Ku­ber­netes vs. Docker - What’s the dif­fer­ence?

Docker is a platform for creating, packaging, and running ap­pli­ca­tions in con­tain­ers, while Ku­ber­netes is an or­ches­tra­tion system that manages and scales those con­tain­ers. In other words, Docker handles the con­tainer­iza­tion of ap­pli­ca­tions, and Ku­ber­netes takes care of au­to­mat­i­cal­ly deploying, or­ga­niz­ing, and scaling them.

What are the dif­fer­ences? Ku­ber­netes vs. Docker

Docker has achieved a small rev­o­lu­tion with the de­vel­op­ment of container tech­nol­o­gy. For work in software de­vel­op­ment, vir­tu­al­iza­tion with self-contained packages (the con­tain­ers) offers com­plete­ly new pos­si­bil­i­ties. De­vel­op­ers can easily bundle ap­pli­ca­tions and their de­pen­den­cies in con­tain­ers, ensuring that vir­tu­al­iza­tion can occur at the process level. Although there are a number of Docker al­ter­na­tives, the open-source solution Docker remains the most popular platform for creating con­tain­ers.

Ku­ber­netes, on the other hand, is an ap­pli­ca­tion for or­ches­tra­tion (that is, man­age­ment) of con­tain­ers; the program itself does not create the con­tain­ers. The or­ches­tra­tion software accesses the existing container tools and in­te­grates them into its own workflow. Thus, con­tain­ers created with Docker or another tool are easily in­te­grat­ed into Ku­ber­netes. Then, you use or­ches­tra­tion to manage, scale, and move the con­tain­ers. Ku­ber­netes ensures every­thing runs as desired and also provides re­place­ments if a node fails.

Use cases for Docker and Ku­ber­netes

In the com­par­i­son of Docker vs. Ku­ber­netes, it is no­tice­able that the two tools differ in their use cases but work hand in hand. To un­der­stand the different functions of Docker and Ku­ber­netes, let’s look at an example.

Most ap­pli­ca­tions today are organized with mi­croser­vice ar­chi­tec­tures because this ar­chi­tec­tur­al style allows for better scal­a­bil­i­ty, flex­i­bil­i­ty, and main­tain­abil­i­ty by breaking down complex systems into smaller, in­de­pen­dent services.

Step 1: Program mi­croser­vices and create con­tain­ers

In the first step, the ap­pli­ca­tion must be pro­grammed; the team develops the in­di­vid­ual mi­croser­vices that make up the app. Each mi­croser­vice is written as a stand­alone unit and has a defined API for com­mu­ni­ca­tion with other services. Once the de­vel­op­ment of a mi­croser­vice is completed, it is con­tainer­ized with Docker. Docker allows mi­croser­vices to be packaged into small, isolated con­tain­ers that contain all necessary de­pen­den­cies and con­fig­u­ra­tions. These con­tain­ers can then be run in any en­vi­ron­ment without com­pli­ca­tions arising from different system con­fig­u­ra­tions.

Step 2: Configure or­ches­tra­tion with Ku­ber­netes

After the mi­croser­vices have been suc­cess­ful­ly con­tainer­ized, Ku­ber­netes comes into play. In the next step, the team creates Ku­ber­netes con­fig­u­ra­tion files that specify how the con­tain­ers (in Ku­ber­netes lingo, these are also called Pods) should be deployed across different servers. The files include details such as how many instances of a par­tic­u­lar pod should be run, what network settings are required, and how com­mu­ni­ca­tion between the mi­croser­vices works.

Ku­ber­netes takes care of the automatic man­age­ment of these con­tain­ers. If a mi­croser­vice fails or a container crashes, Ku­ber­netes ensures that the container is au­to­mat­i­cal­ly restarted, allowing the ap­pli­ca­tion to continue func­tion­ing without system outages. Ad­di­tion­al­ly, Ku­ber­netes can perform the function of a load balancer and dis­trib­ute con­tain­ers across multiple servers to ensure better uti­liza­tion and scal­a­bil­i­ty. If traffic for the ap­pli­ca­tion increases, Ku­ber­netes can au­to­mat­i­cal­ly start new pods.

Step 3: Updates

With Ku­ber­netes, not only is the de­ploy­ment of con­tain­ers sim­pli­fied, but also the man­age­ment of updates. If the de­vel­op­ers want to bring new code into pro­duc­tion, Ku­ber­netes can gradually replace the con­tain­ers with the new version without causing downtime. This ensures the ap­pli­ca­tion remains con­stant­ly available while new features or bug fixes are im­ple­ment­ed.

Direct com­par­i­son of Ku­ber­netes vs. Docker

Docker Swarm, the Ku­ber­netes al­ter­na­tive

Even though Ku­ber­netes and Docker work won­der­ful­ly together, there is still a com­peti­tor for the or­ches­tra­tion tool: Docker Swarm combined with Docker Compose. While Docker can handle both solutions and even switch between the two, Docker Swarm and Ku­ber­netes cannot be combined. Therefore, users often face the question of whether to rely on the very popular Ku­ber­netes or to use Swarm, which is part of Docker.

The structure of the two tools is es­sen­tial­ly very similar – only the names of the in­di­vid­ual aspects change. The purpose is also identical, which is to manage con­tain­ers ef­fi­cient­ly and ensure the most eco­nom­i­cal use of resources through in­tel­li­gent scaling.

Swarm reveals ad­van­tages in in­stal­la­tion: Since the tool is an integral part of Docker, the tran­si­tion is very easy. While you have to set up or­ches­tra­tion with Ku­ber­netes first—which ad­mit­ted­ly isn’t very complex—every­thing is already there with Swarm. Since you are most likely already working with Docker in practice, you don’t need to fa­mil­iar­ize yourself with the specifics of a new program.

Ku­ber­netes shines with its own GUI: The ac­com­pa­ny­ing dashboard provides not only an excellent overview of all aspects of the project but also enables the com­ple­tion of numerous tasks. Docker Swarm, on the other hand, offers such con­ve­nience only through ad­di­tion­al programs. Ku­ber­netes also stands out in terms of func­tion­al­i­ty: unlike Swarm, which needs extra resources for mon­i­tor­ing and logging, Ku­ber­netes includes these ca­pa­bil­i­ties by default as part of its core features.

The main benefit of both programs lies in scaling and ensuring avail­abil­i­ty. It is said that Docker Swarm is generally better in terms of scal­a­bil­i­ty. This is due to the com­plex­i­ty of Ku­ber­netes, which leads to a certain slug­gish­ness. However, the complex system ensures that automatic scaling with Ku­ber­netes is better. Ad­di­tion­al­ly, a sig­nif­i­cant advantage of Ku­ber­netes is that it con­tin­u­ous­ly monitors the state of the con­tain­ers and directly com­pen­sates for any failures.

Swarm has an edge in load balancing as it provides even dis­tri­b­u­tion right out of the box. With Ku­ber­netes, achieving load balancing requires an extra step—de­ploy­ments need to be converted into services before traffic can be evenly dis­trib­uted.