Every new day brings new devices that connect to the internet. People aren’t only connecting their computers and phones to the internet, nowadays there are smart TVs, smart homes, smart cars, and dozens of other smart things that require a stable internet connection in order to work.
Most users run time-sensitive apps where lag considerably diminishes the quality of the user experience. Far-off centralized cloud services suffer from high latency and are often the ones to blame for poor app performance.
Consequently, edge computing was developed to bring data processing closer to the user and solve network-related performance problems. Specifically, edge containers are designed for organizations to decentralize services by moving key components of their applications to the edge of the network.
Thanks to edge container hosting, organizations are able to achieve lower network costs and better response times. That’s why this technology is heavily used in web hosting.
If you are interested in learning more about edge containers, take a look below.
Definition of (edge) containers
Containers allow users to package application code, dependencies, and configurations into a single object that can be deployed in any environment.
When it comes to edge containers, the definition is quite simple. These containers are decentralized computing resources located as close as possible to the end-user with the aim to reduce latency, save bandwidth, and enhance the overall digital experience.
How do containers work?
Containers are easy-to-deploy software packages and containerized apps that can be distributed easily. In turn, this makes them a good fit for edge computing solutions.
Edge containers can be deployed in parallel to geographically-diverse points of presence (PoPs) to ensure higher levels of availability compared to a traditional cloud container.
What’s the difference between cloud containers and edge containers?
The key difference between cloud containers and edge containers is location. Cloud containers run in far-off continental or regional data centers but edge containers are actually located at the edge of the network. This means that edge containers are closer to the end-user.
Thanks to this difference (location), edge containers use identical tools as cloud containers do. Consequently, developers can use their existing Docker expertise for edge computing. When it comes to container management, organizations can use a Web UI, terraform, or a management API.
Finally, edge containers can be monitored with proves and their usage can be analyzed with real-time metrics.
Pros and cons of edge containers
First, let’s list a few advantages of edge containers:
- Edge containers provide significantly low latency since they are located just a few hops away from the end-user.
- Traffic can be distributed globally to the nearest container with a single Anycast IP.
- Since an edge network has more PoPs than a centralized cloud, edge containers can be deployed to multiple locations at once. This gives organizations a chance to better meet regional demands.
- Container technologies such as Docker are seen as mature and battle-tested. On top of that, no retraining is needed so developers testing edge containers can use the same Docker tools they are familiar with.
- Centralized apps can have high network charges since all traffic is concentrated in the cloud vendor’s data center. Edge containers are close to the user and they can provide pre-processing and caching.
And here are some drawbacks:
- If you plan on having multiple containers spread among many regions, you better plan it out carefully and monitor everything since the process is a bit complex.
- The sheer size of the network makes the attack surface more extensive. Therefore, configuring secure network policies is quite important.
- Edge containers have separate charges for traffic between PoPs, which should be considered aside from regular ingress and egress charges.
Container images creation
Usually, container images are created from a Dockerfile. The focus is placed on this technology just to keep everything simple and easy to understand.
Dockerfiles are text files containing commands in order to determine how the image should be built.
Every line of a Dockerfile has an instruction that creates a new read-only layer of the image, built from the previous layer of the image, or in the case of a FROM instruction, an image specified in the Docker file.
In addition, every line of the Dockerfile corresponds to a layer of the image that is created when the Dockerfile is built. This allows users to build from other images, extending their functionality. Docker also provides a library of official images that are regularly updated and are very useful to build from.
Container hosting platforms
Containers are used in a large variety of ways by public cloud service providers like AWS, Google, Microsoft Azure, IBM BlueMix, Oracle, etc. to manage web and mobile applications at scale for enterprise corporations and start-up companies.
DevOps teams use containers to guarantee that a web server will be installed with a specific stack of software that contains all of the required dependencies for the code.
Continuous Integration/Continuous Delivery (CI/CD) requirements for Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS) products require development teams to issue regular version upgrades with security patches, bug fixes, new features, updated content design, etc., which necessitates coordination between distributed programming teams.
VPS resources, however, stay ‘always on’ with purposely over-provisioned system hardware allocation. However, many web hosting companies have already integrated OS installations from disk image collections to their cloud VPS hosting platform software with the web browser UI support for more efficient systems administration options.
The most popular container platform is Docker. It uses the Docker Runtime Engine as an alternative to a hypervisor like KVM, Xen, or Microsoft Hyper-V for virtualization.
Many companies run Docker with a scaled-down operating system like Rancher, CoreOS, SUSE MicroOS, VMware Photon, or Microsoft Windows Nano. Containers are also used with OpenStack, CloudStack, and Mesosphere DC/OS installations for large scale cloud orchestration of data center networks.
These networks frequently include multiple data centers internationally and load balancing software with additional optimizations for web traffic support on hardware.
The main advantage of container hosting
The main advantage of container hosting plans is the ability for companies to provision elastic web server clusters with auto-scaling, load balancing, and multiple data center support for complex web/mobile app deployments.
Elastic cluster servers can support dedicated server workloads with more efficient resource allocation for uptime & downtime traffic. ‘Pay-as-you-go’ billing is designed to be more cost-efficient for businesses over dedicated server hardware and in-house data center management.
Platform-as-a-Service (PaaS) options allow smaller businesses to use the same cloud hosting and container orchestration software services as the largest enterprise companies use in production at an affordable or entry-level cost.
This also makes it easy for small businesses and start-ups to develop new software for web/mobile applications using distributed programming teams and DevOps tools.