Currently, we are creating a JAR file and using microservices. There are around 178 services in a single project. We use Docker to manage and do load balancing for all the services together.
I use Docker for containerization, deployment, and to create packages. Docker has a wide range of uses and integrates well with other command-line tools like Terraform. Docker is most helpful when trying to work with CI/CD pipelines.
Containerization is one of the use cases of Docker. Basically, Docker provides containers to its users. So, users can build, run and share containers among developers.
We primarily use the solution to create the node for the containers to deploy multiple apps. We have iOS applications in the containers, and we can build multiple microservices in the containers. It provides access to the content for public IPs. We can host it, for example, on AWS can contain some instances in Azure or AWS.
We're utilizing Docker extensively as all our products and services are deployed on Kubernetes, which is based on Docker. Our reliance on it is high. We have various services, including Python, C++, and Node.js, and several applications that are deployed via Docker. Our usage of Docker is almost 100 percent across all entries.
We used to have a silo problem. Docker solved it because we're able to containerize the microservices that we're developing in the form of Docker mail. Once we run the Docker image, it becomes a container. This container is guaranteed to run in every machine because we're installing Docker as the platform. On top of Docker platform, we're curating the Docker images and running the container. That container has a limited number of libraries and a limited number of data, which is required to run the application. Each container has a limited library system, which is required to run the application. This encapsulation makes it work perfectly, irrespective of the system. It works perfectly once we have encapsulated the application and containerized it. This is guaranteed to run in each machine. We're deploying the solution on Azure cloud. We're curating the CI/CD pipeline. In the CI/CD pipeline, we're curating the Docker images and pushing it to the container registry. We're writing the steps for how to build the Docker image into the YAML code. Once the Docker image is built, it's pushed to the container registry. We're writing this YAML code in the pipeline. Every person on the DevOps team is using this Docker tool. We have plans to increase usage because it's a great tool, and it's the latest technology. We're no longer developing monolith architecture, so everyone is developing applications with microservices. Docker is the best tool to containerize the application and encapsulate it.
I'm using Docker local Kubernetes development. I'm building software that uses Docker for cloud and on-premises applications. I'm consulting for a company that provides an enterprise database solution built using Docker containers and Kubernetes, so everyone at the company is using Docker indirectly.
Tech Lead Consultant | Manager Data Engineering at Ekimetrics
Real User
Top 5
2022-11-07T12:29:47Z
Nov 7, 2022
Our primary use case for this product is for packaging our solutions. In addition, we use it for packaging our web apps and deploying them on public cloud, primarily on Azure.
Our primary use is to deploy the applications in a secure environment. We prefer that our developer and the Docker files can make the images. After we have captured the images we use our CI/CD tool and deploy our applications. This makes our publisher fast and our containers are isolated from each other. We increase our security by using Docker.
Specialist - Cloud Services and Software at NRG Energy, Inc.
Real User
Top 10
2022-09-28T15:06:17Z
Sep 28, 2022
We are using Docker in our Java pipeline which is based on DevOps. We use Docker because we do not have to set up an environment to let people try applications.
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.
Currently, we are creating a JAR file and using microservices. There are around 178 services in a single project. We use Docker to manage and do load balancing for all the services together.
I use Docker for containerization, deployment, and to create packages. Docker has a wide range of uses and integrates well with other command-line tools like Terraform. Docker is most helpful when trying to work with CI/CD pipelines.
We work with containers for forecasting.
I use the tool for SQL, MySQL, and web development.
We use Docker to build, run, and ship any application.
We use the solution to pick up applications and migrate them to run inside containers in Java.
Containerization is one of the use cases of Docker. Basically, Docker provides containers to its users. So, users can build, run and share containers among developers.
We primarily use the solution to create the node for the containers to deploy multiple apps. We have iOS applications in the containers, and we can build multiple microservices in the containers. It provides access to the content for public IPs. We can host it, for example, on AWS can contain some instances in Azure or AWS.
We're utilizing Docker extensively as all our products and services are deployed on Kubernetes, which is based on Docker. Our reliance on it is high. We have various services, including Python, C++, and Node.js, and several applications that are deployed via Docker. Our usage of Docker is almost 100 percent across all entries.
We used to have a silo problem. Docker solved it because we're able to containerize the microservices that we're developing in the form of Docker mail. Once we run the Docker image, it becomes a container. This container is guaranteed to run in every machine because we're installing Docker as the platform. On top of Docker platform, we're curating the Docker images and running the container. That container has a limited number of libraries and a limited number of data, which is required to run the application. Each container has a limited library system, which is required to run the application. This encapsulation makes it work perfectly, irrespective of the system. It works perfectly once we have encapsulated the application and containerized it. This is guaranteed to run in each machine. We're deploying the solution on Azure cloud. We're curating the CI/CD pipeline. In the CI/CD pipeline, we're curating the Docker images and pushing it to the container registry. We're writing the steps for how to build the Docker image into the YAML code. Once the Docker image is built, it's pushed to the container registry. We're writing this YAML code in the pipeline. Every person on the DevOps team is using this Docker tool. We have plans to increase usage because it's a great tool, and it's the latest technology. We're no longer developing monolith architecture, so everyone is developing applications with microservices. Docker is the best tool to containerize the application and encapsulate it.
Our primary use case for Docker is local development. We use Windows for most of our use cases, which means we need two Docker Desktop tools.
I'm using Docker local Kubernetes development. I'm building software that uses Docker for cloud and on-premises applications. I'm consulting for a company that provides an enterprise database solution built using Docker containers and Kubernetes, so everyone at the company is using Docker indirectly.
Our primary use case for this product is for packaging our solutions. In addition, we use it for packaging our web apps and deploying them on public cloud, primarily on Azure.
Our primary use is to deploy the applications in a secure environment. We prefer that our developer and the Docker files can make the images. After we have captured the images we use our CI/CD tool and deploy our applications. This makes our publisher fast and our containers are isolated from each other. We increase our security by using Docker.
We use this solution for data collection and transfer across applications.
We are using Docker in our Java pipeline which is based on DevOps. We use Docker because we do not have to set up an environment to let people try applications.
Docker is an open-source container runtime for running container images. We are using Docker Swarm which is similar to Kubernetes but from Docker.