In the fast-paced universe of software development, especially in the cloud-native realm, DevOps and SRE teams are increasingly emerging as essential partners in application stability and growth. DevOps engineers continuously optimize software delivery, while SRE teams act as the stewards of application reliability, scalability, and top-tier performance. The challenge?

In the fast-paced universe of software development, especially in the cloud-native realm, DevOps and SRE teams are increasingly emerging as essential partners in application stability and growth. DevOps engineers continuously optimize software delivery, while SRE teams act as the stewards of application reliability, scalability, and top-tier performance. The challenge?

Google Cloud Platform (GCP) offers a wide range of features to support their core deliverable, highly available and scalable infrastructure-as-a-service. One of the features—GCP’s log management and available via GCP Log Explorer— is offered to support customers’ basic logging requirements.

In this tutorial, you’ll see how to deploy Solr on Kubernetes. You’ll also see how to use the Solr Operator to autoscale a SolrCloud cluster based on CPU with the help of the Horizontal Pod Autoscaler. Let’s get going! 🙂

Logs serve as an invaluable resource for monitoring system health, debugging issues, and maintaining security. But as our applications grow more complex, the volume of logs they generate is increasing exponentially. While logs are crucial, not all log data is equally valuable. With the surge in volume, costs associated with storing and analyzing logs are skyrocketing, impacting both performance and cost. The need for effective log management is more urgent than ever.