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Tag: devops best practices

DevOps Automation: A Detailed Guide
DevOps automation is a productive platform where human assistance is reduced. Those processes that drive feedback loops between development and operations teams are pondered upon and worked accordingly through a structured strategy. The deployment of iterative updates can be done faster to applications in production through the tactical use of automation testing services in DevOps. In this article, you will get a brief understanding of the process of incorporating automation in DevOps and optimizing performance.

What is DevOps Automation?

It is a specific technological process wherein information technology and software engineering best practices are designed to enable continuous delivery and automation of software products. The testing, development, monitoring and deployment of software is automated by the automation platform. DevOps processes are automated by DevOps automation scripts, which are considered to be specific tools.

This ensures that software delivery is carried out at a faster pace and developers can focus and work on other crucial testing tasks. Faster testing and deployment of software are ensured by automation scripts. This process is carried out in a repeatable, reliable and consistent manner.

Through the tactical implementation of DevOps automation, organizations can streamline their activities, enhance software quality and reduce the time consumed for marketing activities. The focus should also be on leveraging automation testing services.

The following are key processes that need to be taken into consideration for optimizing DevOps automation activities:
1. The Necessity of a Platform: A proper platform is required to carry out automation in DevOps. This platform should enable users to monitor, define and execute automated workflows and ensure that processes are provided with the required visibility.
1. Attainable Goals Need to be Set: Well-defined goals need to be set for the automation process. A proper roadmap can be followed by the team to make sure that the process is a success.
1. Used Processes Need to be Automated Frequently: Specific operations that should be automated first need to be identified. Organizations can get impacted frequently through these used
1. Automated Processes Need to be Tested: Testing should be carried out by the team to ensure that it is functioning appropriately. The testing can be conducted regularly to make sure that the DevOps test automation process runs as expected.
1. Automated Processes Need to be Monitored and Adopted: The processes should be monitored and necessary adjustments should be made if required. When the process is carried out properly it guarantees effective results.
1. Automated Processes Need to be Tracked and Reported: The progress of the automation process needs to be properly tracked and reported. The process is provided with the required visibility and areas for improvement are identified.
1. The Continuous Integration (CI) Platform Should be Leveraged: The development team that writes the code is combined by the CI platform into a single main source code Those bugs or errors that arise in the code are quickly identified by developers. It is a coherent part of automation testing services.
1. Continuous Delivery (CD) Platform Should be Used Tactically: The software is delivered to customers and users with reliable, fast and consistent delivery. It in turn helps organizations to ensure that their software is working as per the specific requirements and is always up to date.
1. Infrastructure as Code (IaC) Should be Utilized: IaC is a specific process that helps organizations quickly manage, configure and deploy their IT infrastructure. When IT infrastructure management tasks are updated, the costs and time of an organization are reduced to a great extent.
When the above-mentioned processes are prioritized, DevOps automation can be achieved succinctly. This in turn helps quality software to be delivered quickly.

Initiating the Process of DevOps Automation
1. Identify the Current State of the DevOps Environment: Before the DevOps process is automated, the existing domain should be clearly understood. The people, techniques and tools involved in the current DevOps flow need to be properly examined.
1. Highlight the Areas of the DevOps Process that Need to be Automated: Once the current environment is properly understood, the areas that can benefit from automation are required to be identified. The activities that can be automated must be considered.
1. Select the Right Tools: For carrying out DevOps automation successfully, appropriate automation tools must be selected. The type of tasks that need to be automated should be taken into account.
1. Build the Automation Pipeline: Once the right tools have been selected, the DevOps automation pipeline needs to be built. It includes the devices being configured, making the necessary infrastructure and creating the automation scripts.
1. Test and Deploy the Automation Platform: Before the automation platform is deployed, it needs to be tested to make sure that it is working as expected. Once the checking is done (the team must ensure that everything is functioning correctly), the automation platform can be deployed to production.
1. Monitor and Optimize the Automation Process: Once the deployment has been done, it needs to be monitored to make sure that it is running efficiently and correctly. Tweaks or adjustments can be made to optimize the performance.
Here are a few of the best DevOps automation tools:
1. Kubernetes: It is an automation and container orchestration platform and is popularly used among DevOps teams. Containers are managed at a large scale and work well with Docker. The management of hundreds of containers is automated. Containerized apps can be deployed to a cluster.
2. Docker: It is a Linux-based open-source tool. Containerized environments are created for apps wherein they are made more secure and portable, and conflicts are reduced while testing. DevOps is enabled by the Docker tool so that applications can be built and run quickly and efficiently.
The containers can be accessed through the docker engine and then applications can be executed within a remote environment. Those organizations that are focused on minimizing infrastructure costs can opt for Docker.
1. Splunk: Through this tool, machine-generated logs or data are searched, analyzed and visualized in real time. The machine state is analyzed and hardware failure points are identified. The machine data is pushed to Splunk and all the available data is processed by the tool.
2. Ansible: It is an agentless configuration management tool that offers continuous delivery and can be easily deployed. Many repetitive tasks such as intra-service orchestration, application deployment and cloud provisioning are automated. Nodes can be connected through this tool and modules are pushed from a centralized place.
Conclusion

DevOps encourages collaboration and boosts the culture factor among development, operations and other relevant teams. The objective is to embrace the agile model and carry out technological processes at a faster pace. Automation not only improves the efficiency of DevOps but also helps in carrying out tedious tasks meticulously and easily. For more detailed and insightful information on the tactical implementation and execution of DevOps automation, you can consult with a premium software testing services company.
August 20, 2024
From Chaos to Clarity: Streamlining DevSecOps in the Digital Era

These days, securing the software development lifecycle from end to end requires organizations to deploy, maintain, and master a cacophonous mix of tools that often do more to create discord rather than bring harmony to DevSecOps processes. The reason for this is simple: Each tool employed to secure a software supply chain independently runs scans and generates alerts that lack context, are often redundant, or flat-out contradict one another.

Developers and the software engineers that support these applications are, of course, expected to correlate the steady streams of alerts and address vulnerabilities to meet security thresholds required to propagate the release to an upstream environment. The reality is that not all of the vulnerabilities flagged as high and critical need fixing, nor is it possible for a team to address all of the vulnerabilities. On average, a development team has the bandwidth to address 10% of its vulnerability backlog in any given month. This makes it imperative to prioritize the vulnerability backlog based on impact rather than severity if we are to give these development teams a ghost of a chance to succeed in improving their security posture.

