Snowflake has gained significant traction in the data warehousing space due to its unique architecture, flexibility, and ease of use. Heck, after using a legacy approach for some time, we at CloudZero went with Snowflake. While at it, we noticed Snowflake customers express concerns about costs more often than they would like. So, in this guide, we’ll share our best tips for getting the most out of Snowflake without overspending.

If cost optimization is your only reason for adopting Kubernetes and containers, you might be in for a rude surprise — many companies find that costs increase after moving to Kubernetes. Even companies who adopt Kubernetes for other reasons, like time-to-market advantages, should follow basic cost control best practices to stay within the budget. Optimizing cloud costs related to running Kubernetes doesn’t have to involve trade-offs for performance or availability.

According to Gartner, 90% of global organizations will run containerized applications in production by 2027. The need for continuous innovation, performance, and availability is driving this shift to meet customer expectations. Kubernetes plays a crucial role in this transformation. It offers a robust open-source platform for managing containerized applications. Yet, ensuring optimal application performance is only possible with observability.

It’s all well and good to say that “every engineering decision is a buying decision.” It’s one of our favorite phrases here at CloudZero! However, it’s one thing to say it and quite another to LIVE IT. That’s pretty much the driving force behind CloudZero: We want your team to be able to access your company’s cloud spend data, analyze it from every angle that might be helpful, and use that information to grow the business.

Here is the thing. You don’t need more than one cloud service provider unless you are considering a multi-cloud strategy. And even if you plan to work with all three cloud vendors, you’ll want to know which one is right for specific services. To help you decide, we’ll share the strengths, pricing, and other differences between Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) below. Let’s start from the very beginning.

Businesses move to the cloud for several reasons. For some, moving to the cloud means gaining access to the best enterprise-level technology without the associated costs of handling, maintaining, and managing the underlying infrastructure. For others (like startups), the ability to scale quickly and respond faster to market demands is at the top of the list.

Pricing matters. Charge too little and you won’t earn enough revenue to stay afloat. Charge too much and you could lose thousands in potential business. You don’t want to price out some customers. So what can you do? This is where tiered pricing comes into play. The SaaS pricing approach can be helpful for companies looking to meet the needs and budgets of their different customer personas.

The Amazon Elastic Block Store (EBS) service should provide high-performance block storage for Amazon EC2 instances. Yet, without careful management, Amazon EBS can become inefficient, leading to performance bottlenecks and cost overruns. For example, EBS volumes persist even after an EC2 instance has been terminated. The unused EBS volumes continue to incur costs.

Cloud observability tools offer visibility into your cloud infrastructure. They collect data from various sources to help you understand your applications’ performance. The tools enable you to monitor, optimize, and troubleshoot your cloud environment. In this guide, we’ll share why cloud observability is important and the best tools to consider.

It’s a fast-paced business world out there. This means artificial intelligence (AI) models that help modern businesses win are more than welcome. The right model can drive innovation, streamline workflows, and save you money. But OpenAI’s powerful models can have a catch: High-frequency API usage, complex queries, and data processing can lead to unexpectedly high costs. Surprise costs eat up budgets and threaten other critical investments. Not good.

Gartner predicts that by the end of 2025, 80% of organizations will use cloud automation tools to orchestrate workloads. The firm also forecasts that spending on public cloud services will hit $679 billion by the end of 2024, with SaaS leading the cloud computing market. This surge in cloud spending will shape the future of SaaS, and cloud automation tools will play a key role in this transformation.

Many SaaS companies struggle to get engineers to take charge of costs and lower cloud expenses. Confused business leaders often put the problem on the shoulders of the engineers: Surely, it’s just that the engineers don’t care enough to stay within budget, or maybe they just don’t want to participate in the culture of cost efficiency leadership is trying to build. But what if your engineers actually do want to optimize costs—they just don’t have the tools and data to do so?

AWS is the most popular cloud service provider partly due to its global data center network. The distribution enables organizations to configure their workloads to meet the needs of their global clients. The thing is AWS Regions charge different rates for almost everything, from compute and storage to data backup and retrieval services. And these cost variances can add up quickly.

Although container-related technology existed before 2013, Docker revolutionized and propelled it into the mainstream. Using Docker, developers could automatically create containers from application source code, share libraries, and reuse containers. Docker enables you to track container image versions, roll back to an earlier iteration, and track who built a specific one. You can even upload only the deltas between two versions.

HighRadius is a FinTech company that specializes in using automation to make financial management easier. So naturally, RamKishore Middela, assistant vice president of cloud engineering at HighRadius, recognizes more easily than most the benefits of automating his company’s cloud cost management with CloudZero.

GCP Cost Reporting is one of several tools provided by Google Cloud Console. The more you know about them, the more you’ll understand your Google Cloud bill. In addition, knowing the drivers behind your costs will help you reduce waste and maximize your GCP spend. This quick guide to GCP reporting tools will guide you on how to do it. We’ll also share how to get more detailed cost intelligence such as Cost per Customer or Cost per Feature on top of basics such as total and average costs.

Whether you’re growing rapidly and need to expand your infrastructure or demand has slowed and you need to scale down, AWS Auto Scaling can help. While manual scaling is time-intensive and costly, auto scaling is an automated process that adjusts capacity for predictable performance and costs. Auto scaling can help you optimize how your application is used and reduce wastage and optimize cloud spend.

For years, CloudZero has been a leader in the cloud cost allocation space, a statement supported by the fact that we remain the only cloud cost management platform to have received SOC1 Type 2 certification for our extreme accuracy when it comes to allocation and financial reporting capabilities. To quote our co-founder in the 2022 blog post listed above, “Quite simply, we organize cloud spend better than anyone else in the world.” Even so, we’re always looking to iterate and improve.