The concept of DevOps has at its heart the goal of integrating code development and operation of the IT infrastructure and software that makes up the overall application.
The organizational collaboration and integration of function and process is achieved by leveraging and implementing DevOps Practices to ensure that all aspects of the Software Development Life Cycle (SDLC) such as coding, testing, deployment and day-to-day operations are working together toward the common goal of improving efficiency, providing a better security posture and automating the end-to-end delivery process.
DevOps provides the foundation that enables a cloud environment to thrive and succeed whether it is on-premise or in a hosted environment.
Like all implementations, we have success and some bumps along the journey. Based on my experience, the following are key considerations and best practices to help you smooth out the road ahead:
Continuous Integration. Software development is a complicated process with many sub processes and milestones such as version control, testing, deployment and post deployment tasks and restarts. Traditionally these tasks end up with different teams or team members - each with their own timeline and procedures. DevOps aims at automating these tasks and minimizing human intervention in the deployment process. Tools such as Bamboo and Jenkins among others should be considered.
Continuous Delivery. Continuous delivery methodology assures that there are no bottlenecks or breakpoints in pushing the code from one environment to another. Issues or bugs occurring in a live production environment can be resolved quickly as the automated integration and delivery processes ensures consistent and efficient movement of the code through the whole delivery pipeline. Continuous Delivery provides the framework for making the complete infrastructure agile and flexible so that required changes can be propagated to a targeted environment without challenges.
Automating Testing. Besides development, the most important part of the SDLC process is testing. Functional, regression and load tests ensure a stable and secure release. Instead of running the tests manually, test automation tools and framework such as Selenium ensures that the code is is used as input and the output is a report showing success, failure or partial failure due to bugs and test case violations. Effective test automation is achieved by first identifying the right test and use case scenarios, configuring and coding the automation tool set before finally running the test s and analyzing the results.
Configuration Management. Success of Agile and DevOps practices rely heavily on having a proper and well-organized configuration management and tools to manage IT Assets as well as code. Standardizing the approach towards resource configuration and enforcing this practice across the IT landscape through automation should be a prerequisite. Tools such as Ansible, Chef and Puppet allow users to make configuration changes in one file and in one place and then pushes the changes across multiple servers and environments.
Monitoring and Operational Excellence. Proactive monitoring is important for all teams and departments. An operational imperative is to create visibility and transparency for the development and operations team. Information gleaned from bug identification to sharing the analysis of operational metrics such as load time, query execution times, or system resource utilization elevates the team’s performance and productivity to ensure that the application is functioning properly.
Monitoring can also be leveraged to identify abnormal behavior of the application such as load and access attempts as well as aid in improving the security posture of the application.
Log Management. A modern application which is distributed with multiple components generates many log files. These logs provide vital information about the application and its state. The logs need to be well-structured, contain relevant information and should be easy to interpret. The right type of end-to-end logging helps teams analyze an application performance and provide a view of the user experience which is invaluable. For example, centralized logging for applications with multiple servers serves as a force multiplier and assists in debugging during outages. Setting up alerts with the logs can actually prevent outages. Tools such as Splunk is an effective method to establish log aggregation efficiently and effectively.
Data Driven Improvements. Actual data and statistics drawn from user and application data allow the DevOps team to think about continuous improvement. And with the assistance of usage patterns and application graphs, the team is able to visualize where there are improvement opportunities. At each step of the development and delivery process, reviewing the actual data in the form of errors, failures, re-tries, bugs, etc., allows the development team and the operational teams to better collaborate in improving the efficiency of the processes and drive better value. This data-driven approach should be used by the teams to make the SDLC process more cohesive, repeatable and continuously refined.
DevOps should be looked at as a mindset rather than just a set of principles or guidelines. It is a critical piece of the Agile software development process and a major milestone when it comes to the adoption of Cloud.