For many years, managing cloud complexities has always been a challenge for both cloud-enabled and native companies. From waste reduction, RI management, to cluster optimization, the glaring gaps in the industries are causing businesses to underperform, lose money, and be vulnerable to security breaches. But as more sectors are quickly shifting from on-site servers to cloud, the need for a cutting-edge DevOps solution is paramount for both growth and profitability.
We had the chance to interview James Wilson, Vice President of Engineering and Product Development leader at nOps, a real-time, event-driven cloud platform that provides an AI-powered SaaS solution. The company helps rapid-growth companies build, manage, and operate a well-architected AWS or Azure infrastructure that is secure, cost-optimized, reliable, efficient, and operationally excellent.
What are the industry gaps that you’ve noticed in cloud management that led you to the foundation of nOps?
Many of the legacy cloud management solutions in the market provide tooling for investigation without actionable insight or automation. At nOps, our goal is to make every recommendation actionable and automated. It’s become an obsession for us. So much so, that you don’t pay for nOps if we don’t save you money as a direct result of our automated optimization and remediation. This is what sets us apart in both vision and execution.
Can you talk about your time at nOps and how that led to forming an expert product engineering team in delivering world-class solutions?
When I joined nOps, I was fresh off of a decade spent building a large-scale multi-cloud SaaS solution. I recognize the challenges that engineering teams face putting the guard rails in place to ensure meet to deliver capability to the market with performance, security, and reliability while balancing the ROI that finance teams require to grow the business. The nOps mission directly addresses the challenges that engineering teams face, which are a direct inhibitor to innovation.
The bar at nOps is very high. We don’t just look for people that can write code, each team member must have domain expertise across the public cloud, DevOps, security, compliance, and cloud FinOps. We don’t just build features, we build solutions that make an impact on our users. All of this mission requires a tremendous amount of data — every engineer has to have a deep grasp of the data and the flexibility to use a variety of tools and frameworks to analyze and provide meaningful recommendations at scale.
As an ML-powered FinOps team, some of your specializations include continuous cloud waste reduction, continuous container cluster optimization, continuous RI management, and spot orchestrator. Can you talk about your technologies that help companies manage their cloud? How does it work?
Over time, nOps has naturally evolved into a cloud data and automation tool that is relentlessly focused on FinOps realization. We’re constantly adding new data sources to improve recommendations and expand our feature set. This has required us to change the way that we ingest, process, and work with the data.
Our solution is cloud-native from inception, which allows us to rapidly deploy and scale new services without re-architecting native code. We use a message-based approach to inter-service communication, which allows each new feature service to subscribe to a variety of events flowing through our system.
We have adopted an Extract-Load-Transform approach to data warehousing and built a data mart for each of our clients which keeps the data both highly partitioned, and easy to extend. We base most of our existing recommendations on cost and usage data, resource metadata, cloud event data, and resource utilization data. Because of the way that we store and access the data in its raw format, it’s super easy for customers to add data sources such as Kubernetes insights or high-resolution network flow logs — both of which can lead to substantial savings. This also allows us to apply every new optimization development to all of our customers with ease.
We leverage a highly scalable ML and data transformation stack which means that our data and engineering teams can focus more of their efforts on building — and less time on tooling. Our data ingest, Spark, SQL engine, and job compute are a one-stop shop for software, data, and ML engineers alike.
Our engineering team is completely connected to feedback in both a systematic and human form. Each squad takes an hour of focus time each day to work as a team on improving recommendations and improving feedback loops from both application and field teams.
Everything about nOps’ solutions is “automated and data-driven.” Walk us through your automated cost optimization solution and how it’s a difference-maker in business operations.
Our solution starts by analyzing the lost opportunities across the dominant pillars of optimization: commitment management, scheduling, Kubernetes, Spot, and Cloud Waste. Most of the solutions are one-click integrations. Each of these solutions is not only designed to integrate with the way that modern engineering teams work, but provides clear and consumable business impact analysis that FinOps teams can use to track, allocate, and show back both costs and savings to stakeholders throughout the business. Our product is built by FinOps professionals for FinOps professionals.
Can you talk about your partnership with AWS and Azure and how nOps supports the pillars of these Well-Architected Frameworks? Are there any future product partnerships on the horizon with them?
Our partnership with AWS is second to none. We have developed and launched integrations with AWS Eventbridge, EKS, and Systems Manager in partnership with the AWS service teams over the past few months alone. Every insight in nOps is aligned with the Well Architected Framework, and we are the leading provider of automated Well Architected assessment in the world today. We have a regular technical cadence with the Well Architected team to keep in alignment with the constant stream of advances. Our partnerships with Azure are also growing with equal momentum. I don’t want to spoil any surprises, but you can expect big announcements in this area.
Your key solutions include AWS and Azure security and compliance. How does nOps’ technology help customers avoid security breaches and ensure compliance with industry standards like SOC 2 or HIPAA?
nOps has a full suite of security insights that are mapped beyond Well Architected. We map our insights and remediations to both SOC2 and HIPAA and using our Eventbridge integration any nOps security rule can be fully, securely automated directly with the customer account.
Describe the integration process of nOps to existing workflows.
We start every nOps integration using our own rapidly growing and changing AWS environment and engineering team as a customer. We design our integrations for the way that modern, cloud-centric, DevOps-oriented development teams work. Risk-free commitment is completely zero-touch and uses AI to continuously optimize commitments across available service types. The scheduler uses AWS Eventbridge to allow a seamless integration into your environment and give client teams total security and control. Our other solutions integrate either via Eventbridge or with Infrastructure-as-Code to both actively optimize and also automatically generate changesets to apply configuration changes.