Wherever you are on your cloud journey, you’re likely under pressure to cut or at least control your cloud spend. You may be undertaking “quick fix” cost cutting tactics such as turning off resources or moving workloads to cheaper services. But, as you may be finding out, tactical, reactive cost management activities generally only work for the short term and do not solve systemic inefficiencies that only increase over time if not addressed.

At Spot by NetApp, we see an increasing number of customers embracing Azure either as their primary cloud or as part of a hybrid or multi-cloud deployment strategy. While these customers are reaping significant business benefits from Azure, optimization of application infrastructure, controlling costs and mitigating operational burden continue to challenge Azure cloud operations (CloudOps) teams.

Let’s get right to the point: most Kubernetes workloads are underutilizing CPU and memory, with 49% of containers using less CPU than their defined requests. Although Kubernetes provides users with the ability to define resource guidelines for containers based on CPU and memory needs, it can be difficult to define and maintain these resource requirements for dynamic applications, especially in fast scaling scenarios.

The release of Apache Spark 3.4 introduced Spark Connect, and we are thrilled to announce that we now offer full support for Spark Connect on Spot Ocean for Apache Spark. This blog will provide an overview of what Spark Connect is and how to effectively utilize it with Spot Ocean for Apache Spark.

As we make Spot Connect available for all users today, we’re taking a moment to look back at the journey we’ve embarked upon since its beta release. Spot Connect made its debut with a clear vision—to revolutionize cloud operations by automating workflows, and the response from the Spot by NetApp community has been instrumental in shaping its evolution. Here’s a retrospective on the key milestones and lessons we’ve gained during this transformative year.

The Spot by NetApp portfolio has again been recognized as a leader and outperformer in the GigaOm 2023 Radar for Cloud Management Platforms (CMPs). This industry analyst report highlights key CMP vendors whose primary purpose is to help organizations manage the increasing complexity of cloud environments and control costs more effectively.

Azure Reservations and Savings Plans are discounted pricing models for certain Azure services. By purchasing a reservation or savings plan, you can reduce your costs in Azure by committing to specific usage terms in advance. The commitment gives Azure more visibility into your one-year or three-year resource needs while guaranteeing your usage for the term, and you will enjoy discounts on those core services.

Spot is thrilled to announce that we have achieved AWS Spot EC2 Service Ready status. This achievement validates Spot’s continued commitment to delivering a reliable and seamless experience for users by leveraging AWS Spot Instances.

Managing container environments, such as Kubernetes data planes and ECS requires more than achieving cost savings. Yes, this is a vital component of optimizing your containers. But you also need to optimize for availability and usage, all while having a clear visualization of how your costs break down across compute, network, and storage.

When it comes to choosing the right AWS container optimization solution, building a DIY suite of free optimizer tools may seem like a great idea, but will it provide everything you need? The hidden, total cost of ownership (TCO) for open-source tools can quickly build up, making it a less manageable option when compared to a third-party optimizer. Our helpful list of what you need to consider will help you decide which AWS container optimization solution is right for you: a DIY toolset or a managed suite.