At Koyeb, we're working to build the most seamless way to deploy apps to production without worrying about infrastructure. But there's still plenty to keep you busy at the application layer with performance tuning and troubleshooting. That's why we're introducing Metrics — an easy way to monitor and troubleshoot application performance. Deploying on Koyeb makes thinking about infrastructure or orchestration unnecessary.

The digital landscape is always moving forward, and so is the way we manage our applications and services. We are proud to introduce something exceptional for our users: A brand-new DreamFactory Amazon Machine Image (AMI) launch.

Discover where IIS log files are located on both Windows servers and Azure. This guide offers a step-by-step tutorial on how to locate and view your IIS logs, ensuring efficient troubleshooting and security audits. For a standard Windows Server, the default log location is: %SystemDrive%\inetpub\logs\LogFiles If your IIS logs are not stored in the default location, follow these directions below to look up where they are currently being stored.

Speed and efficiency are paramount during the build process. If you use a Dockerfile to build your container images from source code, you want to know about build cache. In this blog post, we’ll talk about what happens when you create a Docker image using a Dockerfile, how caching works with Docker, and how to optimize your Dockerfiles to maximize the benefits of build cache with Docker and on Koyeb.

According to research from Matillon and IDG, data volumes increase by 63 percent per month on average in an organization. Examining such substantial volumes of data without the right tools makes it impossible to make informed decisions, even in small businesses. The key to deriving useful and profit-driving insights from data is data visualization - which turns complex raw figures into meaningful visual representations of the data. Google Charts is a free data visualization library provided by Google.

Google BigQuery is a robust and scalable cloud-based data warehouse that allows storing and analyzing vast amounts of data. BigQuery is a natural choice if your data already exists on the Google Cloud Platform (GCP). But before you leverage the platform, you need to extract the source data, carry out transformations, and load the data into your data lake or warehouse. This is where the ETL process and the ETL tools play a significant role.

Today, we are excited to announce the support of Dockerfile based deployments in general availability. You can now deploy any GitHub repository that contains a Dockerfile across all our locations worldwide. It can be used to deploy APIs, full-stack applications as well as workers with no extra cost. Building and deploying using Dockerfiles offers more flexibility: you can deploy any kind of application, framework, and runtime, including with custom system dependencies.

In today's cloud-centric world, ensuring data quality and reliability on AWS is more crucial than ever. Dive into the best practices for data observability to harness the full potential of your data assets.