Here's the question of the hour. Can you use serverless Elasticsearch or OpenSearch effectively at scale, while keeping your budget in check? The biggest historical pain points around Elasticsearch and OpenSearch are their management complexity and costs. Despite announcements from both Elasticsearch and OpenSearch around serverless capabilities, these challenges remain. Both of these tools are not truly serverless, let alone stateless, hiding their underlying complexity and passing along higher management costs to the customer.
Is your organization currently relying on an ELK cluster for log analytics in the cloud? While the ELK stack delivers on its major promises, it isn't the only search and analytics engine - and may not even be your best option for log management. As cloud data volumes grow, ELK monitoring can become too costly and complex to manage. Fast-growing organizations should consider innovative alternatives offering better performance at scale, superior cost economics, reduced complexity and enhanced data access in the cloud.
What is the difference between logs and events in observability? These two telemetry data types are used for different purposes when it comes to exploring your applications and how your users interact with them. Simply put, logs can be used for troubleshooting and root cause analysis, while events can be used to gain deeper application insights via product analytics. Let's review some application telemetry data definitions for context, then dive into the key differences between logs and events and their use cases. Knowing more about these telemetry data types can help you more effectively use them in your observability strategy.
