Log Analytics for ITOps, DevOps, & CloudOps

Presented by

Kevin Petrie, VP of Research at Eckerson Group and Thomas Hazel, CTO and Founder at ChaosSearch

About this talk

Log analytics can help by providing visibility into the intricate workings of IT components. ITOps, DevOps, and CloudOps engineers can use log analytics to ensure their IT environments meet the rigorous demands of the business. But you need the right log analytics tool to achieve these objectives. View this Webinar to learn: * Objectives, functionality, and use cases for ITOps, DevOps, and CloudOps * How log analytics supports these "ops" disciplines * Questions to address as you evaluate and compare log analytics tools The modern IT organization struggles to manage competing priorities. While ITOps engineers need to stabilize and control their growing environments, DevOps engineers need to accelerate application releases. CloudOps engineers seek to achieve both those goals as they move to cloud platforms, but still must integrate with persistent on-premises systems. This webinar explores why log analytics matters, and will define criteria by which you can evaluate log analytics solutions, including analytical flexibility, ease of use, performance, scalability, and open interoperability — as well as its implications for other types of management tools in your environment.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (13)
Subscribers (665)
ChaosSearch helps modern organizations Know Better™ by activating the data lake for analytics. The ChaosSearch Data Lake Platform indexes customers’ cloud data, rendering it fully searchable and enabling analytics at scale with massive reductions of time, cost and complexity. ChaosSearch was purpose-built for cost-effective, highly scalable analytics encompassing full text search, SQL and machine learning capabilities in one unified offering. The patented ChaosSearch technology instantly transforms your cloud object storage (Amazon S3, Google Cloud Storage) into a hot, analytical data lake.