The constant alert storms also lead to fatigue and introduce a real risk of false negatives. The one that got away!

DevSecOps workflows today are little more than sections of an orchestra playing without a score with the expectation that some methodology to consistently lock down a software supply chain will magically manifest.

What’s obviously missing is an orchestration framework that triggers the security workflow in response to changes within the SDLC. Ideally, it works seamlessly with the CI/CD workflows, but without being dependent on them, creating a symphony capable of providing a better security posture for the organization.

The Trouble With DevSecOps

In cloud-native, microservices-based application development environments, teams could be developing using multiple technologies, each optimized for delivering a certain service. Each technology may require a certain specialized scanning tool—and that’s just code; by the time we add binary, infrastructure pipeline, data and identity to the mix, you end up with a vast array of tooling and a huge set of policies that every change needs to be assessed against.

Yes, you can scan containers on a periodic basis before deploying to production and that might be OK if you are deploying one release per month. However, even then you could argue that by the time the vulnerabilities are picked up, it’s too late and you have already lost the battle on efficiency.

The very reason you went with a microservice-based architecture is so that it’s easy to scale and quick to build and deploy. Ideally, you would want to be releasing features rapidly for your customers. This means a very high degree of change, which in turn means the point-in-time assessment you did will simply not be fit for purpose in terms of protecting your assets. Every commit has the potential of exposing a new risk, which may end up being discovered too late if left to point-in-time assessments.

Instead, if security is orchestrated seamlessly and asynchronously through tool-agnostic interfaces across your CI/CD pipelines, delivering the outcomes required to secure your digital assets from the first commit right through to the production deployments and beyond, you have truly adopted DevOps. In this scenario, every change is assessed in real-time, and its impact is projected across to development, operations, and security with a clear call to action.

This approach also provides a more extensible and scalable framework for organizations as they advance through their journey of DevSecOps adoption.

Summary

No development team deliberately sets out to build and deploy an insecure application. The reason applications with known vulnerabilities are deployed so often is because the cognitive load associated with discovering and remediating them is simply too high. The average developer can only allocate 10% to 20% of their time remediating vulnerabilities. The rest of their time is spent either writing new code or maintaining the application development environment used to write that code. If organizations want more secure applications, they need to find ways to make it easy for developers to correlate, prioritize and contextualize the vulnerabilities as they are being identified. Most of the time when developers are informed a vulnerability has been discovered in their code, they have long since lost context.

Vulnerabilities need to be immediately identified at the time code is written, builds are created, and pull requests are made – and identified in a way that is actionable. Otherwise, that vulnerability is likely to be thrown atop the massive pile of technical debt that developers hope they’ll one day have the time to address.

At this juncture, it’s only a matter of time before governments around the world enact legislation that will hold organizations more accountable for the security of the software they build and deploy. Savvy DevSecOps teams already recognize that existing approaches to managing DevSecOps workflows will need to be revamped to address these requirements. The challenge and the opportunity now is to put in place a scalable security orchestration framework that eliminates friction in DevSecOps workflows and drives efficiency through real time assessments, ensuring that your software is secure by default.

March 25, 2024
Best of 2023: Documentation as Code: A Game Changer for DevOps Teams?

As we close out 2023, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2023.

Documentation-as-code (DaC) is a growing trend in the world of software development. It is a philosophy that treats software documentation in the same way as software code. In other words, it means writing, storing, managing and delivering documentation through the same systems used for code. This approach is becoming an important part of DevOps culture, facilitating efficient and effective collaboration between development and operations teams.

The concept of documentation-as-code borrows practices from software development and applies them to the realm of documentation. Writing documentation-as-code allows us to use tools and processes that are already familiar to us from the software development process, such as version control, automated testing and continuous integration. This results in documentation that is more consistent, up-to-date and faster to produce, all while being stored in a format that is easily readable by both humans and machines.

Documentation-as-code enables a shift-left approach to documentation, where documentation is created and updated early and often. This shift results in more accurate, timely and relevant documentation since it is updated as the code changes. Furthermore, because documentation is treated as code, it becomes a part of the development process rather than an afterthought. This approach helps to bridge the gap between development and operations, making it easier for teams to deliver high-quality software at a faster pace.

5 Principles of Documentation-as-Code

Version Control

One of the key principles of documentation-as-code is version control. Just as with code, documentation changes over time. New features are added, old ones are deprecated and bugs are fixed. Therefore, it’s necessary to track these changes and have the possibility to revert to previous versions if needed. This is where version control comes into play.

Version control systems like Git are perfect for managing documentation. They allow you to track changes, create different versions of documents and merge changes from different contributors. This makes it easier to collaborate on documentation and ensures you always have a history of changes.

Plain Text Formats

Another principle of documentation-as-code is the use of plain text formats. Plain text formats, such as Markdown or reStructuredText, are easy to read and write, and they can be version-controlled and diffed, just like code. This makes it easy for anyone on the team to contribute to the documentation.

Plain text formats are also platform-independent, meaning they can be read and edited on any operating system. This is a huge advantage over proprietary formats like Word, which require specific editing software and may not be compatible across different platforms.

Furthermore, plain text formats can be easily converted to other formats like HTML or PDF for publishing. This means you can write your documentation once in a plain text format and then generate a variety of output formats for different audiences or purposes.

Collaboration and Peer Review

Documentation-as-code promotes collaboration and peer review. Because documentation is stored in a version control system and written in a plain text format, it’s easy for anyone on the team to contribute to the documentation. This means that developers, testers, operations staff and even customers can all contribute to the documentation, resulting in more comprehensive and accurate documentation.

In addition to facilitating collaboration, documentation-as-code also encourages peer review. Just like code, documentation can benefit from being reviewed by others. This can help to catch errors, improve clarity, and ensure consistency. Many version control systems have built-in tools for code review that can be used for documentation as well.

Automated Testing and Deployment

Just like code, documentation can and should be tested. Automated testing of documentation can help to catch errors like broken links, missing images or incorrect formatting. There are many tools available that can automatically test your documentation, and these can be integrated into your continuous integration and continuous deployment (CI/CD) pipeline, just like your code tests.

