AWS tags are a bit like flossing your teeth every day — or getting eight hours of sleep a night. Everyone agrees they’re good habits that will make life easier down the road. But sometimes life gets in the way, and those habits fall a little short. Most teams set out with the intention to tag their infrastructure, but in our experience, it’s rare that companies have a perfect, thorough AWS tagging strategy.

Like a lot of SaaS companies, the CloudZero engineering team uses our own product — or as many would say, we “eat our own dog food” and “drink our own champagne”. So, when we built and released our cost per customer functionality last year, it was only natural that we were our own guinea pigs.

One of the most important things SaaS companies need to think about in order to be successful is financial modeling. To succeed in the increasingly competitive SaaS space, finance teams need to carefully consider a wide variety of KPIs and find ways to effectively manage both present and future cash flows. Cash flows and liquidity are two of the most common challenges faced in this industry — if effectively addressed, your company can position itself for long-term success.

Serverless computing is one of the fastest-growing areas in software development, along with hybrid clouds and using multi-cloud strategies. The global serverless architecture market is expected to grow at a CAGR of 16.2% in 2021 through 2026. It will reach $10.29 billion from $4.2 billion in 2020, according to MarketWatch. The serverless approach promises to help developers beat the cons of self-managed and even virtual server infrastructure. But is serverless right for you?

Every engineering team has their own approach when it comes to development methodologies. Most teams have embraced popular frameworks, Agile Scrum seems to be the most popular, both putting their own spin on it and choosing the parts that work for them. Despite any differences, we’re all out to achieve the same goal. We want a process that scales with our organizations and results in happy teams, high velocity, and quality software.

Choosing the right service plan is crucial when you are using Amazon Web Services (AWS). With 170 distinct services, ranging from compute to storage to networking and content delivery — each offered at different price points — the process requires careful consideration to make the right choice for your business. By default, AWS services are available on-demand and you pay a monthly bill for services used.

There’s no question that engineering teams at innovative tech companies are busy. No matter how successful your company is, there’s always a long backlog of feature enhancements that can make it challenging to focus on other priorities. So, it’s no surprise that one of the most common questions we get from companies that engage with us is “How much of an effort will this be for my engineering team?” The short answer is that you can get value within minutes.

The promise of running a business on the cloud is that — in theory, at least — you should be able to scale your infrastructure up and down with your customer utilization. This should lead, again in theory, to less maintenance and more opportunity for innovation.

There’s no question that the cloud offers efficiencies and innovation opportunities that are near impossible to replicate on-premise. In fact, Amazon reports that companies achieve 31% infrastructure cost savings, as well as 62% more efficient IT infrastructure management, when they move to AWS (and that doesn’t include the many other cost benefits — like improved security and on-demand services). But the extent of those efficiencies can vary.

Businesses are always looking for ways to increase efficiency and eliminate waste. For software-driven companies, DevOps is one approach that helps to achieve this. The goal of DevOps is faster software delivery to the end-user while maintaining high software quality. DevOps enhances collaboration between operations and development teams for faster code deployment. When evaluating the effectiveness of your DevOps model, it is critical to use metrics relevant to your organization.