 DevOps is the marriage of application development teams with system operations teams, their philosophies and actions.
In an agile environment, development, testing and operations all must work together to meet frequent iterations, releases and delivery goals. This calls for a collaborative development environment that supports data orchestration with other lifecycle tools.
The article will explain how multitool integration support can help organizations perform the DevOps life cycle, which includes continuous planning, continuous integration, continuous testing, continuous monitoring, continuous delivery and continuous feedback mechanism.
The Drivers of DevOps
Today, with the increasing competition and the need for an early market release, the software development industry is undergoing a paradigm shift. Agility has become an inevitable process across all organizations. In addition, shorter ROI cycle spans, frequent releases, increased CRs and different IT systems and tool technologies have made the situation critical.
The industry demands higher transparency, maximum visibility, minimum turn-around time, lesser human intervention and efficient processes at every stage, from development to delivery.
However, organizations that use specialized tools to manage builds, deployments and delivery processes continue to face difficulties when it comes to data orchestration and process automation across the tool chain.
In an agile environment, developers and testers need to ensure not only that code changes work and integrate well, but also that frequent iterations do not make the product unstable. Hence, seamless cross-tool collaboration is very important here.
The process chain consisting of Code –> Build –> Provision –> Test –> Defect Fix –> Deploy –> Release needs to run continuously and smoothly without compromising delivery deadlines or the product quality.
Automation is the Catch Line
With the rising demand for continuous delivery and sprint-based development, manually setting up a test, build and deployment environment is burdensome and time-consuming.
Software teams need to automate the entire cycle of build, provisioning and deployment of test environments, including the tools, scripts and test data to ensure rapid delivery. They also need to collaborate around the application architecture and monitor event-action-based mechanism for seamless data flow across the tool chains.
Reports show the most important DevOps components are IT automation, agile development and collaborative teaming of personnel. Therefore, without centralized orchestration of tools, achieving DevOps is not a realistic situation. Since organizations spend around 73 percent of their DevOps budget in tool acquisition, it is important they know how to get the tools working together to overcome DevOps obstacles.
In the process of connecting their existing and new toolsets, most organizations search for an integration methodology that is scalable, reliable and easy to maintain. Point-to-point integration between tools help, but to a limited extent. Even a single change in integration rules involves complex coding and high maintenance across development, test and deployment cycles.
How ESB-based Integration Can Help
An enterprise service bus (ESB)-architected integration hub connects both the existing and the new tools to support a seamless data flow between them across the DevOps life cycle.
Once integrated, the data from both the development and the operations tools become readily available for use to every stakeholder. The benefit of using ESB-based integration is that you can add or remove any tool based on your connectivity requirements.
In a typical scenario, DevOps teams use a series of cross-functional tools starting from project planning to delivery and operations. Neither of these tools comes with built-in integration features, which results in inconsistent flow of information among tool users.
Project managers use application lifecycle management (ALM) or Agile planning tools to detail the scope of work and tracking progress reports. Upon unit testing, developers use a different tool to check in a code from their integrated development environment (IDE) to the source code management (SCM) repository. They also perform a code quality analysis before committing to the SCM.
In such a scenario, continuous integration (CI) can be achieved only when developers bring these planning, unit testing, code analysis and SCM tools under one roof. That is, connecting the tools through a common integration hub. It also helps developers to manage everything from within the IDE.
After successful check-ins, build engineers trigger the SCM tools for automated build and testing. Upon a successful build, testers engage in continuous testing using manual and test automation tools, followed by provisioning for continuous deployment. They also perform load testing, API testing and security testing using separate tools. An integration support helps to keep the real-time data flowing between the build and the testing tools uninterrupted and seamless.
A DevOps system also includes application performance monitoring (APM) tool for continuous monitoring of memory consumption, CPU usage, database health and release tracking. Operations team use help desk/ IT service management (ITSM) tools for continuous feedback generation and customer support. And delivery managers use continuous delivery tools for defining and tracking release pipeline through graphical interface.
When all these tools are connected to a central integration hub, product release and help desk operations become faster and efficient. The integration between development and ITSM tools facilitates continuous feedback generation, which helps to improve the product quality.
Through an integrated tool ecosystem, project managers can create a DevOps workflow based on business logic and automate the data movement across tool systems. Business analysts, developers, testers and delivery managers can also get real-time update on development progress and keep track of actionable items. Supervisors can route cross-tool data to a central repository and generate meaningful reports and analytics before taking business decisions.
Fig:Â ESB Integration Bus Facilitating Adoption of DevOps
An ESB-based integration tool helps organizations to implement and leverage the best DevOps practices by establishing connections across all participating tools. An integrated tool ecosystem helps achieve the following:
- Real-time collaboration between development, delivery and operations tools
- Continuous planning from requirements capturing and review to design and code analysis
- Cross-tool traceability for defining relationships between various data objects
- Test strategy implementation for continuous testing
- Continuous integration through automatic triggering of build on successful completion of code check-in
- Continuous testing through workflow based automatic triggering of both manual and automated test cases
- Scheduled test automation script execution enabling continuous delivery
- Continuous monitoring of release quality through reports and dashboards
- Automated defect identification and resolution for faster help desk response
- End-to-end traceability providing better release predictability and change impact analysis
- Meaningful reports, metrics and KPIs for quick decision-making
- Continuous delivery through tracking release pipeline
How Inter-tool Connectivity Brings Continuity
To understand the stages of engineering practice, let us consider a sample DevOps scenario in an IT service organization.
The organization uses an ITSM tool to manage support tickets submitted by customers. On submission of a ticket, it is automatically passed on to an ALM tool as user stories or defects for internal development.
On allotting to a sprint, developers and testers view the user stories or defects from IDE, SCM and test tool. Once the coding is complete and codes get checked in at an SCM tool, an automatic build gets triggered using a build tool. Upon successful completion of the build, tool provisioning is done through a virtual machine.
The successful build can be automatically deployed using a deployment tool and automated tests can be executed through a test automation tool. The test results are then captured and linked with test cases and the source requirements for traceability.
The defects that are raised in the defect tracking tool for failed test cases can be automatically routed to developers for fixing.
Fig:Â DevOps scenario achieved in a collaborative tool environment
Once connected to an integrated tool system, users get a complete visibility of the tool records and their relationships from within their own tools. Developers, testers and help desk managers can get complete traceability view between development artifacts and change requests or defects.
When all the tools participating in DevOps sync with each other, developers can easily view the support tickets reported by the operations team right from their own IDE.
The help desk team also gets a real-time update whenever a change request gets implemented or a defect is resolved by the development team. It eliminates the latency in communication between the Dev and Ops teams to a great extent.
In addition, customers get frequent updates from the help desk team, which makes them happy and confident about the product performance.
Conclusion
Implementation of DevOps is not a “Do once and forever” type of task. Just deploying the right set of tools to the right users will not serve the purpose. Proper connectivity between and across the DevOps tools chain is necessary if you want to create a collaborative work environment around the Dev and Ops teams.
An integrated tool system saves considerable amount of time and effort, which would otherwise be wasted on manual execution, monitoring and reporting of data during DevOps implementation.
About the Author / Sanat Singha
Sanat Singha is a senior technical and web marketing writer. He takes special interest in ALM process, technologies and tools integration as an industry. Sanat does content marketing, professional blogging, social media promotion and website analytics.