In addition to testing, documentation can also be automatically deployed. For example, when you push changes to your documentation repository, your CI/CD pipeline can automatically build and deploy the updated documentation to your website or documentation portal. This ensures that your documentation is always up-to-date and matches the current state of your software.

Single Source of Truth

The final principle of documentation-as-code is the concept of a single source of truth. This means that there should be one, and only one, definitive source of information for each piece of documentation. This source should be stored in a version control system, and all published versions of the documentation should be generated from this source.

Having a single source of truth ensures consistency across all versions of your documentation. It also makes it easier to manage and update your documentation, since you only have to update one source, rather than multiple copies.

Benefits of Documentation-as-Code for DevOps Teams

Improved Collaboration

In traditional setups, documentation is often seen as a secondary function; something that’s done after the actual coding. This approach often leads to bottlenecks and miscommunications, with developers and operations teams working in silos.

With DaC, documentation becomes part of the code itself. This means that everyone on the team has a stake in keeping it updated and accurate. It promotes shared responsibility and understanding, fostering a culture of collaboration.

Greater Consistency and Accuracy

Another key advantage of DaC is its contribution to consistency and accuracy. By treating documentation like code, we can use the same tools and practices used for code review and testing to validate our documentation.

This approach ensures that our documents adhere to specified standards and are free from errors. It also enables us to automate the process of checking for consistency in terms, formatting and structure, saving us from tedious manual work and reducing the chances of human error.

Moreover, since the documentation lives alongside the code, it’s easier to keep it in sync with the system’s current state. This ensures that our documentation always accurately reflects the system, eliminating the confusion and inefficiencies that come with outdated or inaccurate documents.

Streamlined Update and Maintenance Processes

DaC streamlines the processes of updating and maintaining documentation. Traditional documentation often becomes outdated quickly, requiring significant time and effort to update.

But with DaC, updates become part of the development process. Whenever code changes, the documentation changes with it. This removes the burden of having to update documentation separately and ensures that it’s always up to date.

DaC Best Practices for DevOps Teams

Here are a few best practices to help you effectively implement documentation-as-code in your DevOps pipeline.

Start Early

One of the best practices to implement DaC is to start early. Begin documenting as soon as you start coding. This ensures that the documentation grows organically with the code and reduces the likelihood of important details being forgotten or overlooked.

Use Lightweight Markup Languages

When implementing DaC, it’s advisable to use lightweight markup languages like Markdown or AsciiDoc. These languages are easy to learn and use, and they allow you to write documentation that’s readable both in its raw form and when rendered to HTML or other formats.

Documentation Reviews and Feedback Loop

Just like code reviews, documentation reviews should be a regular part of your development process. This ensures that the documentation is accurate, comprehensive, and adheres to your team’s standards. Also, incorporate a feedback loop for your documentation. This allows your team to continuously improve the documentation based on feedback from users and stakeholders.

Modularity and Reusability

Lastly, design your documentation for modularity and reusability. Break it down into small, manageable pieces that can be easily updated and reused across different parts of the application.

Conclusion

Documentation-as-code is an invaluable tool for DevOps teams. It improves collaboration, ensures consistency and accuracy, facilitates version control and streamlines the update and maintenance processes. By adhering to the best practices outlined in this blog post, you can harness the full potential of DaC and significantly enhance your team’s efficiency and effectiveness.

January 5, 2024
BMC Adds More Tools to Modernize Mainframe Applications

BMC this week added a BMC AMI DevX Code Insights tool that makes use of machine learning algorithms to break apart monolithic COBOL mainframe applications into subprograms that are easier to update and refactor.

In addition, BMC is now making available BMC AMI zAdviser Enterprise, a commercial instance of a previously announced free tool that uses machine learning algorithms to collect telemetry data from mainframe applications. The commercial version of the tool adds a dashboard built and maintained by BMC that makes it simpler to consume that data.

John McKenny, senior vice president and general manager of Intelligent Z Optimization and Transformation at BMC, said BMC AMI DevX Code Insights visually maps a mainframe application to analyze data flow and debug applications made up of millions of lines of code in real-time that would otherwise be too complex to unravel. Armed with the insights gained, IT teams can then isolate business logic, refactor subprograms, add application programming interfaces (APIs) or remove dead code as they see fit, he added.

BMC AMI DevX Code Insights also makes it simpler for organizations to onboard new developers to a project at a time when many of the original developers of COBOL applications are retiring, said McKenny.

In the coming year, BMC is also committed to adding generative artificial intelligence (AI) tools to its portfolio for reengineering mainframe applications, added McKenny. Those tools, for example, will make it simpler to create documentation for legacy applications, he noted.

It’s not clear how quickly organizations that have mainframes are looking to re-engineer applications, but as more of them adopt DevOps best practices, they are being updated more frequently. The less monolithic the application, the simpler that task becomes. The issue is that mainframes tend to run large applications that access large amounts of data, so many IT teams are naturally fearful of breaking them if they are reengineered, noted McKenny.

While there is no doubt that the process of reengineering applications will become more automated in the years ahead, software engineers will still be needed to manage the overall process, said McKenny. The role of the software engineer will undoubtedly evolve, but it’s not likely software development and deployment will be wholly automated any time soon, he noted.

In the meantime, IT organizations that manage mainframes continue to embrace DevOps best practices to varying degrees. There may be some applications that they continue to build and deploy using waterfall methodologies, but as mainframe applications become integrated into digital business workflows, the need to update them faster becomes more apparent.

The challenge, as always, is not only providing IT teams with the tools to make that transition but also navigating the cultural issues that inevitably arise any time a change of this magnitude is made to the software development life cycle (SDLC). Regardless of the approach, the building and maintenance of mainframe applications are evolving. The only issue that remains to be resolved is finding ways to reduce the level of friction that transition creates as quickly as possible.

December 1, 2023
DevOps Best Practices for Faster and More Reliable Software Delivery

Imagine a scenario where teams creating the software and delivery aren’t just passing information but sitting together, brainstorming and solving problems in real time. That’s the core of DevOps. It’s not a one-click software solution, but teams working together to provide a reliable solution for seamless and faster software delivery.

Let’s take an example of an app or software update; users would expect it to work seamlessly. The secret here for that seamless experience is often a well-structured DevOps strategy. DevOps isn’t just about speeding things up, it’s about balancing the need for speed with the need for stability.

