Elasticsearch (ES) is a powerful tool offering multiple search, content, and analytics capabilities. You can extend its capacity and relatively quickly horizontally scale the cluster by adding more nodes. When data is indexed in some Elasticsearch index, the index is not typically placed in one node but is spread across different nodes such that each node contains a “shard” of the index data. The shard (called primary shard) is replicated across the cluster into several replicas.

Businesses are increasingly adopting distributed microservices to build and deploy applications. Microservices directly streamline the production time from development to deployment; thus, businesses can scale faster. However, with the increasing complexity of distributed services comes visual opacity of your systems across the company. In other words, the more complex your system gets, the harder it becomes to visualize how it works and how individual resources are allocated.

We will focus on the audit logging of Google cloud itself, however, the input supports the below sources when it refers to Google Cloud Logs.

At the beginning of every successful data exploration journey, a query is constructed. So, with this latest Grafana release, we are proud to introduce several new features aimed at improving the Grafana Loki querying experience. From query expression validation to seeing the query history in code editor and more, these updates are sure to make querying in Grafana even more efficient and intuitive, saving you time and frustration.

If you’re in the cloud engineering and DevOps space, you’ve probably seen the name OpenSearch a lot over the last couple of years. But, what is your current understanding of OpenSearch, and the components around it? Let’s take a closer look.

Any software application or a system can have bugs and issues in testing or production environments. Therefore, logging is essential to help troubleshoot issues easily and introduce fixes on time. However, logging is useful only if it provides the required information from the log messages without adversely impacting the system’s performance. Traditionally, implementing logging that satisfies these criteria in Java applications was a tedious process.