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Dynatrace launches Databases app to provide DBA insights across all databases

Dynatrace

Maintaining optimal application performance is crucial for businesses, and fast databases are vital in achieving this goal. For an effective approach to database performance, it’s crucial to have a comprehensive overview of all databases, including server-side DBs.

Database 186
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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. Dynatrace users typically use extensions to pull technical monitoring data, such as device metrics, into Dynatrace.

Database 272
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The Ultimate Guide to Database High Availability

Percona

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. This guide provides an overview of what high availability means, the components involved, how to measure high availability, and how to achieve it.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Redis® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health.

Metrics 130
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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus. Named after the Greek god who brought fire down from Mount Olympus, Prometheus metrics have been transforming observability since the project’s inception in 2012. What is Prometheus?

Metrics 180
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases.

Storage 288
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Storage Autoscaling With Percona Operator for MongoDB

Percona

Previously, deploying and maintaining a database usually meant many burdensome chores and repetitive tasks to ensure proper functioning. Today along with their team, we will see how pvc-autoresizer can automate storage scaling for MongoDB clusters on Kubernetes. In our lab we will use AWS EKS with a standard storage class.

Storage 112