The potential value of migrating to the cloud has inspired many organizations to transition their on-premises big data platforms to a cloud-based platform. Although it seems obvious to migrate big data workloads away from the on-premises data center to the cloud, simply moving your application does not necessarily ensure that your organization can immediately reap the benefits.
When it comes to overseeing large complex systems supporting big data applications, the cloud presents a very different operational and management paradigm than a fully on-premises implementation. Even when engineers experienced with systems management relearn techniques for monitoring and troubleshooting cloud-based applications, it is clear there is no way to manually mitigate emerging risks.
In this webinar, we consider key aspects of cloud system observability and management, including cost management, ensuring compliance with agreed service-level agreements (SLAs), and balancing cloud resource usage to optimize performance. Attendees will learn about:
- The concept of observability for overseeing cloud-based big data applications
- Efficiently and autonomously optimizing big data environments at scale
- Automating performance analysis to help identify performance issues
- Determining where system complexity introduces congestion and bottlenecks that impact observing SLAs
- Understanding cloud service use and optimizing cloud service costs