As businesses embrace microservices and cloud-native architectures, DevOps stands at the center, helping businesses efficiently manage IT workloads. DevOps is an innovative methodology that integrates development, operations, security and business teams to seamlessly coordinate and deliver quality products faster and better. From planning and development to delivery and operations, DevOps works right through the entire application lifecycle.
DevOps brings developers and operations together so that the code is automatically build, tested and deployed in a continuous model. It uses a Continuous Integration / Continuous Deployment (CI/CD) pipeline with automation incorporated across the product lifecycle to accelerate the development process and improve efficiencies while reducing costs.
A CI/CD pipeline comprises a series of steps involved in the delivery process of quality software. It includes the following steps:
- Build Phase: The application code is build and compiled here
- Test Phase: The compiled code is tested here
- Release Phase: The code is pushed to the repository
- Deploy Phase: Code is deployed to production
While DevOps offers amazing benefits to IT teams, many organizations fail to leverage it owing to a lack of understanding of this methodology. Understanding different categories of DevOps and implementing the right tool stack is important. Here are 3 important DevOps categories every organization should focus on.
1) Software DevOps
Software DevOps is where the core software is developed. It involves planning the design, assigning tasks to the team and creating artefacts using tools such as coding software, integrated development environment (IDE), version control system, testing framework and issue management.
Integrated Development Environment (IDE): Developers use a text editor to write, debug and edit code. However, an IDE comes with much more features than a text editor offers. Along with an editor, the IDE offers debugging and compilation enabling you to build, test and deploy code from a single dashboard. Choosing the right IDE improves productivity, reduces errors and eases the development process. While choosing an IDE, ensure that it can be integrated with services across the DevOps lifecycle. Visual Studio, IntelliJ and Eclipse are some of the popular IDEs available in the market.
Version Control System: When multiple developers work on a software project, keeping track of code changes becomes a critical requirement. A version control system helps you to keep track of each code change and revert to a specific version when a release crashes. Git is the most popular VCS system. CVS, Mercurial and SVN are other options available in this segment.
Testing Framework: A testing framework offers a set of guidelines to design and run test cases using the best testing tools and practices.
Issue Management: It is a process of identifying system-level conflicts and defects in the workflow based on events or metrics. It involves detection, response, resolution and analysis.
To achieve continuous delivery, it is important to choose the right CI/CD tools and implement automation wherever possible. Here are a few best tools for software DevOps:
Jenkins is an open-source CI server tool that comes free of cost. It supports Linux, Windows and macOS platforms as well as major programming languages. The main advantage of Jenkins is its plug-in repository. You can find a plugin for most of the development tasks. Moreover, it can be easily integrated with other CI/CD platforms. Debugging is easy. However, it is important to check if the plug-ins are updated. Another downside is the lack of a user-friendly UI. It has a learning curve concerning the installation and configuration of the tool.
Github Actions is a CI/CD platform that enables developers to directly manage workflows in their Github repository. As such, you can perform repository-related tasks in a single place. It offers multiple CI templates. Github Actions comes with 2000 build minutes free per month.
GitLab is a CI software developed by GitLab Inc. for managing DevOps environments. It is a web-based repository that enables administrators to perform DevOps tasks such as planning, source code management, operations, monitoring and security while facilitating seamless coordination between various teams through the product lifecycle. This platform was written in Ruby and launched in 2014 as a source code management tool. Within a quick time, it evolved as a platform that covers the entire DevOps product lifecycle. It comes with an open-core license which means the core functionality is open-source and free but additional functionalities come with a proprietary license.
AWS Code Pipeline
AWS CodePipeline is a powerful DevOps product from AWS that enables developers to automate and manage the entire product lifecycle. The tool automatically creates a build, runs the required tests to launch an app whenever a code change is detected. It offers an intuitive GUI dashboard to efficiently monitor and manage workflow configurations within the pipeline. As AWS CodePipeline is tightly integrated with other AWS services such as S3, Lambda or 3rd party services such as Jenkins, it becomes easy to create quality software faster and better. You can simply pull code from S3 and deploy it to Elastic Beanstalk or Codedeploy.
2) Infrastructure DevOps
Infrastructure management is another crucial component of a DevOps environment. With the advent of Infrastructure as Code (IaC), managing the infrastructure became simple, cost-effective and risk-free. Infrastructure as Code is an IT method of provisioning and managing infrastructure resources via config files, treating infrastructure as software. IaC enables administrators and developers to automate resource provisioning instead of manually configuring hardware. Once the hardware is transformed into software, it can be versioned, rollback and reused.