According to research, 99% of organizations witnessed a positive impact after implementing DevOps in their business delivery processes. They’re deploying updates far more frequently, their failure recovery is lightning-fast, and they see fewer issues when they launch new features.

Using DevOps for Efficient Software Delivery

DevOps is crucial for organizations looking to resolve the complexities of modern software delivery. It bridges the gap between ‘code complete’ and ‘code in production,’ ensuring that software isn’t just created but delivered swiftly and effectively to the end-user. This approach not only accelerates time-to-market but also enhances product quality and customer satisfaction.

By adopting continuous integration and continuous delivery (CI/CD), automation, and constant feedback, DevOps empowers teams to respond to market changes with agility and confidence. It’s about balancing processes, people and technology that work together to unlock higher efficiency, innovation and success.

Implementing Continuous Integration and Continuous Deployment (CI/CD)

Continuous integration and continuous deployment (CI/CD) are core practices in the DevOps approach, designed to streamline and automate the steps in getting software from development to deployment. CI/CD establishes a framework for development teams that supports frequent code changes while maintaining system stability and high-quality output. This method depends on automation to detect problems early, reduce manual errors and speed up the delivery process, ensuring that new features, updates and fixes are available to users quickly and reliably. Teams should follow several best practices:

• Commit to Version Control Rigorously: Every piece of code, from application to configuration scripts, should be version-controlled. It ensures that any changes can be tracked, rolled back or branched out at any point, providing a solid foundation for collaborative development and deployment.
• Automate the Build for Consistency: Automation is the key to CI/CD. By automating the build process, one can ensure that the software can be reliably built at any time. This automation includes compiling code, running database migrations, and executing any necessary scripts to move from source code to a working program.
• Incorporate Comprehensive Automated Testing: A robust suite of automated tests, including unit, integration, acceptance, and regression tests, should be run against every build to catch bugs early. Automated tests act as a safety net that helps maintain code quality throughout the rapid pace of DevOps cycles.
• Replicate Production in Staging: A staging environment replicates your production environment and is crucial for pre-deployment testing. It should mimic production as closely as possible to surface any environment-specific issues that could otherwise cause unexpected behavior after release.

• Ensure Quick and Safe Rollbacks: The ability to roll back to a previous state quickly is essential. This safety measure minimizes downtime by swiftly reversing failed deployments or critical issues without going through a prolonged troubleshooting process during peak hours.
• Monitor Relentlessly Post-Deployment: Continuous monitoring of performance, user experience, and error rates is crucial for catching issues not identified during testing. This real-time data feeds back into the development cycle, helping to improve the next iteration of the software.

Security Practices in DevOps (DevSecOps)

Security is a fundamental element that must be implemented in software development and operations. Integrating security into the DevOps lifecycle means shifting from a traditional security approach to a DevSecOps where security is embedded in the development process, from design to deployment.

To ensure that security is not sidelined in the DevOps cycle, here are some best practices:
• Embed Security Early and Often: Integrate security tools and practices at the earliest stages of the development cycle. This includes code analysis, threat modeling and security requirements gathering.
• Automate Security Processes: Use automation to scan for vulnerabilities, configuration issues and compliance violations. Integrate automated security tools within the CI/CD pipeline to run automatically with every build.
• Practice Infrastructure as Code (IaC): Manage and provision infrastructure through code, which is version-controlled and reviewed for security like application code.
• Stay Compliant: Keep track of relevant regulatory standards and ensure practices meet or exceed these requirements. Regularly review and audit processes to maintain compliance.
• Threat Modeling and Risk Assessment: Regularly perform threat modeling to anticipate potential security issues and conduct risk assessments to prioritize security efforts.
• Continuous Monitoring and Response: Implement real-time monitoring to detect and respond to security incidents promptly. Have an incident response plan that can be executed immediately when necessary.

Cloud Integration in DevOps

Cloud services offer on-demand resources that can be quickly equipped and scaled to meet the needs of any development project. Integration of cloud services with DevOps provides scalable, flexible and efficient resources that align with the rapid and iterative nature of modern software development. Cloud capabilities allow DevOps methodologies to succeed, providing always available resources that adapt dynamically to varying workload demands.

Maximizing the cloud’s potential within DevOps requires adherence to several best practices:
• Firm Infrastructure: Systems should be replaced rather than altered to maintain consistency. Utilizing pre-configured images for servers and containers enables quick, reliable rollouts.
• Configuration Management: Keeping configurations distinct from application code simplifies the management and scalability of the environment, promoting clear operational boundaries.
• Security and Compliance: Security practices must be integrated into cloud operations. Tools provided for identity management, data encryption, and regular compliance audits are critical for maintaining a secure environment.
• Cost Management and Optimization: Active monitoring and reporting on cloud expenditures are essential. Resources should be optimized based on demand, and reserved instances should be considered for predictable workloads to manage costs effectively.
• Continuous Monitoring and Improvement: Persistent monitoring of cloud resources and applications is crucial. Insights from monitoring guide informed decisions on enhancements, assuring availability and optimal performance.
• Disaster Recovery and High Availability: Cloud infrastructure should be architected to withstand failures. Strategies like multi-region deployment and automated failovers guarantee continuous application availability and resilience.
• Performance Tuning: Ongoing evaluation of cloud resources and workloads is necessary for performance optimization. Features like scaling and load balancing are necessary to meet performance benchmarks.

The Role of Testing in DevOps

Testing in DevOps is a practice that integrates into every stage of software development and deployment. Continuous Testing within DevOps ensures that every change made to the codebase is automatically tested, reducing bugs and improving quality. This approach helps maintain a steady pace of delivery while protecting the reliability and stability of the software. Adopting strategies that enhance the efficiency and effectiveness of testing processes is critical for DevOps’ success.

