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?

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.

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.

Microsoft Azure was a relative latecomer to the public cloud market: AWS preempted everyone in 2006, and Google GCP came next, in 2008. By the time Azure launched in 2010, the public cloud market had already grown to more than $24 billion. Despite being third to the party, Azure had a key advantage: The Microsoft Office Suite was (and is) a go-to choice for corporate collaboration.

For data professionals interested in data modeling, artificial intelligence, and machine learning, Databricks offers a powerful cloud data platform. The Databricks Lakehouse combines data lake and data warehouse capabilities in one architecture. This makes Databricks particularly suitable for building sophisticated data analytics, Artificial Intelligence (AI), and Machine Learning (ML) models. Plus, Databricks claims its lakehouse is up to 12X cheaper than traditional alternatives.

You need a robust platform to speed up your read/write operations per second if you provide services such as live streaming, social media networking, and analytics. By storing frequently accessed objects in faster memory (RAM or in-memory data stores instead of slower disk-based storage), caching reduces latency. Amazon ElastiCache is a managed, in-memory data store and caching service in one.

MongoDB has evolved into the database solution of choice for developers looking to build efficient, scalable applications in the cloud. But, as when using any cloud-based infrastructure, using MongoDB introduces an additional layer of complexity to customers’ IT spend. This week, we announced support for MongoDB on the CloudZero Platform.