Why DevOps?
Why DevOps and how your Business can leverage in DevOps Environment?
Whether you are a project manager or entrepreneur looking to develop your software Product to scale your business globally, it very important for you to understand what is a devops tech company, and why you must hire them over ordinary tech.
What is DevOps?
The term DevOps is relatively new and broadly misunderstood even today by my Organizations, people think of DevOps as just an IT role, more specifically as a hybrid between a developer and a systems administrator.
What is a Silo and how DevOps can be a rescue?
Companies tend to create a new silo called DevOps and try to fill this silo with super-administrators who are magically awesome at both development and operations. Sometimes it is easier to find a unicorn. DevOps is not a group neither a role, DevOps is a culture shift or a new way of thinking about how we develop and deploy/release software. The DevOps movement is about tearing down silos and fostering communication and collaboration between development, where operations, quality assurance, product, and management were dreadfully degraded.
Why Developing on a DevOps environment should be the Mind-Set of a Tech Entrepreneur?
Beginning of The Devops.
The first conference was held in Belgium in the year 2009, by John Allspaw and Paul Hammong titled as “10 deploys per day “where Dev and Ops Cooperation at Flickr,” got together to discuss how to create a more collaborative culture among developers and operations. On Twitter, attendees of the conference used the hashtag DevOps to discuss the conference online. The topic gain massive support as more DevOps Days sprung up across the globe. Eventually, the hashtag became the name of this new movement.
Now resentment of tech companies has been solved by the devops environment, whereas earlier they were facing setbacks in their entire development and operation process due ineffective communication, where Systems become fragile due to software being built in silos where the different teams are not communicating effectively
Why devops environment is so important?
The DevOp environment focuses primarily on a system thinking approach.
The Early innovators in this space coined the term CAMS, which stands for culture, automation, measurement ,and sharing. The goal of DevOps is not to hire superhuman people who are experts at development and operations; instead, the goal is to build systems with a mind-set that the needs of development, operations, and quality assurance are all interrelated and need to be part of a collaborative process. No longer will developers only be responsible for code, testers only be responsible for testing, and operations only be responsible for operating the system.
In a DevOps culture everyone is responsible and accountable for the entire system. Everyone is on a shared mission with shared incentives. Everyone is responsible for delivery and quality. DevOps thinking as described by Gene Kim, a notable author and practitioner of DevOps, can be boiled down to these four principles:
1. Understand the flow of work.
2. Always seek to increase flow.
3. Don ’t pass defects downstream.
4. Achieve a profound understanding of the system.
These principles apply to the entire team. Whether a person is in development, operations, or product, each member of the team should fully understand how the system flows, proactively find ways to improve that flow and eliminate waste, and understand the entire system top to bottom. In addition, the team must insist that defects are not allowed to live on forever because the longer they stick around, the more expensive and complex they are to fi x, resulting in unplanned work in the future. Building and releasing software is a similar process to manufacturing and shipping products. In fact, the DevOps movement is greatly influenced by lean manufacturing principles.
What should be the main focus of Devops Environment?
One of the main focuses in the DevOps movement is to maximize the flow of software creation from concept to development to release. To accomplish this goal, teams should focus on the following six practices:
1. Automate infrastructure
2. Automate deployments
3. Design for feature flags
4. Measure
5. Monitor
6. Experiment and fail fast
Automate Infrastructure
One of the great advantages of cloud computing is that infrastructure can be abstracted via APIs, thus empowering us with the ability to treat infrastructure as code. Since provisioning and deprovisioning infrastructure can be scripted, there is no excuse not to automate the creation of environments.
In fact, we can build code and environments at the same time. A best practice is to enforce the policy that every sprint that ends with a complete set of code should also include the corresponding environment, as well. By enforcing this policy, the user stories in the sprint should include the necessary development, operations, and quality assurance requirements. By delivering the code and its test harnesses with the environment we greatly increase the flow of our work.
In the old days, we would deliver the code, and throw it over the wall to quality assurance, which then threw it over the wall to the operations team that would have to stand up the appropriate environment. Due to a lack of collaboration and communication between these silos, a lot of back-and-forth meetings, phone calls, and e-mails were required in order for operations to attempt to manually create the correct environment. This often led to bottlenecks and environmental issues, since the operations team was not involved in the early discussions.
