New Capability Uses Sophisticated Machine Learning Algorithms to Detect and Alert Customers When Cloud Resource Provisioning Deviates from the Norm
BOSTON – June 26, 2017 – FittedCloud, a leading provider of cost management solutions for Amazon Web Services (AWS) powered by machine learning, today announced a new anomaly detection capability. The new capability is included in FittedCloud’s cost optimization offerings for EBS, EC2, and DynamoDB and alerts customers of any abnormal changes to resource provisioning in near real time.
In today’s connected world, chances of intrusion and malicious attacks are constant. Public cloud environments, such as AWS, are not immune. For example, if a company’s identity and access management (IAM) keys get exposed or stolen they can be used by an attacker to create a large number of public cloud compute and storage resources that can cause financial harm. Unfortunately, there are no mechanisms that exist in public cloud infrastructures to prevent such a malicious act.
Human or programming errors in automation scripts can also cause abnormal changes to resource provisioning. These types of errors can create a significant number of resources not only causing direct financial harm but also restricting resources needed for mission critical applications.
FittedCloud enhanced its predictive analytics capabilities to now find anomalous data patterns and inform AWS customers about changes to their infrastructure resources that are out of the norm. For example, FittedCloud’s cost management solutions will identify when a higher than the usual number of EC2 resources are created, when EBS capacity is greater than normal, or when a greater than the standard amount of data is uploaded to S3 buckets. FittedCloud’s anomaly detection alerts provide the location of the attack and credentials used for attack, among other pertinent details.
“FittedCloud continues to offer the only cost management solutions for helping AWS customers find and fix wasted spending and automatically right-size resources, all powered by patented, sophisticated machine learning algorithms,” said Jin Ren, co-founder, FittedCloud. “We are pleased to now offer anomaly detection as well. In dynamic AWS customer environments, resource utilization changes constantly and our solutions are now able to help customers prevent malicious or unintended resource allocations by identifying and reporting provisioning anomalies based on historical usage patterns.”
“FittedCloud is solving a significant challenge – wasted spending on AWS resources such as compute and storage. Fitting the cloud to customers’ needs with machine learning helps customers from buying more resources than are necessary,” said Prashant Parikh, Vice President of Engineering, Erwin. “Given how fast AWS environments change and the amount of data they create, anomaly detection is instrumental in helping customers mitigate the financial risk of an attack that creates an exorbitant amount of resources. If an anomaly is found, FittedCloud’s alerts will make it quick and easy to identify the cause of the problem and fix it.”
For more information about FittedCloud’s new anomaly detection, please visit FittedCloud Anomaly Detection and read our new blog, Real-Time Anomaly Detection – Protect yourself from malicious spend attacks on clouds.