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.

Do you love reading about how various performance-related issues are traced out and fixed? If so, here's our story of how we fixed the Redis performance issues we were facing by optimizing JedisPool. We hope this will help you strengthen your IT environment. Our Redis performance issues and efforts to find the cause

This is the third part of my DevOps 101 series, so before we get going, let’s do a quick recap of what we’ve covered previously In DevOps 101: What, who, why, and how, I talked about how the definition from Microsoft’s Donovan Brown encapsulates DevOps succinctly as: The union of people, process, and products, to enable the continuous delivery of value to the end users.

With Cloud SQL for SQL Server, you can bring your existing SQL Server on-premises workloads to Google Cloud. Cloud SQL takes care of infrastructure, maintenance, and patching so you can focus on your application and users. A great way to take better care of your application is by monitoring the SQL Server error log for issues that may be affecting your users such as deadlocks, job failures, and changes in database health.

When looking for a highly scalable time series database, there are a number of criteria to investigate and evaluate. First up, it’s always a good idea to consider open source software. It’s more likely to have gone through comprehensive troubleshooting, it’s typically more reliable as it has more timely and widespread peer-review, it better guarantees technology independence, it’s easier to find engineers who are familiar with it and it has great security.