The benefits of the cloud – agility and elasticity, guaranteed uptime, and significant savings in hardware deployment – are well-known. Cloud providers offer a rich and sophisticated set of building-blocks for forming a resilient infrastructure – but the responsibility to use them wisely still lies with the end-user. The realistic expectation, at best, is for a “shared-responsibility” management model for cloud resilience, security, and uptime.
Infrastructure growth on the cloud comes with relative ease. New services are introduced all the time, including by cloud providers that add new features at dizzying speeds. And, in maintaining and servicing an IT environment, in-house and third-party IT teams are all involved in executing changes and updates. Some of these new features, changes and updates, however, can negatively affect the environment in unpredicted ways, lead to misconfigurations and potentially, to downtime or outages in the cloud environment. Achieving resiliency in the public cloud and uninterrupted availability under such conditions is a real challenge especially since the resilience risks to IT environments on the public cloud stem from multiple sources.
Given the intricacy and interconnectedness of such IT environments, it is practically impossible to manually identify issues that may lead to errors. Automated, proactive discovery of these irregularities is critical to preventing outages and ensuring the highest levels of availability of the cloud environment.
How can enterprises take advantage of new, useful capabilities in the public cloud without sacrificing their environment’s integrity and availability?
AvailabilityGuard NXG™ for Public Cloud addresses the newer resilience challenges that come with public cloud environments. Our new SaaS offering helps customers prevent outages and assure resilience for public cloud infrastructure and services, covering multiple public cloud environments and layers, starting with AWS and Azure.
Secure and non-intrusive, the solution checks for misconfigurations across virtual machines, virtual networks, load balancers, databases, cloud storage, DNS, and more. A built-in risk detection engine based on deep knowledge and utilizing machine learning algorithms identifies single-points-of-failure before they impact business. A detailed description of the problem and the recommended path for resolution are presented to the appropriate team so that they can take immediate remediation action.
Using deep knowledge and AI/ML algorithms, it helps enterprises realize more of the net benefits of having a public cloud IT environment.