Here are some strategies to achieve this:
• Automate Testing Wherever Possible: Automation is critical to maintaining the speed and consistency required in DevOps. Prioritize the automation of regression, integration, and performance testing to catch defects quickly.
• Leverage Service Virtualization: Use service virtualization to simulate components that are unavailable or still under development to allow testing to proceed without delays.
• Parallelize Test Execution: Run tests in parallel where possible to reduce the time required for the testing process. Cloud-based solutions can be particularly effective for parallel test execution.
• Shift-Left Testing: Integrate testing early in the development cycle to identify and fix issues sooner, which is more cost-effective and reduces time to market.
• Incorporate Testing into the Build Process: Embed testing into the build and deployment pipeline to ensure every build gets tested and issues get identified before they reach production.
• Maintain Test Data Management: Implement tools and practices for managing test data effectively, ensuring that tests can access up-to-date and relevant data sets.
• Regularly Review and Update Test Suites: Keep test suites up to date with application changes to ensure they remain relevant and effective at identifying new and existing defects.

Conclusion

DevOps will become even more ingrained in the software delivery process, with advancements in AI and machine learning likely introducing unprecedented levels of automation and predictive analytics. As technology evolves, integrating DevOps practices into current business models will be crucial. For many organizations, this means seeking expert DevOps consultation to navigate the complexities of modern software delivery and to tailor these practices to their unique challenges and goals. As DevOps evolves, it will continue to pave the way for faster, more reliable and more secure software delivery that keeps pace with the demands of the changing digital landscape.

November 30, 2023
What is a Shadow Deployment?

Shadow deployment, at its core, is a software deployment practice where any changes to a software application are deployed in a parallel environment that mimics the production environment. The deployed changes are not visible to the end-users, hence the term “shadow.” This hidden deployment enables us to observe the behavior and impact of the changes without causing any disruption to the live application.

The primary purpose of shadow deployment is to test real-world application behavior under load, identify performance bottlenecks, and ensure that the application changes don’t affect the user experience negatively. It allows developers to test changes in an environment that closely replicates the live production environment, thereby reducing the risk of unforeseen issues cropping up post-deployment.

In essence, shadow deployment is akin to having a rehearsal before the actual performance. It provides a safety net to developers and aids in ensuring a smooth transition when the changes are finally deployed to the live environment.

Benefits of Shadow Deployment

Risk Mitigation

One of the most significant benefits of shadow deployment is risk mitigation. In traditional deployment methodologies, code changes are often deployed directly to production, which may lead to unforeseen issues and disruptions.

With shadow deployment, the risk of such disruptions is significantly reduced as the changes are first deployed in a parallel environment. This allows for thorough testing and validation, ensuring any bugs or performance issues are identified and rectified before the changes hit the production environment. This is also useful for DevSecOps teams, as it can help them understand the security impact of a new deployment without exposing it to attackers.

Shadow deployment also offers the benefit of rollback. If any critical issue is identified during the shadow deployment, the changes can be rolled back without affecting the live environment. This provides a safety net to developers and businesses, ensuring that the user experience is not compromised.

Real-World Testing

Another significant advantage of shadow deployment is that it allows for real-world testing. In traditional testing methodologies, simulated data is used, which may not accurately represent the live environment. However, in shadow deployment, the parallel environment mirrors the live environment, ensuring testing is done under real-world conditions.

This offers a more accurate representation of how the changes will perform when deployed to production. It helps identify issues that might not be apparent in a simulated testing environment, ensuring a more robust and reliable deployment.

Efficient Scaling

Finally, shadow deployment aids in efficient scaling. In today’s digital landscape, applications need to be scalable to handle varying loads. Shadow deployment enables developers to test the scalability of their changes in a real-world environment, thereby ensuring efficient scaling.

It allows for the testing of various aspects of scaling, such as database scaling, server load balancing and more. This ensures that when the changes are finally deployed to production, the application can efficiently scale based on user demand.

Use Cases for Shadow Deployment

Performance Testing

One of the primary use cases of shadow deployment is performance testing. It allows developers to test the performance of their changes under real-world conditions. This includes testing aspects such as response times, server loads, database queries and more. The insights gained from this testing can be used to optimize the changes, ensuring optimal performance when deployed to production.

Application Migration

Shadow deployment is also widely used during application migration. When migrating an application from one platform or technology stack to another, it is crucial to ensure that the migration does not negatively impact the user experience. Shadow deployment allows for the testing of the migrated application in a parallel environment, ensuring that any issues are identified and rectified before the migration is made live.

Service Dependency Validation

In today’s microservices architecture, applications often depend on various services to function correctly. Shadow deployment can be used to validate these service dependencies. It allows developers to test if their changes are compatible with the dependent services, ensuring smooth interoperability when deployed to production.

Testing New Plugins or Extensions

Finally, shadow deployment can be used to test new plugins or extensions. Plugins and extensions often add new functionalities to an application, and it is crucial to ensure that these additions do not impact the application negatively. Shadow deployment allows for the testing of these plugins and extensions in a parallel environment, ensuring that they work as expected when deployed to production.

Shadow Deployment Vs. Other Deployment Strategies

Let’s compare the practice of shadow deployment with some of the other common deployment strategies used in the industry.

Blue-Green Deployment

Blue-green deployment is a strategy that reduces downtime and risk by running two identical production environments. The blue environment is live, while the green environment is idle. When a new version of the application is ready, it’s deployed to the idle environment, tested and, once everything is confirmed to be working, traffic is switched from the blue to the green environment. This approach allows for instant rollback if issues arise.

Shadow deployment, on the other hand, takes a slightly different approach. It involves deploying a new version of the application alongside the live version and sending the same input to both. The new version doesn’t affect the live system, and its output is discarded. This strategy allows for extensive testing and performance comparisons without any risk to the live system.

Canary Deployment

Canary deployment is another strategy that involves rolling out changes to a small subset of users before deploying it to the entire infrastructure. This strategy allows teams to test the performance of new features on a small scale before a full-scale rollout.

In contrast, shadow deployment does not expose the new version to any users. Instead, it uses real production traffic to test the new version, discarding its output to ensure it doesn’t affect the live system. This allows for full-scale testing without risking user experience.

Feature Flags

Feature flags, also known as feature toggles, allow developers to switch on or off certain features in their applications. This helps manage the rollout of new features and enables easy rollback if things go wrong.

Shadow deployment, however, focuses more on system performance rather than individual features. It uses duplicate traffic to test the entire system, providing valuable insights into how the new version will perform under real-world conditions.

Best Practices for Shadow Deployment

Now that we understand how shadow deployment fits into the broader landscape of deployment strategies, let’s delve into the best practices to follow when implementing this strategy.

