Make sure you avoid logging information like business names, related personnel (employees, clients, suppliers, etc.), an

There are many container engines available, but the most prominent competitor to Docker is Podman, developed by Red Hat. Unlike Docker, Podman doesn’t need daemon to run and also doesn’t need root privileges which has been long-standing concern with Docker. Based on the name, Podman can not only run containers, but also pods. In case you are not familiar with concept of pods, then pod is the smallest compute unit for Kubernetes. It consists of one or more containers — the main one and so-called sidecars — that perform supporting tasks. This makes it easier for Podman users to later migrate their workloads to Kubernetes. So, as a simple demonstration, this is how you would run 2 containers in a single pod:

In most enterprise applications, for security and compliance reasons, it is mandatory to keep a separate log for data-related operations with all important information like access IDs (user/system), exact service instances and role privileges used, timestamps, data layer queries, and snapshots of both previous and new states of the changed dataset (diff). An audit trail must capture all data-related attempts (access, import, export, etc.), and CRUD operations (creates, reads, updates, deletes) performed by the users, as well as by the other systems and services.

First, let me introduce Buildah. Buildah is another tool developed by Red Hat and it plays very nicely with Podman. If you already installed Podman, you might have even noticed the podman build subcommand, which is really just Buildah in disguise, as its binary is included in Podman.

rkt — rkt (“rocket”) is container engine developed by CoreOS. This project is mentioned here really just for completeness, because the project ended and its development was halted — and therefore it should not be used.

System events must capture information on behaviour events (startups, stops, restarts, security events), changeover modes (cold, warm, hot), inter-service communication (handshakes, connection building statuses — connect, disconnect, reconnect, retry events), service instance IDs, actively serving APIs, actively listening IP and port ranges, configurations loaded (initial load up and dynamic updates), overall service health, and anything that helps to understand the behaviour of the system.

LXD — LXD is container manager (daemon) for LXC (Linux Containers). This tool offers ability to run system containers that provide container environment that is more similar to VMs. It sits in very narrow space and doesn’t have many users, so unless you have very specific use case, then you’re probably better off using Docker or Podman.

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file with two stages: in the first one we compile the project and in the second one we deploy the application on the web server. However, a Node container is not the best option to serve web pages (HTML, CSS and JavaScript files, images, etc.), the best option would be to use a server like Nginx or Apache. In this case I will use Nginx.

Almost all the privacy laws (e.g., GDPR, CCPA) clearly advise developers to keep PII away from the logs. PII includes information like first name, last name, username, gender, birthday, mailing and billing addresses, emails, phone numbers, social security numbers (SSN), and credit card numbers.

CRI-O — When you google what is cri-o, you might find it described as container engine. It really is container runtime, though. Apart from the fact that it isn’t actually an engine, it also is not suitable for “normal” use. And by that I mean that it was specifically built to be used as Kubernetes runtime (CRI) and not for an end-user usage.

Every application has its unique business cases and user journeys, and they reveal many insights for the domain experts in the system. For instance, whether a certain transaction takes too long or the end users get stuck at some functionality all the time are very critical pieces of information in terms of user experience. Other business-related information, like transaction volumes and active users and their stages, is important for deriving business insights and even can be used for business intelligence purposes too.

As for its features, it follows same route as Podman — it’s daemonless and rootless and produces OCI compliant images, so it’s guaranteed that your images will run the same way as the ones built with Docker. It’s also able to build images from Dockerfile or (more suitably named) Containerfile which is the same thing with different name. Apart from that, Buildah also provides finer control over image layers, allowing you to commit many changes into single layer. One unexpected but (in my opinion) nice difference from Docker is that images built by Buildah are user specific, so you will be able to list only images you built yourself.

Revealing threats and vulnerabilities with the help of application runtime and log messages is an art that every enterprise software developer must learn. In general, security breaches and catastrophic failures in applications do not happen suddenly. Most of the time, there are some clues that no one notices in the first place. Therefore we must always log suspicious human activities (e.g., failed authentication and verification attempts with all low-level information like networks used, request origins, and user roles and privileges attached) as well as the system behaviours (e.g., increasing of spikes in resource consumption patterns, high loads on web servers, services getting choked randomly). When a suspicious event is noticed, make sure the logs capture all information related to it, ideally a full-stack trace including parameter values and additional information available from the application context.

Diligence is a great characteristic of computing devices, but they may not be as perfect as we were taught at school. Performance anomalies or sudden unexpected degradations in services (mostly due to unhandled errors and corrupted data) can happen at any given time. To identify them, it is always recommended to publish stats on overall system health and performance. Such stats may include information like API calls counts (both successfully served ones and a separate failure count), network latencies, average roundtrip times, memory consumption, and other application-specific information (mostly decided by the business context).

There are other container engines besides Docker and Podman, but I would consider all of them a dead-end tech or not a suitable option for local development and usage. But to have a complete picture, let’s at least mention what’s out there:

When comparing Docker with any other tool we need to break it down by its components and first thing we should talk about are container engines. Container engine is a tool that provides user interface for working with images and containers so that you don’t have to mess with things like SECCOMP rules or SELinux policies. Its job is also to pull images from remote repositories and expand them to your disk. It also seemingly runs the containers, but in reality its job is to create container manifest and directory with image layers. It then passes them to container runtime like runc or crun (which we will talk about little later).