By far the most consistent area of focus I’ve had in my career is monitoring and observability. Way back in 2005 while at Orbitz, I had the opportunity to learn from and work alongside Chris Davis, the original author of Graphite. It was an enormous success both at Orbitz and within the industry as a whole, and it’s been an honor and privilege to essentially ride that initial wave of monitoring innovation my whole career.

6 years later, another adjacent area emerged as my second-most common area of focus, and that is the collection of specific metrics used to quantify end-user usage, which are typically used to generate the bills for SaaS companies which have any sort of pay-per-use cost dimensions. Even including Omnistrate, I’ve now had direct involvement with the design and development of the metrics systems and/or billing integrations for the past 5 companies I’ve worked at over the past decade, and it’s incredible to me how similar the problems and solutions have been even when the industry or design of each business’ technical architecture has been so different from each other.

In today’s post I’d like to explore the internal complexities of SaaS billing systems and what challenges and design patterns for addressing them keep showing up. Hopefully by the end of this you’ll have a better understanding of how SaaS billing works and a blueprint for how to go about implementing it yourself if you need to.

Before the cloud, getting fresh hardware and deploying your new software was always done in big budget events involving procurement, finance, several IT teams and the whole process included no small amount of arguing most of the time.

Now that we have the ability to just press a button or make an API call to have a trove of shiny, powerful VMs added to our fleet at a moments’ notice, surely all the other problems regarding provisioning have been simplified as well, right?

In today's fast-paced digital landscape, the way enterprises consume and leverage software is undergoing a profound transformation. No longer confined to the traditional bounds of on-premises solutions and cumbersome software updates, businesses worldwide are pivoting towards Software as a Service (SaaS) platforms.

Beyond the obvious allure of cost savings and scalability, what deeper transformations are driving this shift? As we delve deeper into this transformative journey, we'll uncover the compelling reasons why enterprises are increasingly putting their trust in SaaS solutions and how this paradigm shift is reshaping the future of business technology.

Building upon our initial introduction of the control and data planes, this post delves deep into the interplay between these two planes. Shedding light on their individual roles and their combined impact on the overall SaaS experience. As we navigate through this post, we'll uncover the magic behind how these components work in tandem to ensure seamless operations, swift data transfers, and a scalable environment.

Scaling - it’s the reason we’re all using this cloud thing anyway, right? Surely all of your applications have been tested to effortlessly scale from 0 to 1,000 in milliseconds, and your databases can rebalance after scaling within minutes with zero impact to anything important, correct?

Don’t worry, I don’t think anyone has fully cracked this nut. But why is this? What makes it so difficult to actually get ALL the benefits of the infinitely flexible cloud?

The Complications and Strategies

In the first post of this two-part series, we introduced primary topics under the umbrella of cloud platform monitoring and went into a bit of detail for how they present specific challenges. In this follow-up post we’ll explore some of the state-of-the-art strategies for dealing with these issues and the additional complications that will arise when utilizing these techniques.

Introduction to Cloud Monitoring

Most people who work in platform engineering and cloud infrastructure are aware that you need to design both your applications and your underlying platform for high availability and fault tolerance, but there is a large range of resiliency from “relatively reliable” to “bulletproof”. The common adage goes something like this; for each “additional 9” of reliability, you’ll need to spend an exponentially greater amount of effort and cost to achieve it.

Why is this? And what goes into these additional levels?

Software as a Service, commonly known as SaaS, is more than just a tech buzzword. It has reinvented the software ecosystem and redefined the user experience. Let’s delve deeper into why the SaaS model is a game-changer, elucidating each point with detailed explanations and real-world examples.

In the world of computing and cloud services, the terms "control plane" and “data plane” are increasingly mentioned, even though these are actually older terms that originally came about in the networking world. This blog post aims to dive into the history of these concepts, where they are used and why, and how they’ve been extended into the emerging domain of SaaS. Let's dive in.

Certification

We are back with more exciting news. After our proud announcement of achieving the SOC 2 Type I certification, we have now achieved another significant milestone by earning the SOC 2 Type II Certification. This milestone underscores our commitment to creating a safer, more secure environment for our clients and their data.