To make matters worse, once the environment was finally completed, the code that was deployed to it was running in this environment for the first time, which usually introduced new bugs late in the project life cycle. Finding bugs late in the life cycle caused teams to prioritize these bugs, only fi x the critical ones, and shove the rest into the backlog with tons of other bugs from previous releases that may never make it to the front of the priority list. This is obviously not the way to create quality and speed-to-market. Operations should empower development to create their own environments,
but in a controlled fashion. Providing self-service infrastructure is another great way to increase the flow of development; however, without the right level of governance, self-service can lead to chaos, inconsistent environments, nonoptimized costs, and other bad side-effects. The way to properly allow for self-service provisioning is to create a standard set of machine images that people with the proper access can request on demand. These machine images represent standard machines with all of the proper security controls, policies, and standard software packages installed. For example, a developer may be able to select from a standard set of machine images in a development or quality assurance environment for a web server running Ruby, an application server running NGINX, a database server running MySQL, and so on. The developer does not have to configure any of these environments. Instead. The just requests an image and a corresponding target environment. The environment gets automatically provisioned in a few minutes and the developer is off and running. What I just described is how self-service provisioning can work in an Infrastructure as a Service (IaaS) model. In a Platform as a Service (PaaS) model, developers with the appropriate access to nonproduction environments can perform the same self-service functionality using the PaaS user interface.
Automate Deployments
Automating deployments is another critical task for increasing the fl ow of software development. Many companies have perfected automation deployments to the point where they deploy multiple times a day. To automate deployments, the code, configuration files, and environment scripts should share a single repository. This allows the team to script the deployment process to perform both the build and the corresponding environment at the same time. Automating deployments decreases cycle times because it removes the element of human error from deployments. Faster and better-quality deployments allow teams to deploy more frequently and with confidence. Deploying more frequently leads to smaller change sets, which reduces the risk of failure.
In the old days, deployments were cumbersome manual processes that usually had a dependency on specific people who were knowledgeable about the steps involved to deploy a build. The process was not repeatable because of the manual intervention required and deployments were often dreaded exercises that occurred late at night or early in the morning and involved urgent bug fixing after experiencing issues with the deployment. Since the deployments were challenging and buggy, teams often chose to deploy less frequently due to the fear of breaking the production system. Automated deployments aim to resolve all of these issues. Automation takes the art out of deployments and makes it easy enough that anyone with the right permissions can deploy software by simply picking a version and an environment and clicking a button. In fact, some companies that have mastered automation require new hires to perform a deployment in a nonproduction environment as part of their training on their first day of work.
Design Feature Flags
Another new trend for modern-day deployment methodologies is the use of feature flags. Feature flags allow features to be configured to be turned on or off or to only be available to a certain group of users. This is useful for a couple of reasons. First, if a feature has issues, once it is deployed it can be quickly configured to be turned off. This allows the rest of the deployed features to remain running in production and gives the team time to fix the issue and redeploy the feature when it is convenient. This approach is much safer than having a team scramble to quickly fix a production issue or cause the entire release to be backed out. Another use of feature flag is to allow a feature to be tested in production by a select group of users. For example, imagine our fictitious auction company, Acme e-Auctions, is launching a new auction feature that allows the person leading a live auction to activate a webcam so the bidding customers can see her. With the feature flag and a corresponding user group setting this functionality can be turned on for just employees so they can run a mock auction in production and test out the performance and user experience. If the test is acceptable, they may choose to allow the feature to run in a select geography as a beta test to get feedback from customers before rolling it out to all users.
Measure, Monitor, and Experiment
We discussed at length measuring and monitoring in Chapter 12. The point to add here is that by leveraging feature flags, we can run experiments like A/B testing to gather information and learn about the system and its users. For example, let ’s say that a product manager has a theory that the registration process is too complex for some users and she wants to test a new, simpler registration form. By leveraging feature flags and configurations, the new registration page can be configured to display every other time a registration page is requested so that the team can compare the user metrics of the new registration page against the user metrics of the existing registration page.
