We don’t typically announce new SPM, Logsene, or Search Analytics releases, but yesterday’s release calls for an exception. Logsene release deserves its own post, so we’ll post that separately. For a quick rundown you can jump over to SPM Changelog. This blog has a bit more descriptive info.
The most visible change in SPM is the whole new, much more modern UI based on Bootstrap. Yes, we have designer(s) on our team now! You can now much more seamlessly switch between your SPM, Logsene, and Search Analytics apps and the whole experience should feel a lot smoother. Dashboards were previously fairly hidden, but should now gain visibility. The “Common” part of SPM, Logsene, and Search Analytics, what we internally call “SUA”, has been radically changes to make navigation much simpler. While we’ve made lots of UI/UX changes in this release, you’ll see us improving the UI/UX going forward, too. Please tell us (e.g. leave a comment here) what you think about the new UI, good and bad stuff, and tell us what sort of user experience you’d like to get from SPM! While the new UI is impossible to miss, there is more in this release:
- We’ve expanded SPM integration to Redis and Apache Storm. SPM can now monitor both Redis and Storm and alert you on any of their metrics. This is in addition to monitoring Solr and SolrCloud, Elasticsearch, Hadoop, HBase, Kafka, ZooKeeper, Sensei, JVM, System, and Custom metrics. Don’t forget to tell us what you want to monitor!
- More security-sensitive SPM users asked if they could hide their hostnames, which led to the new hostname aliasing/obfuscation feature. See Can hostnames in SPM be obfuscated or customized? in SPM FAQ. This is really handy not only because it avoids sending hostnames over the network, but because it lets you specify nice, user-friendly nicknames/aliases for them, so you know which host is which in SPM.
- When we announced Algolerts a couple of months ago we pointed out a few known kinks. We’ve taken care of a couple of them in this release. This boils down to being smart about recognizing regular metric variations and not confusing them with actual anomalies, as well as not missing anomalies that were until now masked by preceding anomalous patterns.
- We’ve improved the SPM Client, which now loads in a separate classloader from the application in monitors when launched in embedded mode. This avoids any potential conflicts between libraries included in the SPM Client and those loaded in the monitored application’s process.
If you enjoy performance monitoring, log analytics, or search analytics, working with projects like Elasticsearch, Solr, HBase, Hadoop, Kafka, Storm, we’re hiring planet-wide!