TinyPNG
TinyPNG (by Tinify) is a free image optimization service built for developers and designers. It utilizes smart lossy compression to reduce the file sizes of JPEG, PNG, WebP, and AVIF files by up to 80% with no visible quality loss. That means faster load times, better SEO, and lower bandwidth.
You can compress, convert, and resize images via a clean web interface or integrate it into your workflow with the API. The platform also provides an image CDN for fast global delivery of optimized assets. SDKs are available for Python, Node.js, PHP, Java, Ruby, and .NET. WordPress plugin included, plus plenty of community-driven integrations.
No tuning, no noise, Tinify just works. Whether you're optimizing a handful of images or processing millions, it scales effortlessly. All plans include a generous free tier, and support is quick when you need it.
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Google Cloud Run
Fully managed compute platform to deploy and scale containerized applications securely and quickly. You can write code in your favorite languages, including Go, Python, Java Ruby, Node.js and other languages. For a simple developer experience, we abstract away all infrastructure management. It is built upon the open standard Knative which allows for portability of your applications. You can write code the way you want by deploying any container that listens to events or requests. You can create applications in your preferred language with your favorite dependencies, tools, and deploy them within seconds. Cloud Run abstracts away all infrastructure management by automatically scaling up and down from zero almost instantaneously--depending on traffic. Cloud Run only charges for the resources you use. Cloud Run makes app development and deployment easier and more efficient. Cloud Run is fully integrated with Cloud Code and Cloud Build, Cloud Monitoring and Cloud Logging to provide a better developer experience.
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AWS Elastic Beanstalk
AWS Elastic Beanstalk offers a user-friendly platform for deploying and scaling web applications and services built using various programming languages such as Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker, utilizing well-known servers like Apache, Nginx, Passenger, and IIS. By merely uploading your code, Elastic Beanstalk takes care of the entire deployment process, which includes capacity provisioning, load balancing, auto-scaling, and monitoring application health. Importantly, you maintain complete control over the AWS resources that support your application and can access the underlying infrastructure whenever necessary. There is no extra cost associated with Elastic Beanstalk itself; you are charged solely for the AWS resources required to store and operate your applications. Notably, Elastic Beanstalk is considered the quickest and most straightforward method for deploying your application on AWS. You can effortlessly upload your application using the AWS Management Console, a Git repository, or an integrated development environment (IDE) like Eclipse or Visual Studio, ensuring a seamless integration into your workflow. This flexibility allows developers to focus on coding rather than worrying about the intricacies of deployment.
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Hawkular Metrics
Hawkular Metrics is a robust, asynchronous, multi-tenant engine designed for long-term metrics storage, utilizing Cassandra for its data management and REST as its main interface. This segment highlights some of the essential characteristics of Hawkular Metrics, while subsequent sections will delve deeper into these features as well as additional functionalities. One of the standout aspects of Hawkular Metrics is its impressive scalability; its architecture allows for operation on a single instance with just one Cassandra node, or it can be expanded to encompass multiple nodes to accommodate growing demands. Moreover, the server is designed with a stateless architecture, facilitating easy scaling. Illustrated in the accompanying diagram are various deployment configurations enabled by the scalable design of Hawkular Metrics. The upper left corner depicts the most straightforward setup involving a lone Cassandra node connected to a single Hawkular Metrics node, while the lower right corner demonstrates a scenario where multiple Hawkular Metrics nodes can operate in conjunction with fewer Cassandra nodes, showcasing flexibility in deployment. Overall, this system is engineered to meet the evolving requirements of users efficiently.
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