The advent of Ruby on Rails and AWS Elastic Compute Cloud in 2006 enabled businesses to scale cloud resources on-demand. However, the massive growth in web components and frameworks posed severe scalability challenges as administrators struggled to version and manage dynamically changing infrastructure configurations. By treating infrastructure as code, organizations were able to create, deploy and manage infrastructure using the same software tools and best practices. It allowed rapid deployment of applications.
IaC can be implemented using two models namely Declarative Configuration and Imperative configuration. In a declarative approach, the configuration is defined in a declarative model that shows how the infrastructure should be while the Imperative model defines steps to reach the desired state. Terraform and AWS CloudFormation are the two most popular IaC tools that enable organizations to automatically provision infrastructure using code.
Infrastructure as Code took infrastructure management to the next level. Firstly, it rightly fits into the DevOps CI/CD pipeline. The ability to use the same version control system, testing frameworks and other services of the CI/CD pipeline facilitates seamless coordination between various teams and faster time to market while significantly reducing costs. It also helps organizations leverage the containerization technology wherein the underlying infrastructure is abstracted at the OS level, and the hardware and OS are automatically provisioned. As such, containers running on top of it can be seamlessly deployed and moved across a wide variety of environments.
Secondly, IaC offers speed and efficiency with infrastructure automation. It is not confined to compute resources but extends to network, storage, databases and IAM policies as well. The best thing about IaC is that you can automatically terminate resources when they are not in use. Thirdly, IaC reduces operational costs as the number of network and hardware engineers required at every step of operations is reduced. Fourthly, it brings consistency across all deployments as config files use a VCS as a single source of truth. Scalability and availability are improved. Monitoring the performance and identifying issues at a granular level helps reduce downtimes while increasing operational efficiencies. Overall, it improves the efficiency of the entire software development lifecycle.
Terraform is an open-source IaC tool developed by Hashicorp in 2014. Written in Go language, Terraform uses Hashicorp Configuration Language (HCL) to define the desired state of the target infrastructure on a variety of platforms including Windows, Solaris, Linux, FreeBSD, macOS and OpenBSD. Terraform is a declarative-based tool that stores the state of the infrastructure using a custom JSON format along with details of which resources should be configured and how. The tool uses ‘Modules’ to abstract infrastructure into sharable and reusable code. HCL is human-readable and helps you quickly build infrastructure code. Terraform is cloud-agnostic and integrates well with AWS. So, it can be used to manage a variety of cloud environments.
AWS CloudFormation is a managed IaC service from AWS that helps you to create and manage AWS resources using simple text files. Along with JSON template format, YAML is supported. AWS constantly updates the tool to always keep it current while adding several new features regulalry. Nested stacks is a useful feature that encapsulates logical functional areas which makes it easy to manage complex stacks. Similarly, changesets is another useful feature that allows you to inspect changes before applying them. However, CloudFormation is native to AWS. If your infrastructure is AWS-heavy, CloudFormation will serve a great purpose.
3) Database DevOps
DevOps is not just confined to development and operations. Database DevOps extends DevOps capabilities to databases as well, integrating development teams with database administrators (DBAs) such that database code is also included with the software code. As such, database changes can be efficiently monitored and added to the DevOps workflows.
In a traditional development environment, changes made to an application often require changes to be made to the corresponding database. Developers wait for DBAs to make changes to databases that are stored in SQL scripts. These changes have to be reviewed before deploying data to production. As the review is done at the later phase of the workflow, the delay impacts the overall agility and productivity of the project. Errors identified just before a release can be risky and costly as well.
Database DevOps introduces a version control system for database changes. The source control allows you to run builds anytime and roll back if needed at your pace. It also offers an audit trail.
In database DevOps, database workflows are also integrated into the CI/CD pipeline with automation incorporated wherever possible. When a database code change is detected, the system automatically triggers a build. As such, database teams can closely work with other teams on code changes using a well-defined process to improve productivity while reducing task switching.
However, continuous deployment is not easy with regard to databases. When a code change triggers a change to the database schema, it should be migrated to a new structure. You need the right tools to do so. Snowchange is a powerful DevOps database tool that helps you in this regard.
SnowChange is a powerful DevOps database tool developed by James Weakly in 2018 to manage Snowflake objects such as tables, stored procedures and views. Written in Python, Snowchange fits easily into the DevOps CI/CD pipeline as all popular CI/CD tools offer a hosted agent for Python. It is a lightweight tool that follows an imperative approach to DCM (Database migration, schema change and schema migration). It uses a snowchange change script that contains SQL statements defining the state of the database. By looping target databases, the tool applies new changes to the required databases.
Sqitch, Flyway and Liquibase are a few other options in the DevOps database stack.
DevOps is a blanket term that deals with managing an entire product lifecycle. However, it is important to optimize every phase of the DevOps workflow. Choosing the right tool stack for the right process is the key to fully leveraging DevOps.
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