Making Your Engineering Day Easier Through Automation

There’s never enough time to get everything done in a single day. So why not automate as many things as possible? A typical day in the life of a software engineer can be littered with meetings, operational tasks, and planning. The only way to get around this and actually get something done is to automate anything you can.

Automation is powerful, especially for engineers. If you can transform the most mundane repetitive tasks into automted processes you’ll end up freeing up time for more important work. Here are the first things I would prioritize automating in an engineering organization to to enhance the team’s efficiency and productivity.

Email

I’ll start with the most obvious one. Automating your email management can greatly enhance productivity. By setting up rules to automatically delete useless emails, such as automated ticket management emails, spam, promotions, you keep your inbox uncluttered. This prevents these emails from taking up space and ensures you only see what's important. Additionally, use filters to automatically sort emails into relevant folders. This way, important messages are organized and easy to find. Whatever your email tool is there’s a way to do this. This way you reduce the time spent manually sorting through emails, making your workflow more efficient.

Build Processes

Jenkins, Travis CI, or GitHub Actions can build your code automatically whenever changes are made. I’ve had to work on complex projects where every build was a manual process. It was a real bottleneck and even more of a pain. Introducing Jenkins automated our builds, saving hours of manual work and catching issues early.

Continuous Integration and Continuous Deployment (CI/CD) pipelines automate the process of testing and deploying your applications after each commit. At a previous job, we spent countless hours manually deploying updates. CI/CD reduces errors and deployment times significantly. Nowadays there are many tools out there that make CI/CD pipelines easier to build than ever before!

Testing

Unit Tests: Automating unit tests ensures new code doesn’t break existing functionality. Tools like JUnit for Java or pytest for Python run your tests automatically. We’ve all been in that situation where a last-minute change breaks some critical feature right before a big release. Automated unit tests give thatpeace of mind, catching bugs early and preventing late-night firefighting.

Integration Tests: Automate integration tests with tools like Postman or SoapUI to ensure that different parts of your application work together correctly. During a crucial project, our integration points kept failing without notice. Automating these tests helped us identify and fix issues before they became major problems, ensuring smoother project milestones.

End-to-End Tests: Tools like Selenium or Cypress can automate end-to-end tests, simulating real user interactions with your application. Manually testing user experiences for regression is a tedious and error-prone job and regardless of how much documentation is provided can be hit or miss. Implementing automated end-to-end tests with tools like Selenium can save hours of manual testing and significantly improved release quality.

Security Testing: Automating security tests ensures your application is protected against vulnerabilities. Tools like OWASP ZAP, Snyk, and Burp Suite can automatically scan your codebase and applications for security issues. Early in my career, I encountered a security breach that could have been prevented with regular automated security testing. These tools continuously monitor for vulnerabilities, providing reports and suggesting fixes, thereby ensuring that security remains a priority throughout the development lifecycle. Integrating these tools into your CI/CD pipeline ensures that security checks are performed with every code change, reducing the risk of deploying vulnerable code.

Automated Load Testing: Automating load tests helps you understand how your application performs under stress. Tools like Apache JMeter and Locust simulate high traffic loads, identifying performance bottlenecks before they impact users. During a major release, automated load testing with JMeter revealed several performance issues that we were able to address before going live, ensuring a smooth user experience. By automating load tests, you can regularly test the scalability of your application, making sure it can handle increased traffic and usage without degrading performance.

Chaos Testing: Chaos testing, or chaos engineering, involves deliberately injecting failures into your system to test its resilience. Tools like Chaos Monkey and Gremlin automate these tests, helping you identify weaknesses in your infrastructure. In one instance, automating chaos tests allowed us to uncover critical vulnerabilities in our failover processes, which we then fixed to ensure better system reliability. By regularly running chaos tests, you can ensure that your system can withstand unexpected disruptions and continue to operate smoothly.

Code Quality and Style

Linters and code formatting tools like ESLint for JavaScript or Prettier automatically check your code for style issues and potential errors. Early in my career, code reviews were filled with nitpicking over style. Comments complaining about spacing or empty lines were all over our pull requests. This saves time and ensures your code looks clean and professional. In a previous role, implementing Prettier eliminated endless debates over formatting, allowing the team to focus on functionality and performance improvements.

Documentation

Keeping API documentation up-to-date can be challenging. Tools like Swagger or Javadoc can automatically generate documentation from your code comments, ensuring it's always current and accurate. I recall joining a project with outdated API docs—it was a nightmare. Automating documentation with Swagger made our APIs easier to understand and use, both for new team members and external partners. Tools like Doxygen can turn code comments into comprehensive documentation, making it easier to maintain and share your knowledge.

AI tools like ChatGPT or CodePilot can enhance your code documentation. You can help generate good code comments and documentation, saving time and improving clarity. However, always ensure that using such tools does not violate your organization’s guidelines on feeding code into large language models or similar systems.

