Operations | Monitoring | ITSM | DevOps | Cloud

For over a decade, Amazon RDS (Relational Database Service) has been a popular managed database service companies have used to set up, operate, and scale databases for web and mobile applications. However, modern, high-scale applications can have upward of tens of thousands of clients. This means that maintaining direct connections between the database and application can quickly begin to consume more resources than the query executions themselves.

I was recently joined by Chris Yates, Senior Vice President, Managing Director of Data and Architecture at Republic Bank for our webinar, Gain the competitive edge with a monitoring tool. The session sparked an insightful conversation around estate monitoring from the perspective of a Senior VP, and I wanted to share some of the key take-aways.

PlanetScale is a serverless, MySQL-compatible database platform powered by Vitess. PlanetScale handles database scaling while also providing you with the tools to increase your development velocity, such as branching, non-blocking schema changes, automatic backups, built-in connection pooling, as well as a helpful interface and CLI. Datadog’s new integration gives you deep visibility into your PlanetScale databases, so you can optimize your usage and costs.

At this point in my career, I’ve realized the responsibilities of database administrators (DBAs) and database reliability engineers (DBREs) can differ from company to company, from year to year, and even from quarter to quarter.

Having trouble deploying Kubernetes in a highly available mode and have a backing remote database? This blog is for you. I will explain how to deploy K3s in HA configuration with an external database Postgres. K3s is a certified Kubernetes distribution for IoT and Edge computing. I deployed it on virtual machines in an IBM Z mainframe. Instead of etcd, I choose Postgres as my storage for my K3s clusters. I deployed Postgres in non HA mode.

At Grafana Labs, we’ve seen an increasing number of customers who are scraping hundreds of millions of active time series but need a solution to reliably store and query such a huge amount of data. So in March, we announced our new open source TSDB, Grafana Mimir, the most scalable, most performant open source time series database in the world.

Today, we are excited to announce that the MySQL integration has received an important update, which includes a new pre-built MySQL logs dashboard and the Grafana Agent configuration to view and collect MySQL server logs. The integration is already available in Grafana Cloud, our platform that brings together all your metrics, logs, and traces with Grafana for full-stack observability.

MongoDB is a document-oriented and cross-platform database that maintains its documents in the binary encoded JSON format. Mongo’s replication capabilities and horizontal capability using sharding make MongoDB highly available. An effective monitoring solution can make it easier for you to identify issues with MongoDB such as resource availability, execution slowdowns, and scalability. observIQ recently built and contributed a MongoDB metric receiver to the OpenTelemetry contrib repo.