Select Page

Enterprise Environments: Understanding Deployment at Scale

04

JANUARY, 2021

by Ukpai Ugochi

Have you ever wondered what would happen if you mistakenly added bugs to your codes and shipped them to users? For instance, let’s say an IT firm has its primary work tree on GitHub, and a team member pushes codes with bugs to the primary work tree. The firm may also push the bug-infested software to users without knowing. Users will complain to the firm about the bug, but the problems may take a while to fix, especially if team members don’t work on weekends. This act can earn companies a bad reputation, since it means customer needs go unmet.

So, which aspects of software deployment should IT firms be very mindful about? Why is it necessary to be careful about the codes team members deploy? And how scalable can deploying codes be? These questions may seem overwhelming. Join this ride to see how your organization can deploy codes with the best results.

 

What Is Deployment?

Let’s say that your DevOps team works together on different sections of software. Maybe some team members work on the front end, others work on the back end, and still others validate and test codes. Developers spend lots of time and energy to write codes, test them, and make sure they’re clean. However, developers can’t measure the performance of the software they’re building merely by looking at how clean their code is. What about API (application programming interface) end points? How will developers make sure there are no broken links and the application works as expected in the targeted device or devices?

 

As a result of these uncertainties, codes need to be hosted in a target device or in servers online. What this means is that even as software developers have created workflows that make software development easier, testing the functionality of an application in a targeted device is still a priority in IT firms.

 

Software or application deployment simply involves making the software or application ready for use by hosting it online or in a target device. When an application is deployed online, users can access and use the software as long as they accept the firm’s terms and conditions. An example is when the first version of GitHub was deployed in 2008, only then did users have access to use it.

 

Firms can also deploy new features of an application online after first deploying it on target devices and testing it internally. With test methods put in place and the use of different hosting services, IT firms can deploy continually and pay as they go, or they can choose to pay a fixed amount for a period of time.

What Deployments Tell Us About Enterprise Environments

Before we can fully understand what deployment tells about an enterprise environment, let’s understand what an enterprise environment is. The term refers to the techniques, tools, and procedures an organization uses. For IT firms, it refers to all the processes and tools used during and after software development.

 

What, then, does software deployment tell use about the tools and processes that IT firms use? Why will IT firms use different deploy tools for their different applications? Let’s look at the life cycle of software and how deploy processes can make or mar software releases.

It All Starts With the Code

Of course, the first step to designing and building a computer program is writing codes. The codes software developers write make up the software to be released. Most times, developers work on asynchronous development tools like GitHub and have to work asynchronously, sometimes remotely.

 

Because different team members work on different functionalities of the application, the team lead needs to monitor team members’ codes. The reason firms ship software with bugs to users is that during this tracking of codes, some of the improper and bad codes never got fished out. Therefore, firms need to monitor codes before merging them with the primary code tree.

Testing and Debugging

Whether your organization uses agile or DevOps, testing of team members’ codes after they push them should be a priority. Testing of codes involves evaluating codes to make sure they return the required results when executed. Aside from testing codes, developers test the functionality of the application. This type of test is to make sure software completes the tasks it’s supposed to.

 

Debugging is the next step after testing—fixing errors that emanate from testing. After this stage, the developer sees all the flaws, faults, and errors within the code. With Enov8 test monitoring tools, you can initiate testing of codes while integrating them with tools like Borland, Splunk, and so on.

Building

After writing and testing codes, you’ll need to compile and build them. Building codes involves putting individual units of code together so that software runs properly. Most times, a single developer can build codes using an IDE (integrated development environment).

 

Builds are usually prerelease software versions that only the software companies use. Developers need to deploy software to allow customers to use them. You’re probably wondering why developers need to deploy software before users can use it—after all, the act of building compiles the software.

 

Here’s the catch. For web applications, developers compile codes and then install them in servers for global use. In contrast, for desktop applications, developers build codes with build tools and then ship them to users with instructions on how to install or deploy them in the work environment. Tools such as benchmark release management let organizations monitor and get metrics of the build process.

Deploying

After the build process, deploying software is the next step. To deploy usually involves installing software so people can use it on a computer or target device. Deploying can either be on servers online or on a target device. It’s usually in users’ working environment.

 

Developers can also deploy software in their working environment to test software functionality. In this case, the developer is the user. All the processes for installing and running software in a specific environment are part of deployment. Software deployment is also related to software releasing because software releasing involves redeploying software with new features.

Redeploying and Maintaining

Software maintenance is almost synonymous with redeploying, in my opinion. This is because while maintaining software, developers correct faults, enhance UI/UX, and add new features. How will these new features get to users if developers don’t deploy them?

