The conflict between engineers and finance is notorious. Finance thinks engineers just want to build cool products regardless of the cost. Likewise, engineers often feel their every move gets monitored by hawkish finance employees who seem to only care about costs. How can you, as a leader, encourage both teams to work together harmoniously? And what can you do to diffuse the situation when engineers feel attacked for their infrastructure choices?

Cloud optimisation enables organisations to significantly lower their cloud spending while ensuring the desired performance and necessary compliance. It’s a process that every business should adopt when choosing cloud infrastructure as a foundation for their applications. It’s been proven that applying cloud optimisation best practices leads to a total cost of ownership (TCO) reduction of two-thirds under certain circumstances. But let’s step back for a second.

MongoDB is a popular non-relational database among developers of distributed apps. This Not Only SQL (NoSQL) database system delivers versatility, high scalability, and a flexible querying model. MongoDB is also remarkable for its fault-tolerance, self-healing, and real-time analytics capabilities. But many companies also decry that MongoDB pricing is expensive and complicated. We’ll share how the MongoDB pricing model works.

Application performance monitoring (APM) solutions are essential for any business looking to manage its operations efficiently. By providing real-time insights into the performance of your applications, APM solutions can help you quickly identify areas that need improvement and prevent costly mistakes from occurring in the future. But with so many different types of APM solutions on the market today, how do you know which one is right for your company?

Public cloud users continue to get stung by unexpected costs due to the challenges faced when working with or moving workloads into the cloud. When organizations see this surge in their costs, it typically requires the process of cloud cost optimization to tackle the problem. Cloud cost optimization is the task of minimizing cloud spending by enforcing best practices and appropriate cost-efficient resources.

FinOps, or the practice of managing a company’s cloud computing costs, and DevOps, the process of efficiently building applications in the cloud, should ideally go hand-in-hand. Engineers with a streamlined development process and a cost-conscious mindset can produce functional products with great margins and a high potential for scalability. However, incorporating FinOps into the DevOps lifecycle, and vice versa, isn’t always easy.

Amazon SageMaker makes it easy to prepare data for machine learning (ML) and then train, deploy, and modify ML models. SageMaker is a fully managed service that automates much of the ML lifecycle. So, if you want a single partner to help you through all stages of your Artificial Intelligence (AI) lifecycle, SageMaker might be the answer. Perhaps more important for this post is the promise that Amazon SageMaker can reduce your machine learning model costs. But does SageMaker pricing reflect this?

There are almost as many reasons for learning FinOps practices as there are resources available to learn from. Maybe you operate a SaaS company, for example, or you're looking for a job in FinOps. The FinOps field grows in importance every time cloud services and their associated costs become more complex — which can feel like every single day. Regardless of your situation, you’ll need high-quality FinOps resources that offer up-to-date materials and in-depth information.

As technology improves and customer demands change, many companies must provide fast, engaging, and secure services. Developers rely on platforms that support sub-millisecond response times to power these capabilities in their applications. Amazon ElastiCache and Redis are two of the most popular platforms for building fast, highly available, and scalable data stores.

As per the latest forecast by Gartner, worldwide IT spending is projected to amount to $4.6 trillion in 2023, up by 5.1% from 2022. The demand for IT will be strong in 2023 as enterprises launch digital business initiatives to respond to global economic challenges. In a downward economy, conventional wisdom warrants reducing costs.