Infrastructure as Code (IaC)

Tools like Terraform and AWS Cloud Development Kit (CDK) allow you to define your infrastructure in code, making it reproducible and version-controlled. During a major migration project, CDK ensured our environments were consistent and easy to set up, reducing setup time from days to hours and minimizing configuration errors. With IaC, you can automate the deployment and management of your infrastructure, ensuring that all environments (development, staging, production) are identical. This approach not only saves time but also reduces human errors, making your infrastructure more robust and reliable.

Using IaC tools, you can version control your infrastructure just like application code. This means you can track changes, review them, and roll back if necessary. During another project, we faced a critical issue where manual configurations caused inconsistencies between environments. By switching from manually configured infra to a mix of Cloudformation and CDK in different services, we eliminated this problem. CDK defined our infrastructure, allowing automated provisioning and setup. We could deploy the same configurations across multiple regions and accounts with confidence, knowing that everything would work as expected. Additionally, integrating with CI/CD pipelines ensured that any infrastructure changes were tested and reviewed before deployment, further increasing reliability and reducing downtime.

Consistent Development Environments

Docker creates consistent development environments, eliminating “works on my machine” problems. Early in my career, I spent countless hours debugging environment-specific issues. Docker containers made these problems a thing of the past, ensuring consistent behavior across all environments. By containerizing applications, Docker encapsulates all the dependencies and configurations needed to run the software, making it easier to develop, test, and deploy applications across different environments without discrepancies.

With Docker, you can create an isolated environment that mirrors your production setup, allowing developers to run applications in the same way across different machines. For example, during a critical project deadline, we encountered an issue where the development environment was not replicating the production environment correctly. This led to bugs that only appeared after deployment, causing significant delays. Implementing Docker solved this problem. Each team member could spin up a containerized version of the application that included all necessary dependencies. This approach not only sped up development but also reduced the risk of environment-related bugs making it to production. Docker Compose further simplified the process by allowing us to define multi-container applications, managing dependencies and service interactions effortlessly.

Monitoring and Alerts

I’m a big fan of CloudWatch (Go Figure!). Through it you can automate the monitoring of your application’s performance and resource usage, providing real-time insights into your system’s health. I’ve been in a situation or two before where automated monitoring with CloudWatch alerted us to a critical memory leak before it caused any downtime, allowing us to fix it proactively and before it had any customer impact. CloudWatch Alarms can be configured to send automated alerts via email, SMS, or other methods, notifying you of critical issues as soon as they occur. While you can take the manual route and setup these metrics and alarms via the AWS console, I much prefer doing so in an automated fashion via CDK. This especially helps when deploying your infrastructure across multiple regions or even accounts.

These alarms will likely end up in operational tickets. To take your automation one step further, you can automate the sourcing of graphs relevant to the alarm and links to SOPs or runbooks on operational tickets. This helps the engineer on call to solve the problem quicker and guides them on how to investigate. By including these automated links and graphs, you provide all the necessary information to increase the speed of root cause identification and mitigation. This approach ensures that whoever is on call has immediate access to the tools and knowledge needed to address issues effectively, reducing downtime and improving system reliability.

Notifications

Integrate your workflows with tools like Slack or Microsoft Teams using ChatOps tools like Hubot or Mattermost. This automates notifications about build statuses, deployments, and other important events directly in your chat channels.

Code Reviews

Standardizing pull request descriptions with templates ensures that you include all necessary information for reviewers, making the review process more efficient and thorough. This approach reduced misunderstandings and streamlined our code review process, leading to quicker approvals and fewer iterations.

Tools like SonarQube automatically review your code for potential issues, such as security vulnerabilities or code smells, providing an additional layer of quality control. During a security audit, automated reviews helped us identify and fix vulnerabilities quickly, improving our code's security and robustness.

Setting Up Command Line Aliases

Setting up command line aliases for commonly run commands is a simple yet powerful way to enhance your productivity. By reducing the need to type out long, repetitive commands, aliases save time and minimize the risk of typos and errors. This allows you to execute tasks more quickly and consistently, streamlining your workflow. Additionally, aliases can be customized to fit your specific needs, creating a more efficient and personalized command line experience. This small optimization can significantly improve your day-to-day operations, allowing you to focus on more complex and valuable tasks.

That’s all folks!!!

By automating these tasks, you can reclaim your time and reduce errors. It’s about working smarter, not harder. Set up your automation today and let the machines handle the mundane tasks while you focus on the fun and challenging parts of engineering. Automation not only improves your productivity but also enhances the quality and reliability of your work.

No matter your level of experience, there's always room to optimize and improve your workflow. Ask for feedback, reflect on what works and what doesn't, and don't be afraid to try new tools and approaches.

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