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Should you optimize your Docker container?

This blog explains the reasons for Docker container optimization and responds to the question "Should you optimize your Docker container?"

Docker container optimization

How Docker Works?#

Docker is a leading containerization industry standard that aids in the packaging and distribution of programs in the most efficient manner feasible. Containers are a convenient approach to transporting software to various environments. They assist you in packaging your code with your desired environment settings and other platform-dependent parameters so that it may be quickly instantiated on other computers with little setup overhead [(Potdar et al., 2020)].

Simply put, Docker is an open-source solution that aids in the management of the containers we just covered. Docker, like containers, is platform-independent, as it supports both Windows and Linux-based platforms.

Docker container and cloud computing

The Kubernetes vs. Docker debate#

When stated as a "both-and" issue, the distinction between Kubernetes and Docker becomes clearer. The truth is that you don't have to choose—Kubernetes and Docker are fundamentally different technologies that complement each other effectively for developing, deploying, and [scaling containerized applications].

Kubernetes and Docker collaborate. Docker is an open standard for containerizing and delivering software. Docker allows you to construct and execute containers as well as store and distribute container images. A Docker build can be simply executed on a Kubernetes cluster, but Kubernetes is not a comprehensive solution. Implement extra tools and services to handle security, governance, identity, and access, as well as continuous integration/continuous deployment (CI/CD) processes and other DevOps principles, to optimize Kubernetes in production [(Shah and Dubaria, 2019)].

Docker List Containers#

To list docker containers, use the commands 'docker container ls' or 'docker ps'. Both commands use the same flags since they both act on the same item, a container. It includes many parameters to achieve the result we want because it only shows operating containers by default. The command 'docker ps' is shorter and easier to type.

What Causes Docker Performance Issues?#

Docker is a sophisticated system that is affected by a variety of circumstances, including host settings and network quality. The following are some of the most prevalent causes of Docker slowness:

  • Inadequate Resource Allocation
  • Docker Image Sizes
  • Size of Docker File Context
  • Docker's default configuration is still in use.
  • Latency in the network

How to Optimize Docker Containers?#

There are several ways to make Docker run quicker:

Appropriate Resource Allocation#

The host machine's performance has an impact on the container's performance. A sluggish CPU or inadequate RAM might create a bottleneck, causing Docker's performance to suffer [(Sureshkumar and Rajesh, 2017)].

Docker Image Optimization#

Examine the Dockerfile for the image and ensure that the file context is not too huge. The context contains a list of the files required by Docker to construct a container.

Examine the Dependencies#

Debian-based Docker images may create extra binaries and files while installing dependencies. Some of these interdependencies are not required for the container's usual operation and can be eliminated.

Consider Using Microservice Architecture#

Monolithic programs are typically slower than microservice-architected apps. If your Docker containers are struggling to operate, it might be because the app within the container is too large [(Wan et al., 2018)]. When the app is migrated to microservices, the workload may be distributed among several containers.

Make use of Dedicated Resources#

Hosting containers on the dedicated hardware of Bare Metal Cloud minimizes virtualization overhead and increases container performance. Containerized programs do not share system resources like RAM and CPU, which reduces latency and allows apps to fully exploit hardware.

Use a light operating system#

Building images using a lightweight system can save up to 100 MB of the final image size, resulting in much faster performance.

Dockerfile Layers Cache#

Layer caching can help you produce images faster. When Docker begins constructing an image, it searches the cache for layers with similar signatures and utilizes them [(Liu et al., 2018)]. This feature expedites the construction process.

Dockerfile Layers

Docker for Windows#

Docker containers initially only supported Linux operating systems. Docker may now operate natively on Windows, eliminating the requirement for Linux support. Instead, the Docker container will run on the Windows kernel itself, and the whole Docker tool set is now compatible with Windows. The Docker CLI (client), Docker compose, data volumes, and the other building pieces for Dockerized infrastructure are now Windows-compatible.

Conclusion#

Docker Container optimization is critical for overall performance. As more applications migrate to containerization, it is critical to maintaining them up to date on best practices. Otherwise, you risk losing some of the important advantages Docker has over traditional methods of software delivery, which would defeat the point of using Docker containers in the first place.

Edge VMs And Edge Containers | Edge Computing Platform

Edge VMs And Edge Containers are nothing but VMs and Containers used in Edge Locations, or are they different? This topic gives a brief insight into it.

