When it comes to modern container orchestration, there are a variety of control plane solutions for managing your applications in a containerized environment. Users can opt for managed services (i.e. Amazon EKS and ECS, Google GKE and Azure AKS) or run their own orchestration with Kubernetes. However, the dynamic nature of containers introduces operational complexities that can make your cloud infrastructure difficult to manage.

There are different tools and mechanisms for autoscaling in Kubernetes at both the application and infrastructure layers to help users manage their cluster resources. In this article, we’ll explore two infrastructure autoscaling tools for Kubernetes — Ocean by Spot and open source Cluster Autoscaler.

AWS Fargate is a managed service that enables you to run containers in Amazon Elastic Kubernetes Service (EKS) or Elastic Container Service (ECS). Since Fargate is serverless, you don’t need to provision or manage servers or clusters. However, you do need to set up package containers, define resource requirements, and configure permissions and networking policies. Fargate pricing is determined according to virtual CPUs (vCPUs) requirements, as well as usage of GBs of RAM for running services.

One of the key features of Ocean by Spot is a “headroom” feature, the ability to maintain a dynamic buffer of spare capacity for immediate scale-up. Ocean continuously predicts which workloads are most likely to require scale-up and adjusts headroom in line with this prediction to enable immediate scheduling of new tasks, without waiting for infrastructure provisioning. This shortens the time to execution for these workloads and dramatically speeds up the scale-up process.

Ever experienced bad logging- whether it’s the wrong log, the wrong information, or a multitude of other logging woes? We aren’t able to count the number of times anymore that we’ve happily gone and set log lines, only to find out that it was all for naught. The frustrations are endless. What is meant to be magic for your code, the ultimate savior when debugging, has become the ultimate frustration.

Secrets, by definition, should be kept secret, whichever tool you’re using. While there are plenty of best practices for keeping your Kubernetes secrets actually secret, there are some loopholes that can compromise their security, and might be taken advantage of by malicious entities. This post will cover prevalent best practices for securing your secrets on Kubernetes along with some new approaches for secrets management.

As we discussed in our previous post on cloud cost analysis and optimization, with over 60% of all cloud costs attributable to compute, focusing on compute infrastructure spend should be of the utmost priority. In this post we will focus on the public cloud vendors’ pricing models and how to best leverage them all for maximum cost optimization.

Cloud cost management is essential for business success, especially in times of business and global volatility. However, gaining quick and clear visibility into all your containerized workloads so you can control and improve the way they are being used, has not been so simple to date. At Spot, we have been addressing these issues and recently introduced cost analysis and showback tools for Kubernetes within our Ocean solution.

Amazon Web Services (AWS) and Kubernetes (K8s) have proven to be a powerful combination, with more K8s users also using Amazon Elastic Kubernetes Service (EKS) more than any other Kubernetes managed service. With EKS, users are able to benefit from the agility and scalability of Kubernetes on AWS without having to manage the K8s control plane. Paired with Ocean by Spot, users are able to abstract away infrastructure management as well.

Ocean by Spot is a fully managed solution for your Kubernetes and/or AWS ECS data plane, with the goal of delivering a serverless container experience for application developers. With that in mind, we are excited to announce that users can now import AWS Auto Scaling Groups (ASGs) into Ocean via the Spot Console.