 

Redeploying involves pushing software codes again after each change to reflect changes in users’ copies. Sometimes redeploying codes are automatic, but it’s also possible to do them manually.

How to Scale Up Deployment

Deploying software shouldn’t be taken lightly. It ushers the software to users. A bad deployment can ruin the trust users have in the company. And what about the money it could cost your organization if software takes up unnecessary memory space on the server? Let’s dive into the different methods to scale up deployment—the do’s and don’ts for a successful software deployment.

Step 1: Automate Testing

For a successful deployment, it’s essential to automate testing. The idea of waiting to compile codes before testing is totally wrong because it eats up time. It makes sense to carry out tests after pushing codes. This way, codes that don’t pass tests won’t be accepted into the primary working tree.

 

DevOps teams can automate testing while working with distributed version control systems (DVCS) such as Git, GitHub, and Bitbucket. With this method, testing of codes is continual, so you avoid the rush-hour testing of codes.

Step 2: Automate Deployments With Continuous Integration and Continuous Delivery

To automate deploying, it makes sense to implement continuous integration and delivery. In continuous integration, when team members push codes, the codes undergo tests and are added to the primary working tree. Delivery on the other way round means putting things in place to allow software to be released continually, anytime the team chooses. With this method, the DevOps team can minimize maintenance, maximize innovation, and reduce costs.

Continuous Deployment

There’s a thin line between continuous delivery and continuous deployment. In continuous delivery, the software is ready for release at any time. The act of releasing software to users continually is continuous deployment. With continuous deployment, teams can add new software features, remove bugs, and ship to users swiftly.

Containerization

Bugs used to show up when developers coded in one environment and deployed to another environment. Now, developers can compile codes and related files and dependencies they require to run in different environments, bug free. This method allows software to behave similarly in different operating systems. To use this method, DevOps teams use tools such as Docker, Kubernetes, and so on.

Step 3: Monitoring Deployment

Scaling deployment doesn’t stop at deploying your software. You’ll need to monitor the performance of software after deploying. Also, you’ll need to manage and add new features after deploying (or redeploying).

 

How do you ensure deploying doesn’t fail? What measures do teams need to put in place? With test environment management tools, monitoring software is efficient even after deployment.

Further Reading

Everyone builds projects knowing deployment is inevitable. But not everyone takes deployment procedure seriously. For some, deployment is just a ritual that one must carry out. In this article, we’ve explored why deployment should be a critical process. You’ve seen how DevOps teams can scale up deployment processes and the possible effects of scaling deployment.

 

Want to know more? You can read more about deployment metrics that can aid the optimization of IT operations, giving managers a clear understanding of properties to measure during deployments. You may also want to learn more about metrics for deployment management. And if you want to get a deeper understanding of containerization, this article is a great fit for you.

Ukpai Ugochi

This post was written by Ukpai Ugochi. Ukpai is a full stack JavaScript developer (MEVN), and she contributes to FOSS in her free time. She loves to share knowledge about her transition from marine engineering to software development to encourage people who love software development and don’t know where to begin.

Relevant Articles

What makes a good Test Environment Manager?

07 DECEMBER 2020 by Daniel de Oliveira In today’s application-based world, companies are releasing more applications than ever before. Software delivery life cycles are becoming more complicated. As a result, large companies require hundreds and even thousands of test...

What makes a good Test Data Manager?

19 NOVEMBER, 2020 by Michiel Mulders What Makes a Good Test Data Manager? Have you implemented test data management at your organization? It will surely benefit you if your organization processes critical or sensitive business data. The importance of test data is...

The Pros and Cons of Test Data Synthetics (or Data Fabrication)

22 October, 2020 by Louay Hazami Data privacy is one of the most pressing issues in the new digital era. Data holds so much value for normal internet users and for all types of companies that are looking to capitalize on this new resource. To keep data anonymous and...

Supporting Privacy Regulations in Non-Production

18 SEPTEMBER 2020 by Arnab Chowdhury Every aspect of our daily lives involves the usage of data. Be it our social media, banking account, or even while using an e-commerce site, we use data everywhere. This data may range from our names and contact information to our...

What Makes a Good Enterprise Release Manager?

09 SEPTEMBER, 2020 by Michiel Mulders Do you want your company to scale efficiently? Look for an enterprise release manager (ERM). An ERM protects and manages the movements of releases in multiple environments. This includes build, test, and production environments....

What Is Data Masking and How Do We Do It?

04 AUGUST, 2020 by Michiel Mulders According to the 2019 IBM Data Breach report, the average data breach in 2019 cost 3.92 million USD. Businesses in certain industries, such as healthcare, suffer more substantial losses—6.45 million USD on average. As the amount of...