BOSTON & TEL AVIV--(BUSINESS WIRE)--Logz.io, the leading cloud-native observability platform for modern DevOps teams, today at the ScaleUP 2020 user conference announced several new open source-based monitoring solutions to complement its unified SaaS platform for log, metrics and tracing analytics. Besides the ground-breaking launch of the Jaeger-based Distributed Tracing solution, Logz.io unveiled Smart Tiering, Alerts Correlation and the new Insights based Exceptions to provide engineers with the flexibility and functionality needed to monitor and troubleshoot production issues faster and more cost effectively.
Logz.io Smart Tiering is a new Log Management capability that allows engineers to decrease logging costs by storing data in different ‘tiers’. The three levels to retain data, Real-time Tier, Smart Tier, and Historical Tier, offer the flexibility to define a data management strategy that divides data based on the desired balance between cost, performance and availability.
The newest product enhancements were announced at ScaleUP 2020 alongside hundreds of Logz.io customers, partners and open source advocates. The event, which served as an interactive forum for the Logz.io community to share technical best practices and use cases around production monitoring, troubleshooting and security, featured presentations from customers such as Dish Network, The Economist, Kaltura, Mediatonic (creators of “Fall Guys”) and more.
“We were thrilled to unveil Distributed Tracing and these other significant updates to our core Log Management platform at ScaleUP,” said Tomer Levy, CEO and Co-founder of Logz.io. “Smart Tiering in particular reflects our commitment to helping customers cut the costs of logging while still achieving high performance and availability.”
New Product Announcements
Smart Tiering: Designed to help customers reduce costs by providing the flexibility to divide data across three different availability and performance tiers.
- Real-time Tier for critical production data, with real-time performance and availability for troubleshooting.
- Smart Tier for active and trending data that isn’t accessed as frequently, but needs the same real-time performance. Designed with reduced data replication and a slightly reduced SLA.
- Historical Tier for historical data, with archival to AWS S3 and/or Azure Blob for compliance needs.
Application Insights - Exceptions
A newly redesigned Exceptions tab is now available in Kibana’s Discover. Exceptions surfaces relevant issues with code execution picked up from log messages to reduce troubleshooting and debugging time. Exceptions is part of Application Insights which uses machine learning (ML) to automatically uncover the most relevant exceptions and error messages
The new Alert Correlation feature enhances advanced threat detection in the Logz.io Cloud SIEM, as well as improves alert accuracy in operations use cases. Alert Correlation enables the notification of users when specific sequences of security events are taking place and indicating critical attacks. With the ability to define multi query alerts, engineers can now receive an alert of a brute force attack followed by a malware download by the same actor. This correlation ensures these critical events are not only visible in isolation.
For more information on the new product announcements made at ScaleUP 2020, visit the Logz.io blog.
Logz.io is the leading cloud-native observability platform that enables engineers to use the best open source tools in the market without the complexity of operating, managing, and scaling them. Logz.io offers four products: Log Management built on ELK, Infrastructure Monitoring based on open source Grafana, Distributed Tracing based on Jaeger, and an ELK-based Cloud SIEM. These are offered as fully managed, integrated cloud services designed to help engineers monitor, troubleshoot and secure their distributed cloud workloads more effectively. Engineering driven companies like Siemens, Turner Broadcasting, and Unity use Logz.io to simplify monitoring and security workflows, increasing developer productivity, reducing time to resolve issues, and increasing the performance and security of their mission-critical applications.