AIOPS & The Future of Cloud Infrastructure

Moving to the Cloud and using DevOps strategies requires different skills and tools than traditional data center infrastructure. Many organizations need help from an experienced partner to do this correctly.

The challenge doesn’t stop with the initial migration or deployment. Technology leaders recognize the need to manage the availability and performance of their technology assets. But most lack the skills and resources to do this effectively, putting their businesses at risk.

Choosing the wrong managed services provider in the cloud can make the problem worse.

Cascadeo is developing the cascadeo.io AIOps-enabled Managed Services platform to address this challenge. The platform is backed by a 24x7x365 global NOC and human operations team.

The system has been built from the ground up to bring the latest machine learning and predictive analytics technologies to a much broader audience.

The system costs $499 per month, including the platform, operational tooling, and 24×7 MSP operations. This is much less than other solutions with similar capabilities.

Here is how it works in practice:

Using the Cascadeo AI portal, cloud customers sign-up for the service (SaaS style) and grant access to their cloud environment(s).

Next, they select and configure solutions for monitoring, ticketing, alerting and may optionally add custom runbooks for manual remediation.

The Cascadeo AI platform supports numerous integrations to leading SaaS solutions – allowing customers to leverage their existing investments.

For unsupported or non-existent solutions, customers may select Cascadeo-provided options, all of which we deploy free-of-charge through deployment automation and programmatic configuration management.

Ingesting operational telemetry from the client cloud environment, the Cascadeo AI platform’s back-end Analytics platform leverages AWS and other AI/ML platform technologies to learn what the normal operational patterns are within a customer’s deployment.

The system looks for anomalies in the data, and can often detect issues before they become service-impacting incidents.

When a trouble ticket is opened, it is automatically processed by an automation which marks it up with AI-derived insights: likely criticality and business impact, possible runbook recipes or response plans, expected time to resolution, and more.

Predictive Analytics (applied to time-series monitoring data) allows the system to predict events and outages; identify, correlate and prioritize events; and identify root cause.

AWS Lambda-powered event handlers manage alerting and routing of notifications to the customer’s desired ticketing and notification systems.

By allowing customers to “come as they are” and bring their own operational support systems, while back-filling any missing components through automation, the Cascadeo AI platform does the impossible – providing “one size fits all” pricing while allowing complete flexibility and making no rigid assumptions about the architecture, technical sophistication, scale, or customer’s application workload.

Even customers who inherit hand-built one-off cloud environments or lift-and-shift workloads immediately derive benefit, both from the amazing team of humans in the Cascadeo operations team and from a suite of AI platform technologies.

For customers who adopt it, the Cascadeo AI platform utilizes the cross-platform capabilities of AWS EC2 Systems Manager to securely remediate issues in cloud and on-premise environments — without exposing credentials or sensitive VPNs to a broad audience of MSP employees.

Automated and manual operations actions are fed back into the platform to inform future decisions.

Cascadeo is uniquely qualified to build this technology platform because of our extensive experience in cloud professional services.

Among 100+ other successful projects, the company built and operates the entire monitoring platform for a Fortune 500 cloud provider – and has done extensive work enhancing that company’s data analytics systems, as well.

Cascadeo views the platform as the third piece of a virtuous cycle: high-end professional services, custom managed services, and Cascadeo AI for the broader audience who many not need professional services, but cares about a cloud application workload enough to retain a cloud-centric MSP to deliver 24×7 operations.

While other cloud MSPs try for a one-size-fits-all approach, forcing customers to use their tooling and ops methodology, Cascadeo recognizes that every customer is unique and solves for the inherent scalability challenges by building our platform technology.

Look for more news on the Cascadeo AI platform in the coming months, and don’t forget to visit us on the trade show floor at AWS Re:Invent this November!