An Introduction to DevOps – Going Prime Time

Caleb Eghan

An Introduction to DevOps

DevOps is primarily concerned with bridging the gap between the development and operations teams. In this Introduction to DevOps we look at how the emergence of various tools, platforms, and services that provide a complex delivery process, the term DevOps has recently gone beyond its original meaning. When it comes to establishing or upgrading your DevOps delivery cycle, you may wish to employ a systematic approach that is both feasible and cost-effective. The DevOps community has shared immense knowledge and roadmaps that address the best practices and technologies required for development and deployment. When implementing DevOps in your firm, there are several main concerns that must be addressed or taken into account.

What do you aim to achieve with DevOps?

When introducing or adopting a particular technical or nontechnical practice into your organization, it is important to outline what problem it is solving within your organization. Is the problem current or anticipated? Which aspect of your software delivery life cycle requires DevOps? As already mentioned, DevOps is a bridge between the development team and the Operations team. Having this in mind, it will be important to look at what problem DevOps is addressing in the development team and what problem DevOps is addressing in the operations team. Again what challenges will DevOps be addressing in the workflow between the development team and the operations team? By addressing the current and future challenges, you get a clear and precise roadmap towards continuous integration and continuous deployment. This means you’ll be able to match each issue to the appropriate tool, service, or platform to address the issues. This will also help prioritize how your budget is tailored towards infrastructure development or hiring.

How will infrastructures, tools, platforms, and services connect?

DevOps has traditionally relied on the availability of security technologies for static or dynamic vulnerability and code quality scanning, test automation, cloud services as a digital infrastructure platform, and code management platforms to handle continuous integration procedures. There are numerous commercial and free technologies available to aid in your continuous integration and deployment process; nevertheless, it is vital to establish a solid technological baseline that guarantees the appropriate tools are adopted and deployed. To do so, consider the benefits and drawbacks of each tool or platform, as well as how adaptable they are when it comes to incorporating them into your organization.

In a situation of continuous integration(committing code, creating branches, cloning repositories, etc. ), you might consider which platform your code will be sitting on, either GitHub, Azure DevOps, Bitbucket, Beanstalk, Jenkins, etc. Whichever platform you choose, consider how it fits into your organization’s DevOps architecture. Also consider flexibility, team ease, and capabilities that are useful for your deployment environment and scalability.

Infrastructure as code is an area that is widely adopted by DevOps teams. This is when the infrastructure set up on a given cloud platform is automated through code. As initially mentioned, DevOps is primarily about automation, this helps save time, ensure consistency, eliminate ambiguity, and maintain precise technical culture among your team. Tools such as Chef, Terraform, Ansible and Puppet, help DevOps teams adopt infrastructure as a code approach.

Infrastructure as code streamlines the process of manually configuring features and services on a cloud platform for your team. Consider needing to set up storage and a virtual machine for each cloud service you use. A manual method to this could take a long time. The process can be set up once and then replayed whenever a similar scenario is required, by using any of the tools mentioned above. This is more of a click-and-play approach, in which the same code is executed repeatedly as needed.

Security is a critical aspect of your DevOps cycle you might not want to downplay. A DevOps cycle with rigorous security in place will ensure:

  • Vulnerability level in a source code is eliminated or
  • A good infrastructure security patches is carried out.
  • There is an early vulnerability insight to infrastructure.
  • You have a secure token and secret management procedure in place.
  • There is a dynamic end-to-end encryption protocol and multi-factor authentication process in place.
  • Code quality check before and after deployment
  • Rigorous identity access management policies.

All these is to ensure there is a security layer at every level and stage of your DevOps delivery process.  Some of the notable vulnerability scanning and code quality check tools include SonarQube, Eze-Cli, Black duck, SQL Map, etc.

Automated and Manual Testing

One thing you might have to consider as you build a fruitful technical culture within your DevOps teams is how testing of digital product or features is carried out. Testing here covers both automated testing and manual testing. Testing provides first-hand insight into the performance of a feature before it gets to either the development or production environment.

Integrating automated testing into your pipelines is helpful to ensure the test conditions of a feature are satisfied before it is deployed to the development or production environment.  Unit testing also ensures each function within your source code is being tested against a given set of parameters or conditions.

Manual testing is also of great benefit as it provides insight into how a feature behaves when used by a customer.

Platform Data Insight and Monitoring

Every step within your DevOps delivery cycle creates data. Data generated at each level or stage of your DevOps cycle is relevant towards enhancing the cycle and decision making, as result, it is a valuable asset In designing your DevOps architecture, you need to consider how you will collect data on what goes on with your continuous integration and deployment process. CICD tracing with open telemetry could provide pipeline build duration insight, deployment logs capturing, service access timeline, and execution logs.  Open telemetry could be integrated into your codebase as it provides SDKs for languages such as Java, Python, Golang, .Net, PHP, JavaScript, etc.

With data analytics tools such as Splunk and Exabeam, logs and collected data could be easily analysed for a more graphical insight and communicated in visual understanding among your team.

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