Best Application Development Software for Redpanda

Google Cloud Platform (GCP) offers a wide range of tools and services to support application development. These include powerful APIs, SDKs, and serverless offerings that help developers quickly build, deploy, and manage applications. With services like Firebase, App Engine, and Cloud Functions, GCP allows for rapid iteration, CI/CD integration, and auto-scaling applications based on demand. These services are backed by Google’s robust infrastructure, ensuring that applications run reliably even under heavy loads. Additionally, GCP provides extensive documentation and support for developers to streamline the development process. New customers also get $300 in free credits to run, test, and deploy workloads, helping teams get started and experiment with the platform’s capabilities with no upfront cost.

Docker takes away repetitive, mundane configuration tasks and is used throughout the development lifecycle for fast, easy and portable application development, desktop and cloud. Docker’s comprehensive end-to-end platform includes UIs, CLIs, APIs and security that are engineered to work together across the entire application delivery lifecycle. Get a head start on your coding by leveraging Docker images to efficiently develop your own unique applications on Windows and Mac. Create your multi-container application using Docker Compose. Integrate with your favorite tools throughout your development pipeline, Docker works with all development tools you use including VS Code, CircleCI and GitHub. Package applications as portable container images to run in any environment consistently from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE and more. Leverage Docker Trusted Content, including Docker Official Images and images from Docker Verified Publishers.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

Shift testing to the left and find issues earlier, when they are easier and cheaper to fix. Enable developers to do better integration testing, shorten dev cycles and increase productivity. Shorter and more-thorough integration feedback cycles, mean more reliable products. Testcontainers Cloud makes it easy for developers to run reliable integration tests, with real dependencies defined in code, from their laptops to their team’s CI. Testcontainers is an open-source framework for providing throwaway, lightweight instances of databases, message brokers, web browsers, or just about anything that can run in a Docker container. No more need for mocks or complicated environment configurations. Define your test dependencies as code, then simply run your tests and containers will be created and then deleted.