We are (so!) excited to announce that Loom 2.2 is now available for our customers.
As we gradually rolling out the deployment of this version to all of our customers, we would like to take this opportunity and elaborate on the key features of this version and tell you more about some of our esciting features.
You asked for it and we listened!
Starting from this version, it is now possible to create customized visualizations and dashboards within Loom.
Visualizations are a great way to understand and monitor your data, especially when grouped together into a dashboard. Built upon the fields extracted by Loom from your logs, you can easily create dashboards that will represent any aspect of the data, rather it be breakdown of specific fields (http status codes, for example), geographical distribution of your data, or trends over time of specific fields (failed login attempts, for instance). You can now define and share with your team the best visualization of your data using Loom.
Just as a reminder, in addition to Loom’s anomaly detection engine, it was always possible to perform a deeper investigation of any incident within Loom, using the Analytics screen. Using an embedded production-ready Kibana, our users could zoom-in directly from an incident as a whole to the log line or time frame of interest in one click.
On top of this, it is now possible to save your queries and create customized dashboards, all within Loom’s analytics screen. Take a look:
We’ve put a lot of emphasis in helping our customers discover the “unknowns” in their IT stack using Loom’s anomaly detection engine. But what about the things you already know? Or better yet, the things discovered by Loom and now you want to make sure you keep track of? As of this version, it is possible to manually define Custom Alerts, using Lucene query syntax.
This new feature helps you do more with your Loom. You can make your Loom even smarter with 'Custom Alerts' by using simple and intuitive conditional statements:
After slicing and dicing the data in the Analytics screen, and once you have your query ready, just click “Custom Alerts” and Loom will automatically open for you a short form in which you’ll be able to define the threshold for the query and save it as an alert.
Alerts can be defined for every field extracted by Loom, and the syntax allows maximum flexibility when defining the query itself (AND, NOT, OR sequences, ranges, regular expressions and more).
Once created, Loom will monitor the defined metric or metrics 24/7 and will display them in the event feed, as with any other Loom alert.
Loom Collector for Linux servers
Shipping data from your servers can be a tedious task. This is why we developed our collector for Linux servers. Loom collector is using your pre-existing Rsyslog (so no additional agent needs to be installed) to automatically locate and ship log files from your server to Loom. With this collector we aim at reducing the amount of manual work related to getting the data into Loom.
Last but not least, as part of Loom operational excellence approach it is natural for Loom to ensure flawless alerting and effective incident collaboration. As of today, it is possible to get notified about Loom alerts and incidents through PagerDuty, HipChat, Amazon SNS, OpsGenie and SNS++. Loom ensures that the right people on your team get alerted and can resolve incidents before they become emergencies. By adding these, on top of the already existing webhook, Slack and Email integrations, Loom now have native integration with all of the major notification systems.
That's it for now, folks, we're already working on the next big thing.
Coming next: Loom 2.3 is just around the road, with a few new exciting features. Stay tuned!
Loom Systems delivers an AIOps-powered log analytics solution, Sophie,
to predict and prevent problems in the digital business. Loom collects logs and metrics from the entire IT stack, continually monitors them, and gives a heads-up when something is likely to deviate from the norm. When it does, Loom sends out an alert and
recommended resolution so DevOps and IT managers can proactively attend to the issue before anything goes down.
Get Started with AIOps Today!