As of yesterday, the team behind Go has released a new version 1.18 with some significant changes to the language. Those of you who want to start using these new features are in luck: you can do it right away on Platform.sh. If you’re already using Go on Platform.sh, you can upgrade by changing the number in the type key of your app configuration. In your.platform.app.yaml file: If you’re not yet using Go for your project, now’s a great time to give Go a try.

Self service analytics are becoming increasingly popular and essential in this data-driven world. For many businesses, there is a growing need for their internal departments to access their data and business intelligence and harness its power themselves. Traditionally, business intelligence processes are the purview of IT teams and data specialists.

Source: APM in the new normal, survey by eG Innovations and DevOps Institute Cloud adoption is increasing at a rapid pace. The eG Innovations & DevOps Institute APM survey indicates that 88% of organizations are using at least one form of cloud technology. Organizations move to the cloud for agility – they can deploy and have applications running in the cloud in minutes. Cloud computing also offers options for high availability, automated backups, and such.

On December 7, 2021, Amazon’s cloud services recently suffered a major outage that not only affected Amazon services, but also many third-party services we use day-to-day, including Netflix, Disney+, Amazon Alexa, Amazon deliveries and Amazon Ring. Causes for the outage, which began at 7:30 am PST and lasted nearly seven hours, were detailed in a Root Cause Analysis report published by AWS that shed light on factors that may have contributed to the extended length of the disruption.

Put simply, cloud adjacent storage is just a privately owned and operated storage system, within network reach of a cloud provider’s region, but without the pay-as-you-grow and access charges found in public clouds.

The Snowflake data cloud offers powerful data warehousing, analytics, and processing tools. The platform can handle many data workloads on one platform, helping organizations turn data into actionable insight across teams, departments, and regions. Snowflake’s architecture is also unique. Compute and storage are completely independent and both are highly elastic. Yet, Snowflake's per-second billing and highly elastic compute model demand frequent usage and cost monitoring.

Let’s face it. Gaining a competitive advantage in the target market is expensive. Even if you have a good idea and its execution plan in mind, operations related to management, storage, networking, service provisioning, security, and application management will cost you a fortune. To say the least, a cutting-edge IT infrastructure, a reliable team, and a strategy for rapid product releases or expansion/scaling is a must for your product’s success.

In this blog post, I follow on from my previous blog on AWS CloudWatch Part 1 of 2 to explore how you can go beyond basic agentless CloudWatch monitoring by deploying the CloudWatch agent and some of the key information and planning you need to do this. I’ll also cover how eG Enterprise offers out-of-the-box functionality to avoid complex JSON scripting or tooling to implement monitoring.

We are going to deploy a Go application directly from your repo to AWS with Cloud 66. Any application using any language on any framework can be deployed with Cloud 66 as long as it has a Dockerfile. Note: Rails applications are exceptions as we deploy them natively. If your application does not have a Dockerfile, we will suggest one for you based on your code. However, we would recommend reviewing what we have suggested and making sure the Dockerfile meets your requirements.

When Apache Spark introduced native support for Kubernetes it was a game changer for big data. Speed, scale and flexibility are now at the fingertips of data teams—-if they can master Kubernetes. It’s an uphill climb for even experienced DevOps teams. At Spot by NetApp, we’ve seen first-hand the challenges that companies are facing as they navigate the complexities of operating large-scale Kubernetes applications.