Another option would be to test the feature in specific geographies, within specific time frames, or for specific browsers or devices. Feature flags can also be used to test features in production against real production loads.
The feature can be enabled for a test group or as a beta launch to a select location. Once enabled, the feature can be closely monitored and turned off once enough data is collected or if any issues are detected.
DevOps cultures encourage this type of experimentation. Fail fast is a common phrase used in DevOps. With one-click automation of infrastructure and deployments along with the configurability of feature flags, teams can quickly experiment, learn, and adjust, which leads to a better product and happier customers.
Continuous Integration and Continuous Delivery
In our discussion on automation we touched on the automation of environments and builds. Let ’s dig deeper into this topic. Continuous integration (CI) is the practice of building and testing applications on every check-in. No matter how big or small the change is, the developers need to be conditioned to always check in their work.
Continuous delivery (CD) takes this concept one step further and adds automated testing and automated deployment to the process in addition to CI. CD improves the quality of software by ensuring testing is performed throughout the life cycle instead of toward the end. In addition, the build process fails if any automated test fails during the build process. This prevents defects from being introduced into the build, thus improving the overall quality of the system. By leveraging CD, we get software that is always working, and every change that is successfully integrated into a build becomes part of a release candidate.
In the old days, bug fiXes that took only a few minutes often had to wait For many other user stories to be completed so they could be packaged up in a big release. In that model, software was assumed to be incorrect until it was validated by dedicated quality assurance professionals. Testing was a phase that was performed after development and the responsibility of quality fell in the hands of the quality assurance team. Developers often threw poor-quality code over the wall to quality assurance in order to meet the development deadlines with little to no repercussions for the quality of their work. Quality assurance often had to cut corners to complete testing to get the code to operations in time to release the software. This resulted in known bugs being allowed to fl ow into the production system. These bugs would go through a prioritization process where only the most critical bugs would be addressed so that the project data would not be missed or would not slip further. With CD, software is assumed to be correct unless the automation tells us otherwise. Quality is everyone ’s responsibility and testing is performed throughout the life cycle. To successfully run projects using continuous delivery, there must be a high level of communication and collaboration along with a sense of trust and ownership throughout the team. In essence, this is the type of culture that the DevOps movement represents.
So, what does all of this stuff have to do with cloud computing? A DevOps culture, continuous integration, and continuous delivery are not mandatory for building software in the cloud. In fact, to large, established companies with tons of process and long delivery cycles this may all sound more like a fantasy than reality. But all three of these buzzwords evolved from innovative practitioners leveraging one of the biggest advantages of cloud computing, infrastructure as code, and putting it to use with some tried-and-tested best practices from lean manufacturing. One of the biggest promises of cloud computing is agility. Each cloud service model provides us with an opportunity to get to market faster than ever before. But it takes more than the technology to realize that agility. As every enterprise architect knows, it takes people, process, and technology. The technology is here now. People like you are reading books like this because you want to learn how to take advantage of this amazing technology to achieve business goals. But without good process, agility will be hard to come by. Here is a real-life example. A client of mine built an amazing cloud architecture that changed the business landscape in its industry. This client turned the business model upside down within its industry, because all of its competitors had legacy systems in massive data centers and large investments of infrastructure spread throughout retail customer stores. This client built an entire solution in a public cloud and required no infrastructure at the retail stores, resulting in quicker implementations, drastically lower costs, and more flexibility. Unfortunately, as my client grew from a small start-up to a large company it did not establish a mature set of processes for builds and deployments. It created a silo of operations personnel, dubbed “DevOps.” Developers threw code over the wall to quality assurance, which threw it over the wall to DevOps. DevOps became a huge bottleneck. The goal of this team was to automate the builds and
the deployments. The problem was that it was not a shared responsibility. Everything fell into this group ’s lap and it could only chip away at the problem. The end result was a lot of missed deadlines, poor success rates of deployments, poor quality, angry customers, and low morale. Even though the company’s technology was superior to the competition, the bottlenecks within IT were so great that it could not capitalize by quickly adding more features to differentiate itself from the market even more. The moral of the story is cloud technologies by themselves are not enough. It takes great people, a special culture of teamwork and ownership, and great processes, which should include as much automation as possible inorder to achieve agility in the cloud.
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