Isolate Real and Shadow Systems

One of the foundational best practices for shadow deployment is the isolation of the real and shadow systems. This ensures that any problems in the shadow system do not affect the real one. The goal is to test how the new version of the software performs under real-world conditions without impacting the live system.

Set Clear Duration and End Criteria

When setting up shadow deployment, it’s crucial to define clear duration and end criteria. This involves determining how long the shadow system will run alongside the real system and what conditions will mark the end of the testing phase. This helps in maintaining control over the process and ensures that you gather the necessary data to make informed decisions.

Set Up Traffic Duplication Efficiently

Efficient traffic duplication is another critical aspect of shadow deployment. This involves mirroring the traffic from the real system to the shadow system in real-time. It’s essential to ensure that this process is efficient to get accurate performance data without overloading your network resources.

Prioritize Feedback Loops

Last but not least, prioritizing feedback loops is crucial in shadow deployment. This involves setting up mechanisms to gather and analyze data from the shadow system. The insights gleaned from this data can provide valuable feedback, helping you refine your deployment process and improve your system performance.

Conclusion

In conclusion, shadow deployment offers a unique approach to software deployment. By allowing for extensive testing under real-world conditions without affecting the live system, it provides invaluable insights into system performance. By understanding its benefits and following best practices, you can leverage this strategy to streamline your deployment process and improve your software systems.

September 29, 2023
What DevOps Teams Need to Know About Responsive Web Design

The role of DevOps in modern software development extends beyond just coding, testing and deployment. One of the significant areas where DevOps teams can bring value is delivering a positive user experience, a critical competitive advantage in the digital era. Responsive web design (RWD) is a cornerstone of a friendly user experience, allowing for seamless website functionality across various screen sizes and devices.

This article explores RWD and its fundamental principles and explains how RWD impacts web application development and deployment. We will review critical considerations for DevOps teams such as performance optimization across devices, the integration of responsive design into CI/CD pipelines, automated testing, the importance of a user-centric approach and consistent monitoring and troubleshooting. The objective is to equip DevOps teams with the necessary knowledge to effectively implement and support RWD, enhancing the user experience and significantly improving overall user satisfaction and engagement.

What is Responsive Web Design?

Responsive Web Design is a web development approach that makes your website layout adjust according to the size of the viewer’s screen. This means that your website looks and functions optimally on a wide range of devices, from desktop computers to tablets and smartphones. The primary goal of RWD is to ensure that users have an efficient and enjoyable experience, regardless of the device they are using.

With the increasing use of mobile devices for internet access, it is essential that your website is accessible and user-friendly on all platforms. By implementing RWD, your organization can ensure that your website offers a seamless user experience, no matter the device.

RWD removes the need for creating different versions of your website for different devices. Instead, you can have a single website that adjusts automatically to fit any screen size. This not only improves user experience but also saves you time and resources in website development and maintenance.

Understanding the Principles of Responsive Web Design

Fluid Grid Layouts

A fluid grid layout is a key principle of RWD. It involves designing your website layout in relative units, such as percentages, instead of absolute units like pixels. This allows your website layout to resize dynamically to fit the screen on which it is viewed.

The advantage of fluid grid layouts is that they offer more flexibility than fixed layouts. They allow your website to adjust smoothly to different screen sizes, ensuring that the user experience is not compromised. This is particularly important in today’s digital landscape, where users access websites from a wide range of devices with different screen sizes.

Flexible Images and Media

The second principle of RWD is responsive images and media. This means that your images and media files should be able to resize automatically to fit the screen size. This is essential to ensure that your images and media do not distort or overflow when viewed on smaller screens.

Flexible images and media enhance the visual appeal of your website on different devices. They also improve the loading speed of your website, which is a crucial factor for user experience and search engine ranking.

Mobile-First Design Philosophy

Mobile-first design philosophy is another key principle of RWD. As the name suggests, this approach involves designing your website primarily for mobile devices and scaling it up for larger screens.

The mobile-first design philosophy is based on the reality that a growing number of users are accessing the internet through their mobile devices. By designing your website with a mobile-first approach, you can ensure an optimal user experience on mobile devices.

Progressive Enhancement

Progressive enhancement is the fourth principle of RWD. It involves building your website in layers, starting with a basic layer that works on all devices and then adding more features and functionalities for devices with advanced capabilities.

Progressive enhancement allows you to provide a basic, functional website for all users regardless of their device or browser. At the same time, it enables you to offer an enhanced website experience for users with modern devices and browsers.

How RWD Affects Application Development and Deployment

Responsive web design has a significant impact on the development and deployment of web applications. It affects various aspects of the process, including the codebase, development and testing process, user interface design and deployment and updates.

Unified Codebase

One of the main benefits of RWD is that it allows you to maintain a unified codebase. Instead of creating separate versions of your application for different devices, you can have a single codebase that works across all platforms.

A unified codebase simplifies the development and maintenance process. It eliminates the need for duplicate coding and testing, saving you time and resources. It also ensures consistency in your application, as all users are accessing the same codebase, regardless of their device.

Development and Testing Process

RWD also influences the development and testing process. Since your application needs to work optimally on various devices and screen sizes, you need to incorporate responsive design considerations into your development and testing process.

Responsive design testing involves checking your application on different devices and screen sizes to ensure that it functions and displays correctly. This can be done manually, using device emulators or through automated testing tools.

User Interface Design

The user interface (UI) design of your application is also affected by RWD. A responsive UI design ensures your application is easy to use and visually appealing on all devices.

Responsive UI design involves creating a flexible layout that adjusts automatically to the screen size. It also requires you to design intuitive navigation and interaction elements that work well on touchscreens and desktop interfaces.

Deployment and Updates

Finally, RWD has implications for the deployment and updates of your application. With a responsive application, you can deploy and update a single version of your application for all devices.

This simplifies the deployment and update process and ensures that all users have access to the latest version of your application. It also makes it easier to fix bugs and issues, as you only need to update a single codebase.

Key Considerations for DevOps Teams

Implementing RWD is not a straightforward task. It requires careful planning and consideration. Here are some key considerations for DevOps teams when implementing RWD.

Ensuring Website Performance Across Different Devices

One of the main challenges in implementing RWD is ensuring that your website performs well on all devices. This requires careful optimization of your website elements, including images, CSS and JavaScript.

You also need to consider factors like loading speed and responsiveness, as these can significantly affect user experience. There are a number of available tools to help you analyze and optimize your website performance.

