Elastic Observability provides a full-stack observability solution, by supporting metrics, traces, and logs for applications and infrastructure. In a previous blog, I showed you how to monitor your AWS infrastructure running a three-tier application. Specifically we reviewed metrics ingest and analysis on Elastic Observability for EC2, VPC, ELB, and RDS.

Does your organization’s data include sensitive information, like intellectual property or personally identifiable information (PII)? Do you want to protect your data from being stolen and sent (i.e., exfiltrated) to external web services? If the answer to these questions is yes, then Elastic’s Data Exfiltration Detection package can help you identify when critical enterprise data is being stolen and exfiltrated.

Unlock the full potential of your observability stack with continuous profiling Identifying performance bottlenecks and wasteful computations can be a complex and challenging task, particularly in modern cloud-native environments. As the complexity of cloud-native environments increases, so does the need for effective observability solutions.

In an earlier blog post, Log monitoring and unstructured log data, moving beyond tail -f, we talked about collecting and working with unstructured log data. We learned that it’s very easy to add data to the Elastic Stack. So far the only parsing we did was to extract the timestamp from this data, so older data gets backfilled correctly. We also talked about searching this unstructured data toward the end of the blog.