“Serverless computing is a cloud-computing execution model in which the cloud provider runs the server, and dynamically manages the allocation of machine resources. Pricing is based on the actual amount of resources consumed by an application.” — “Serverless Computing”, Wikipedia This mundane description of serverless is perhaps an understatement of one of the major shifts in recent years.

Let’s face it. Once you have consumed your free credit, AWS costs an arm and a leg. This is the price to pay for high-quality services. But how can you reduce your costs without sacrificing quality? This post will show you how to reduce your bill by up to 60% by combining four built-in features in Qovery. There are three categories of costs on AWS. The “data transfer”, the “compute”, and the “storage” costs.

Datadog’s features give you full visibility into every part of your application environment, so it’s likely you have many resources to switch between as part of your troubleshooting and development workflows. For example, you might switch from the host map to investigate a performance issue with your services in APM, or jump between dashboards to correlate metrics and troubleshoot a problem with your CI/CD pipeline.

We're excited to share some updates on what we've been working on at Taloflow. We've come a long way since we launched Tim - AWS cost management for developers, which was a finalist for Product Hunt Dev Tool of the Year. Since launch, we've had the opportunity to work with nearly 100 companies and developers. We've helped digital native companies like NS1, Bluecore and Modusbox save money, improve performance, and get a better grasp of their marginal costs on the cloud.

Does your work involve a lot of ITOps Monitoring? If so, chances are you have developed a roadmap for 2021 that addresses digital business disruption, application and infrastructure changes, and the ongoing global pandemic… And here’s an opportunity to incorporate expert advice into your plan.

AI is everywhere. Except in many enterprises. Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail, and for the few models that are ever deployed, it takes many months to do so. While AI has the potential to transform and boost businesses, the reality for many companies is that machine learning only ever drips red ink on the balance sheet.

DevOps fits this odd niche between development and oversight. Like any “Wild West” type of position, pretty much anything goes. Your job is to think of everything including the stuff you haven’t thought of yet. You make the rules, and as long as the lights are on you’re considered a success. But alongside that freedom come the rumors and SLA myths that inspire such dread that you write them off as jokes.

Since 1999, we’ve been developing tools at Redgate to support database deployments for SQL Server. In the past couple of years, we’ve increased our effort in this space by further developing our proprietary technologies based on SQL Compare, and acquiring others like Flyway, the most popular database migration engine. As a result, we now offer tools which provide more options for SQL Server and also support deployments for 20 different database systems.

A new start? 2020 came and went, and in the process, it left a mark in history and our lives that won’t be erased. Together, as a community, we all struggled, we all faced new challenges, we all united and did our best to help each other. We are grateful for the effort of our nurses, doctors, carers, scientific, essential workers, and innovators that have led this fight. We also take a moment to remember those that we have lost and those who have been affected the most.