Incorporating Responsive Design into CI/CD

Continuous integration and continuous delivery (CI/CD) are key practices in DevOps. CI/CD involves integrating code changes regularly and delivering updates to users quickly and reliably. Incorporating responsive design in your CI/CD process can help you ensure that your application is responsive and user-friendly at all times.

Automation in Testing

Testing is a crucial part of the development process. With RWD, testing becomes more complex as your application needs to work on a wide range of devices and screen sizes. Automation can help streamline the testing process and ensure that your application is tested thoroughly and efficiently.

User-Centric Approach

A user-centric approach is essential in implementing RWD. This means considering the needs and preferences of your users at every stage of the development process. From the design phase to testing and deployment, the user experience should be at the forefront of your considerations.

Monitoring and Troubleshooting Responsive Design Issues

Finally, monitoring and troubleshooting are important aspects of implementing RWD. You need to monitor your website performance on different devices and troubleshoot any responsive design issues that arise.

Analytics tools can provide valuable insights into how your website is performing on different devices. They can also help you identify and fix any issues that are affecting your website’s responsiveness.

Conclusion

In conclusion, responsive web design is an essential aspect of modern web development. It ensures your website is accessible and user-friendly on all devices, improving user experience and engagement. By understanding the principles of RWD and considering the key aspects of implementing it, you can unlock the power of responsive design and take your website to the next level.

September 28, 2023
Innersourcing Open Source Principles in the Enterprise
Software development has experienced a seismic shift in recent years, with open source becoming the heartbeat of innovation. A full 90% of enterprise IT leaders say their organization is using open source, according to a Red Hat report. Leading this transformation is GitHub, the ubiquitous platform that not only jumpstarted the open source movement but has also been quietly transforming how enterprises approach development at large.

But it’s not just tech companies trumpeting the open source creed—academics are on board, too. A paper recently published by the University of Georgia found a hard-to-dismiss correlation between open source innovation and overall business success. “We find a significantly positive association between GitHub activity and future realized net income, suggesting that open innovation is a strong predictor of future earnings,” according to the report.

I recently met with Chris Reddington, senior manager of developer advocacy at GitHub, to dive into how and why open source is becoming essential for enterprise innovation. According to Reddington, the once-dominant proprietary information mindset is shifting, with open source cultural principles now permeating most companies, a practice also known as innersource. Put simply, open source is now cool in the enterprise.

Bridging the Open Source-Enterprise Divide

GitHub’s close ties to the open source space have allowed them to illuminate the parallels between the open source and enterprise worlds. Reddington noted that, nowadays, open source and enterprise aren’t really separate communities but rather intertwined facets of the same software ecosystem. This movement is represented by the open source program office (OSPO) becoming more commonplace in large organizations.

For an example of innersource in practice, take Porsche, who recently announced the Porsche FOSS Movement to guide internal common values and development principles around open source. We’ve also seen similar large-scale commitments to open source values at Walmart, Spotify, Facebook and others.

Open source clearly isn’t just for startups—large companies are increasingly seeing an advantage in both using open source software and sharing their own open source components. The growing investment and maturation of OSS initiatives are positive strides, as it’s important to the stability of the free open source software (FOSS) ecosystem as a whole that those using software contribute back to its maintenance, especially to core packages the world depends upon.

The Power of Innersource

The study from the University of Georgia brings to light how enterprises increasingly recognize the need to work in sync with their developers and customers to remain competitive. This is a testament to the evolving nature of development—an industry that’s embracing a “team sport” mentality instead of a siloed approach, explained Reddington. And as enterprises align with open source principles, they are discovering the power of innersource, he said. “Innersource is a development methodology where engineers build proprietary software using best practices from large-scale open source projects, like Kubernetes or Microsoft’s Visual Studio Code,” GitHub explained.

Reddington elaborated on two key elements of this approach:
- Breaking down silos: The traditional organization-centric structure of projects is being replaced by a more transparent and collaborative approach. Innersource encourages transparency and asynchronous communication, tearing down barriers that previously inhibited efficient collaboration.
- Engaging responsibly: Reddington emphasized the significance of enterprises giving back to the open source community. Whether through sponsorships, allocating time for engineers to contribute, or open sourcing their projects, companies can foster symbiotic relationships where they benefit from and contribute to the open source realm.
Essentially, by adopting innersource principles, enterprises foster an environment that promotes collaboration and knowledge sharing, thus enabling innovation to flourish across teams and projects.

Balancing Open Innovation and Proprietary Software

One of the most intriguing aspects of this transformation is finding the equilibrium between open innovation and proprietary software. Reddington acknowledged the necessity for businesses to generate profits, which inherently stems from delivering value.

While reinventing the wheel may be tempting, Reddington highlighted the importance of recognizing existing solutions and incorporating them into ongoing projects. This pragmatic approach maximizes efficiency and enables teams to focus on the unique, value-generating aspects of their work.

Organizations should also consider what software of their own could be open sourced. From a business perspective, this most likely won’t be the “crown jewels,” said Reddington, but ancillary components that others could benefit from. For example, had it not been for Google open sourcing Kubernetes, Lyft open sourcing Envoy Proxy or Facebook sharing GraphQL, we would not have these standard components for all to use.

Open Source Movements: Past, Present, and Future

Over the last decade, we’ve seen significant, more institutional maturation around open source projects. Reddington pointed to the Cloud Native Computing Foundation (CNCF) as a standout. He specifically noted Kubernetes-based Event Driven Autoscaler (KEDA) as a cool project to help scale Kubernetes containers based on the number of events needing to be processed.

He also underscored the surge of interest in generative AI, evidenced by projects like GitHub Copilot. It will be curious to see how AI assistants incorporate open source at their core, such as open foundational models and community-supported datasets.

Potential Setbacks To The Open Source and Innersource Movement

In the dynamic realm of enterprise-scale software development, nurturing innovation can be a complex endeavor. Innersource principles are one way to change the attitude toward development, making it more efficient, collaborative and aligned to the current and future developer experience expectations.

Yet, this isn’t to say we haven’t had some setbacks recently that could threaten the progress the OSS community has built. For example, HashiCorp recently abandoned its open source license around Terraform in favor of a business source license (BSL). There is also an increasing number of supply chain-related attacks that threaten common open source libraries.

