🔥Edureka DevOps Training: https://www.edureka.co/devops-certifi…
This Edureka “Mainframe DevOps Tutorial” session will provide teams struggling to incorporate mainframe development and operations into their enterprise DevOps programs with pragmatic, real-world guidance. Following are the topics covered in the session:
Introduction to Mainframe
Need for Mainframe
Mainframe DevOps Adoption Strategy
Mainframe DevOps Tools
DevOps and Cloud computing are joined at the hip, now that fact is well appreciated by the organizations that engaged in SaaS cloud and developed applications in the Cloud. During the COVID crisis period, most of the organizations have started using cloud computing services and implementing a cloud-first strategy to establish their remote operations. Similarly, the extended DevOps strategy will make the development process more agile with automated test cases.
According to the survey in EMEA, IT decision-makers have observed a 129%* improvement in the overall software development process when performing DevOps on the Cloud. This success result was just 81% when practicing only DevOps and 67%* when leveraging Cloud without DevOps. Not only that, but the practice has also made the software predictability better, improve the customer experience as well as speed up software delivery 2.6* times faster.
3 Core Principle to fit DevOps Strategy
If you consider implementing DevOps in concert with the Cloud, then the
below core principle will guide you to utilize the strategy.
Guide to Remold Business with DevOps and Cloud
Companies are now re-inventing themselves to become better at sensing the next big thing their customers need and finding ways with the Cloud based DevOps to get ahead of the competition.
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From conceptualization to deployment, the process of developing software applications or web applications is complex. By going through several intricate phases of development, a web application or software is tested on multiple levels before being proceeded into production.
In most cases, software application development becomes time-consuming due to its specifications and complexities. In order to deliver the application in a short span of time, software developers are following a universal set of practices called the DevOps lifecycle.
So, what is DevOps in the world of software application development? Let’s deep dive into its meaning, uses, as well as each critical phase in the DevOps lifecycle.
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Once an industry term becomes popular, particularly in technology, it can be difficult to get an accurate definition. Everyone assumes that the basics are common knowledge and moves on. However, if your company has been discussing DevOps, or if you are interested in learning more about it, here are some basics you should know.
DevOps refers to the restructuring of the traditional software application cycle to support Agile development and continuous improvement/continuous delivery. Traditionally, the software was created in large-scale, monolithic bundles. New features and new releases were created in large packages and released in full-scale, infrequent, major deployments.
This structure is no longer effective in the modern business environment. Companies are under increasing pressure to be agile. They must respond rapidly to changes in the business environment to remain competitive. Software development needs to be completely changed as a process so that incremental improvements can be made frequently – ideally, several times per day.
However, changing a development lifecycle completely requires major changes – in people and culture, process, and enabling tooling – to be effective. DevOps was created by the breaking down of cycles between development and operations, combining two separate functions in application development. These changes intend to support agile, secure, continuous improvements, and frequent releases.
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DevOps is supposed to help streamline the process of taking code changes and getting them to production for users to enjoy. But what exactly does it mean for the process to be “streamlined”? One way to answer this is to start measuring metrics.
Metrics give us a way to make sure our quality stays the same over time because we have numbers and key identifiers to compare against. Without any metrics being measured, you don’t have a way to measure improvements or regressions. You just have to react to them as they come up.
When you know the indicators that show what condition your system is in, it lets you catch issues faster than if you don’t have a steady-state to compare to. This also helps when you get ready for system upgrades. You’ll be able to give more accurate estimates of the number of resources your systems use.
After you’ve recorded some key metrics for a while, you’ll start noticing places you could improve your application or ways you can reallocate resources to where they are needed more. Knowing the normal operating state of your system’s pipeline is crucial and it takes time to set up a monitoring tool.
The main thing is that you decide to watch some metrics to get an idea of what’s going on when you start the deploy process. In the beginning, it might seem hard to figure out what the best metrics for a pipeline are.
You can conduct chaos engineering experiments to test different conditions and learn more about which metrics are the most important to your system. You can look at things like, time from build to deploy, number of bugs that get caught in different phases of the pipeline, and build size.
Thinking about what you should measure can be one of the harder parts of the effectiveness of the metrics you choose. When you’re considering metrics, look at what the most important results of your pipeline are.
Do you need your app to get through the process as quickly as possible, regardless of errors? Can you figure out why that sporadic issue keeps stopping the deploy process? What’s blocking you from getting your changes to production with confidence?
That’s how you’re going to find those key metrics quickly. Running experiments and looking at common deploy problems will show you what’s important early on. This is one of the ways you can make sure that your metrics are relevant.
#devops #devops-principles #devops-tools #devops-challenges #devops-adoption-challenges #devops-adoption #continuous-deployment #continuous-integration
DevOps is a new catalyst that is rapidly spreading throughout the tech industry. Over the years it has gained much popularity and everyone has their own interpretation of it. It emerged a few after agile programming practices, and nowadays people are trying to figure out the relevance of enterprise DevOps. Before we move on to that, we first need to understand DevOps, its culture, and some other aspects.
There are many forms of divides in the tech industry. DevOps concepts solve this one in particular. Therefore, to understand and fully appreciate DevOps we first need to focus on this dispute. Within any software company, there has long been a divide between the development and operations teams.
Development teams are responsible for creating feature-rich, seamless integrations that have varying requirements with each new customer. They’re responsible for changing user requirements, maintenance, and continuous development activities. The takeover at the start of the SDLC development cycle.
On the other hand, Operation teams are primarily responsible for system stability and accessibility. They come in towards the end of the process where handover of a software release is given. Their responsibility is reviewing implementations by the development teams and ensuring the system is accessible and stable, and recommend changes if necessary.
To break the silos between Dev and Ops DevOps takes a few leaps, enabling better collaboration and performance.
The agile admin defines DevOps as,
DevOps is the practice of operations and development engineers participating together in the entire service lifecycle, from design through the development process to production support.
The term “Dev” is an umbrella term for not only developers, but any person included in the development of the product. So, this can include QA engineers, SR engineers, and other disciplines as well. Essentially, the “dev” team are the makers of the product.
Secondly, the term “Ops” covers all operations staff including systems engineers, system administrators, release engineers, network engineers, and all other relevant disciplines. The “Ops” team is responsible for the product after its development is complete.
In conclusion, operations engineers need to adopt the same methods adopted by developers and vice versa. DevOps extends Agile principles beyond just the development stage. Rather it extends it over the boundary of development and onto the entire process up till delivery.
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