Introduction

If you have just recently begun learning about virtualization techniques, you could be wondering what the distinctions between containers and VMs. The issue over virtual machines vs. containers is at the centre of a discussion over conventional IT architecture vs. modern DevOps approaches. Containers have emerged as a formidable presence in cloud-based programming, thus it's critical to know what they are and isn't. While containers and virtual machines have their own set of features, they are comparable in that they both increase IT productivity, application portability, and DevOps and the software design cycle (Zhang et al., 2018). The majority of businesses have adopted cloud computing, and it has shown to be a success, with significantly faster workload launches, simpler scalability and flexibility, and fewer hours invested on underlying traditional data centre equipment. Traditional cloud technology, on the other hand, isn't ideal in every case.

Microsoft Azure, Amazon AWS, and Google Cloud Platform (GCP) are all traditional cloud providers with data centres all around the world. Whereas each company's data centre count is continually growing, these data centres are not near enough to consumers when an app requires optimal speed and low lag (Li and Kanso, 2015). Edge computing is useful when speed is important or produced data has to be kept near to the consumers.


What is the benefit of Edge Computing?#

Edge computing is a collection of localized mini data centres that relieve the cloud of some of its responsibilities, acting as a form of "regional office" for local computing chores rather than transmitting them to a central data centre thousands of miles away. It's not meant to be a replacement for cloud services, but rather a supplement. Instead of sending sensitive data to a central data centre, edge computing enables you to analyse it at its origin (Khan et al., 2019). Minimal sensitive data is sent across devices and the cloud, which means greater security for both you and your users. Most IoT initiatives may also be completed at a lower cost by decreasing data transit and storage space using traditional techniques.

The key advantages of edge computing are as follows:
- Data handling technology is better
- Lower connection costs and improved security
- Uninterruptible, dependable connection

What are Edge VMs?#

Edge virtual machines (Edge VMs) are technological advancements of standard VM in which the storage and computation capabilities that support the VM are physically closer to the end-users. Each VM is a self-contained entity with its OS, capable of handling almost any program burden (Millhouse, 2018). The flexibility, adaptability, and optimum availability of such tasks are significantly improved by VM designs. Patching, upgrades, and care of the virtual machine's operating system are required regularly. Monitoring is essential for ensuring the virtual machine instances' and underpinning physical hardware infrastructure's stability. Backup and data recovery activities must also be considered. All of this adds up to a lot of time spent on repair and supervision.

### Benefits of Edge VMs are:-
- Apps have access to all OS resources.
- The functionality is well-known.
- Tools for efficient management.
- Security procedures and tools that are well-known.
- The capacity to run several OS systems on a single computer.
- When opposed to running distinct, physical computers, there are cost savings.

What are Edge Containers?#

Edge containers are decentralized computing capabilities that are placed as near to the end customer as feasible in an attempt to decrease delay, conserve data, and improve the overall user experiences. A container is a sandboxed, isolated version of a component of a programme. Containers still enable flexibility and adaptability, although usually isn't for every container in an application framework, only for the one that needs expanding (Pahl and Lee, 2015). It's simple to reboot multiple copies of a container image and bandwidth allocation between them once you've constructed one.

Benefits of Edge Containers are-
- IT management resources have been cut back.
- Spin ups that are faster.
- Because the actual computer is smaller, it can host more containers.
- Security upgrades have been streamlined and reduced.
- Workloads are transferred, migrated, and uploaded with less code.
containers and VMs

What's the difference Between VMs and Containers even without the context Edge?#

Containers are perfect where your programme supports a microservices design, which allows application programs to function and scale freely. Containers may operate anywhere as long as your public cloud or edge computing platform has a Docker engine (Sharma et al., 2016). Also, there is a reduction in operational and administrative costs. But when your application requires particular operating system integration that is not accessible in a container, VM is still suggested when you need access to the entire OS. VMs are required if you want or need additional control over the software architecture, or if you want or need to execute many apps on the same host.

Next Moves#

Edge computing is a viable solution for applications that require high performance and low latency communication. Gaming, broadcasting, and production are all common options. You may deliver streams of data from near to the user or retain data close to the source, which is more convenient than using open cloud data centres (Sonmez, Ozgovde and Ersoy, 2018). You can pick what is suitable for your needs now that you know more about edge computing, including the differences between edge VMs and edge containers.

Learn more about Edge Computing and its usage in different fields - Nife Blogs