A “Dojo” is a gathering place for computer engineers in the field of software development, where they may work together to hone their programming abilities. It is often a venue for learning, experimentation, and cooperation.
A “Kata” is a specialised exercise or challenge that is aimed to assist programmers in improving their abilities via repetition and concentrated practise. Katas can take on a variety of forms. A Kata is often a brief, self-contained issue or activity that can be finished in a short amount of time. Katas are frequently used as a method to teach new strategies or investigate new approaches to problem-solving.
In this section, we go over some basic ideas that are important for putting what you know to use in the real world. The terms “reference architecture,” “landing zone,” “blueprint,” “code templates,” and “scaffolding” are included in this group of ideas, and they are all connected to one another in some way. The following text emphasises the goals of each notion as well as its role in putting together a group that will come up with answers for an organisation. In addition, it is essential to emphasise that the ideas discussed in this article are not the same as those discussed by Microsoft in their Azure Resources section. Starting with reference architecture, which acts as a technical guide on how to solve business problems with technology, the text moves on to landing zones, blueprints, code templates, and scaffolding, providing a detailed explanation of each concept along the way. Reference architecture serves as a technical guide on how to solve business problems with technology. This section acts as a guide for readers who are interested in applying the knowledge they have gained in a practical setting, and each notion plays a vital part in the process of designing and implementing technological solutions.
Mary was working as the DevOps engineer for a company that was expanding, and she was continually having trouble keeping up with the expectations of the company. Because the software used by the organisation was constructed using a wide variety of distinct components and approaches, it is difficult to maintain and keep up to date. To make matters even more difficult, the programme was developed with the intention of functioning across a variety of platforms and technologies, which makes it much more challenging to administer.
One day, Mary’s employer presented her with a new problem, which was that the firm was intending to switch from on premises datacentre to one cloud provider, and they wanted her to ensure that the transfer happened well. Not only did this include modernising the software so that it could operate on the new cloud platform, but it also necessitated transforming the tightly coupe service architecture of the organisation into a micro segmented design that was more adaptable.
| Technology’s choices |
Azure DevOps is a collection of tools and services that can be used to manage the entirety of the software development lifecycle. This includes all stages of the process, from planning to development to testing to deployment. It offers tools for software testing and distribution, as well as capabilities for collaboration, code management, and continuous integration and delivery. In addition, it manages the software. The following is a list of some of the most important features offered by Azure DevOps:
Work item tracking Azure DevOps provides tools for tracking development work, including capabilities for generating and tracking work items like user stories, tasks, and defects. These tools are included in the work item tracking functionality. Work item tracking
Control of versions: Azure DevOps offers support for version control systems, including Git and Team Foundation Version Control. Version control (TFVC). It includes tools for code collaboration, such as the ability to examine the history of the code, track changes, review code, and merge code.
Read the “Technology’s choices” article to have more context Technology’s choices | LinkedIn YAML rather than JSON YAML, which stands for “YAML Ain’t Markup Language,” is a data serialisation language that is legible by humans and is widely used for configuration files. However, YAML may also be used for data storage. It is comparable to JSON in that it is a method for representing data structures; however, it is simpler to work with than JSON since it is more comprehensible to people and contains less unnecessary words. Indentation is used instead of curly brackets to denote structure in YAML, but curly brackets are used in JSON. This is one of the most significant differences between YAML and JSON. This results in an improvement in YAML’s versatility as well as its readability; nevertheless, it also makes it more prone to formatting errors.
Is it possible to employ natural languages in order to make the DevOps machinery better?
Natural language processing (NLP), which is also known as linguistic processing, may, in fact, be utilised to make DevOps operations more efficient. The following is a list of some of the possible applications of natural language processing (NLP): NLP might be used to automatically categorise user requests or tickets and distribute them to the right group or people to be handled. NLP might be used to automatically categorise user requests or tickets and distribute them to the right group or people to be handled.
A manufacturing pipeline is a set of devices that have been put together in order to provide consistent results. This leads one to believe that one device is capable of connecting to or communicating with another, which is evidence that the input and output are compatible with one another. This is the same fundamental concept behind the pipe command in Linux, which joins instructions by making the output of one programme the input for another programme. When discussing the DevOps pipeline, we refer to each device as an action or a combination of activities that comply to a predetermined standard operating procedure (SOP).
In my records I have digital photos since 2000, even that I have been doing photography for more time than that.
I just realize that I’m clicking on a camera, making the shutter work for over 2 decades. In any case I always try to improve bit by bit, photo by photo.
193k is the current number in my photo counter
There is no way that you can make it without automation. The cloud industrialization (revolution) is based on controlled automation.
Zug, Switzerland
