When the Cloud Honeymoon Has Ended; Successfully Operating in a Cloud Environment
Netflix, a company that accounts for over a third of all downstream internet traffic in the US at peak, is widely regarded as a pioneer in the cloud. I had the privilege to manage the Cloud Solutions team at Netflix through 2013, looking after streaming operations and cloud tooling. I, along with others at Netflix, often spoke publicly about Netflix's migration to the cloud, as we were one of the first to move major infrastructure to the cloud.
Migrating from the data center into the cloud was no easy task, but the hard work emerged after we were functioning in the cloud. Only then did we fully appreciate the complexity of running a globally-distributed, always-on end-user service on top of an elastic software-defined infrastructure. From the start, the cloud-based service was superior to the same service running in Netflix data centers. But we quickly realized the added complexity and management of operating in the cloud.
This led us to build tools like Asgard, ICE, Chaos Monkey, and the rest of the Simian Army, all of which are now a part of NetflixOSS. Back then, Netflix was a trailblazer and early adopter of the cloud. Now, more and more traditional enterprises are going all-in the cloud.
Since leaving Netflix and joining Scale Venture Partners, I have been on the lookout for a company that encapsulates the best practices and tools we developed at Netflix for highly-available and efficient cloud operations because many companies prefer to buy instead of build. I m thrilled to have found it in CloudHealth Technologies. Today, we announced a 12M investment in the company to help support customer acquisition and expansion of the platform.
Cloud Adoption Lifecycle
The typical cloud adoption lifecycle goes like this:
- Teams move to the cloud to increase agility and velocity of feature delivery
- At some point, typically about a year after initial cloud adoption, the organization realizes that the increased agility and velocity come at the cost of increased management complexity, with the side effect of reduced visibility into costs and cost drivers
- As a result, a project is launched to reduce cloud costs and increase visibility into cost drivers. (For example, one use-case is the desire to attribute infrastructure serving costs to each customer to determine per-customer margins.) Because of the dynamic nature of the cloud, added cost visibility and attribution is an ongoing need rather than a one-time analysis. Once costs are under control, broader cloud complexity needs be tackled with increased visibility and automation. For visibility, the value lies in providing a single place that shows that health of the cloud infrastructure while maximizing information flow to enable decentralized decision making. For automation, management complexity is reduced by minimizing human (manual) workflows and allowing software to manage the ongoing operations in the cloud.
- Invariably, organizations hit a stage where cloud adoption matures beyond initial experimentation. At this stage, automation and visibility are needed to extract the true benefits of the cloud and make cloud operations manageable.
When we look across early cloud adopters, we find that many built their own internal sets of management services for making cloud operations more automated, less costly, and more performant, available, and secure. Looking ahead, this need to automate and simplify cloud operations is a universal requirement for cost-effective cloud adoption and one that is very much not limited to early adopters. CloudHealth solves that need and can help any company, small or large, that is serious about maximizing the return of a cloud investment.
What I liked about CloudHealth was that they have a holistic vision for what IT Service Management in the cloud should be. They deliver an easy-to-use, API-driven, cloud analytics platform that addresses all aspects of the traditional IT service management platforms without the heavy investment. The CloudHealth platform collects, integrates, correlates and analyzes the massive amount of data available from all of the cloud-based platforms and services that companies use today thus giving customers the context to develop business models, analyze trends, and report historically. They are setting the pillars for companies to recognize success in the cloud. I look forward to working with the team on their next phase of growth.
Originally published January 21, 2015.