Microsoft Entra ID (formerly Azure Active Directory) or ServiceNow. A dedicated workflow allows automatic synchronization of the database information with Dynatrace and keeps the ownership team information up-to-date.

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An Efficient Object Storage for JUnit Tests

DZone

There are several limitations to store and fetch such data (all restrictions could be found in official documentation ). It's still not possible to continue using light-weighted databases such as HSQL or H2 to implement tests. To resolve the problem it was suggested to find more suitable data storage.

Storage 124
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MongoDB Rollback: How to Minimize Data Loss

Scalegrid

For example, memory-resident databases without persistent disks, such as Redis cluster setups or Apache Spark installations, rely on stand-alone machines. To traditional relational databases, where rollbacks are less likely to cause data loss, MongoDB differs significantly.

Database 130