Challenges and Recommendations for Cloud Data Analytics and Monitoring
The transition to cloud-based applications appears unstoppable. However running applications through a cloud service provider such as Amazon Web Services or Microsoft Azure creates a number of security challenges not seen in on premise deployments. This report will review some of the challenges that create issues with monitoring cloud data analytics, followed by several recommendations for coping them.
The most fundamental activity for cloud security monitoring and response is the collection and analysis of data analytics. Every compliance regulation requires this activity in some form, and for good reason. Therefore any organization moving to the cloud needs to understand how the environment will change with respect to logs and data analytics.
Our first reported challenge, involves the ephemeral nature of assets within cloud data analytics. Compared with data analytics in the cloud, data analytics for on-premises infrastructure and applications are relatively static. In fact, most IT shops avoid changes whenever possible, fearing that a seemingly minor change might cause an outage, for example by breaking a script everyone had forgotten about. This makes it easy to use these static definitions for security, for example in firewall rule tables or log correlation to critical assets. This is unlike a cloud service, who's assets are ephemeral, meaning constantly changing, and hard to track.
Get the complete report, and read all 5 challenges, as well as recommendations to cloud monitoring.