Gazing Into the Future

As Reddington aptly summarized, we’re still in the early days of this transformative journey. The developer community’s inclination for experimentation will undoubtedly drive the solutions to the most pressing challenges in open source. And with enterprise adoption on the rise, the future promises more cohesive collaboration, broader adoption of innersource principles and continued innovation driven by open source values.

Interestingly, we’re seeing more synergy between open source and enterprise domains, which used to feel like separate realms entirely. And it will be interesting to see how businesses continue to balance transparency and proprietary value into the future. No matter what, the lines between them are blurring, enabling companies to harness the power of innersource for enhanced collaboration and innovation.
September 21, 2023
Synopsys Taps NowSecure and Secure Code Warrior to Improve DevSecOps

Synopsys has partnered with NowSecure and Secure Code Warrior to enable organizations to better identify where they can improve DevSecOps best practices.

Scott Johnson, senior director of product management for the Software Integrity Group at Synopsys, said the data captured by the application security testing tools can now more easily be used to identify ongoing issues that, for example, can be used to create better mobile application security tests using the NowSecure platform.

That same data can also be fed into the online learning platform Secure Code Warrior provides to enable developers to improve their cybersecurity skills.

Collectively, those observability capabilities will significantly reduce the overall level of application security risk that organizations today experience, noted Johnson.

Secure Code Warrior CTO Matias Madou noted that improving the cybersecurity expertise of developers is more critical than ever. The more expertise they have the easier it becomes to remediate issues before and after applications are deployed in a production environment.

That’s going to become an even more crucial requirement as the rate at which code is being written increases exponentially with the rise of artificial intelligence (AI). While AI can improve the quality of code being written, it’s also likely an AI platform trained using code collected from the internet is going to introduce vulnerabilities. This is because the code used to train an AI model, such as ChatGPT, from a quality perspective is inconsistent, he added.

It’s not clear at what rate application security is improving due to the adoption of DevSecOps best practices, but as AI becomes more widely employed by developers a paradox is starting to emerge. There is no doubt vulnerabilities developers have inadvertently introduced are being eliminated by AI tools that surface examples of secure code for developers to copy and paste. However, not every example of code is completely devoid of risk, so there is going to be more code that needs to be scanned for vulnerabilities.

This issue will become particularly problematic as regulations making organizations more accountable for application security will become law in the months ahead. Thanks to AI, there is no doubt organizations will be building and deploying applications containing vulnerabilities at much faster rates.

The hope is that AI tools specifically trained to identify vulnerabilities will soon be embedded in the tools that developers and DevOps teams rely on to initially build and deploy applications. However, a gap is emerging between the pace at which AI tools are being used to build applications and the availability of tools using AI to first detect vulnerabilities and help automate the remediation process. As a result, application security issues, at least for the immediate future, will continue to bedevil DevOps teams.

Unfortunately, given the insecure code that has already been deployed, it may be years before application security issues are resolved to the point where the current level of stress for all concerned is meaningfully reduced.

August 18, 2023
How to Empower DevSecOps in a Complex Multi-Cloud Landscape

Organizations are embracing cloud-based application delivery for speed of delivery and scale. However, the proliferation of multi-cloud systems to access and maximize the cloud’s capabilities is driving complexity in IT environments. Many organizations do not consider how multi-cloud adoption is expanding their attack surface—and the risk is growing: The 2023 CrowdStrike Global Threat Report found cloud exploitation cases grew by 95% year-over-year and cases involving threat actors targeting cloud environments were up 288% from a year prior.

The expansion of cloud infrastructure and services has increased the pressure on organizations to protect assets within their multi-cloud environments. To alleviate this burden, more businesses are turning to DevSecOps, a practice that incorporates security at an earlier point in the development life cycle. This practice of shifting left helps improve the quality and reduces risk of applications, as well as makes the delivery of these applications more efficient since any potential issues are found earlier in the development process.

DevSecOps is being adopted rapidly by organizations today to address the expanding array of threats and increasingly sophisticated attacks targeting multi-cloud environments. However, securing the cloud can be tricky due to its dynamic nature and multi-cloud makes shift left security even more complex. For DevSecOps to truly be effective, here are three things that organizations should consider doing.

1. Strive for Complete Visibility in a Multi-Cloud Environment

It is important that DevSecOps teams have a comprehensive understanding of their multi-cloud environment. Without it, they will not be able to identify a variety of security risks including vulnerabilities, privileged credentials, misconfigurations and other threats that may leave their organization’s cloud assets vulnerable.

The best way to get full visibility across multi-cloud environments is through a cloud security posture management (CSPM) tool. With a CSPM tool, DevSecOps teams can identify misconfigurations and proactively detect threats. In addition, DevSecOps teams should also use a cloud infrastructure entitlement management tool (CIEM) to manage identities across all of their cloud infrastructure resources. The primary goal of a CIEM tool is to mitigate the risk that comes from the unintentional and unchecked granting of excessive permissions of user credentials.

2. Visibility and Compliance Do Not Guarantee Security

Organizations need to develop a comprehensive security strategy to mitigate issues within the development process. This may include implementing tools, automation and standards to enable developers to follow the desired security behavior. These approaches reduce developer friction, as well as diminish the likelihood that unsafe or default configurations will be used. Historically, DevOps teams have pushed back on integrating security since their concern is that it slows down the development lifecycle. However, DevSecOps is gaining traction in recent years because organizations are realizing integrating security sooner in the development lifecycle is more efficient than reactively patching problems as they arise.

A tool that DevSecOps teams should look to leverage is cloud workload protection (CWP) because it offers breach protection for workloads, containers and Kubernetes, while enabling them to continue to build, run and secure applications with speed and confidence.

3. Create Consistency With Security Tools

Ideally, organizations should opt for a single platform that consolidates capabilities such as CSPM, CWP and CIEM. The reason for consolidation is to eliminate security gaps from having multiple security solutions. As a result, DevSecOps teams should turn to cloud-native application protection platform (CNAPP) tools to create more consistency within the multi-cloud environment.

Securing multi-cloud environments can be complex. By empowering DevSecOps teams using these best practices, organizations will be able to move faster than today’s adversaries and have the agility to quickly adapt to present and future cybersecurity challenges in their multi-cloud environments.

June 23, 2023