#continous integration

As businesses push toward digital transformation, platform engineering has emerged as a key driver of efficiency, agility, and scalability. A well-implemented platform engineering strategy can streamline software development, enhance collaboration, and reduce operational complexities. In this blog, we'll explore the latest platform engineering strategies that can help organizations stay competitive and innovate faster.

What is Platform Engineering?

At its core, platform engineering is the process of designing and building technology platforms that empower development teams to deliver software faster and more efficiently. This discipline involves creating a shared infrastructure and set of tools, allowing engineering teams to focus on writing code rather than managing environments.

1. Adopt Infrastructure as Code (IaC)

One of the most crucial platform engineering strategies is adopting Infrastructure as Code (IaC). By automating infrastructure provisioning, IaC reduces the risk of human error and ensures that development environments remain consistent. Tools like Terraform and AWS CloudFormation have become industry standards, enabling teams to version control their infrastructure just like they do with application code.

2. Implement a Self-Service Platform

Another key strategy in platform engineering is building a self-service platform for development teams. These platforms can automate repetitive tasks, such as environment provisioning, application deployment, and monitoring setup. A self-service approach empowers developers to quickly access resources without relying on centralized IT teams, speeding up the software delivery process.

3. Embrace Observability

With increasing system complexity, observability is becoming an essential part of any platform engineering strategy. Implementing comprehensive monitoring and logging tools like Prometheus, Grafana, and ELK Stack ensures that teams can detect, troubleshoot, and fix issues before they escalate. This approach reduces downtime and also enhances system reliability.

4. Microservices and Containerization

Microservices and containerization, facilitated by technologies like Kubernetes and Docker, have become foundational in modern platform engineering strategies. These technologies allow organizations to build scalable, modular applications that can be updated independently. Container orchestration platforms enable automated scaling, health checks, and rolling updates, ensuring continuous delivery and minimizing disruptions.

5. Security by Design

Security should be embedded into every layer of your platform engineering process. From automated security checks in CI/CD pipelines to integrating tools like Vault for secrets management, security by design ensures that your infrastructure and applications remain secure throughout their lifecycle. A robust platform engineering strategy includes continuous vulnerability scanning, threat detection, and incident response.

6. Collaboration Between Dev and Ops

Successful platform engineering strategies hinge on strong collaboration between development and operations teams. This is where DevOps practices play a pivotal role. By adopting a DevOps culture, teams can align their goals, improve communication, and work together to streamline software delivery. Platform engineering acts as the enabler of DevOps, providing the infrastructure and tools required for automation and seamless operations.

7. Continuous Integration and Continuous Delivery (CI/CD)

Automation is the backbone of any modern platform engineering strategy. Implementing CI/CD pipelines allows for continuous testing, integration, and delivery of code. Platforms like Jenkins, GitLab, and CircleCI enable development teams to release features faster while maintaining high-quality standards.

8. Scalability and Performance Optimization

A vital component of platform engineering is ensuring that the infrastructure scales with the growing demands of the business. Utilizing autoscaling techniques and performance optimization tools like AWS Auto Scaling, load balancers, and CDN integration can ensure high availability even during peak loads. This proactive approach guarantees optimal performance and prevents bottlenecks.

Conclusion

All we have written Shell scripts. And at the speed we need to deploy is easy to make mistakes (beginner mistakes). So I decided to integrate Shellcheck in Jenkins so that when a commit is done the CI drops a complete shell check analysis of the code.

A test in your CI could be something like:

grep -rIl '^#![[:blank:]]*/bin/\(bash\|sh\|zsh\)' \ --exclude-dir=.git --exclude=*.sw? \ | xargs…

I had many problems with Jenkinsfiles lately. The syntax is so picky that after a push my plan fails just because I forgot a comma or something as ridiculous as that. In my opinion there are better human input methods for such a file, like yaml. But hey! I’m not developing Jenkins.

Anyway I just integrated a target into my project makefile to test the validity of the Jenkins file. The only way in…

Integrating npm jsonlint in your CI

Today I received a pull request on a JSON file where the indentation looked just wrong. We decided to look for a linting solution to run on our CI with some requirements:

It should validate and point out broken JSON.

It should fix indentation.

It should not sort JSON objects.

After some research we found different options with different levels of quality and livelyness. Actually the most…

DevOps with Chef. Sweet.

I needed to setup few servers for QA and provision development environments for my team so I started a small make-based repo where to put all the nasty configuration and provisioning stuff. After few days of work I decided to look for solutions in the world wide web. Then discovered DevOps discipline.

DevOps enlightened me. Is exactly what I was looking for!

I work in an industrial environment…

Definition: Teams practicing continuous integration seek two objectives:

minimize the duration and effort required by "each" integration episode

be able to deliver "at any moment" a product version suitable for release

In practice, this dual objective requires an integration procedure which is "reproducible" at the very least, and in fact largely "automated". This is achieved through version control tools, team policies and conventions, and tools specifically designed to help achieve continuous integration.

Things to be considered before and while doing continuous integration:

Why we want to change?

Get measurable business improvements/impacts by continuous integration - take incremental approach.

Focus on organization and architecture rather than tools, code, infrastructure.

Create culture of continuous improvement.

Check where are we in continuous integration process

This section is borrowed from Jenkins: The Definitive Guide.

Continuous Integration is not an all-or-nothing affair. In fact, introducing CI into an organization takes us on a path that progresses through several distinct phases. Each of these phases involves incremental improvements to the technical infrastructure as well as, perhaps more importantly, improvements in the practices and culture of the development team itself. The following sections paint an approximate picture of each phase.

Phase 1 - No Build Server

Initially, the team has no central build server of any kind. Software is built manually on a developer's machine, though it may use an Ant script or similar to do so. Source code may be stored in a central source code repository, but developers do not necessarily commit their changes on a regular basis. Some time before a release is scheduled, a developer manually integrates the changes, a process which is generally associated with pain and suffering.

Phase 2 - Nightly Builds

In this phase, the team has a build server, and automated builds are scheduled on a regular (typically nightly) basis. This build simply compiles the code, as there are no reliable or repeatable unit tests. Indeed, automated tests, if they are written, are not a mandatory part of the build process, and may well not run correctly at all. However developers now commit their changes regularly, at least at the end of every day. If a developer commits code changes that conflict with another developer's work, the build server alerts the team via email the following morning. Nevertheless, the team still tends to use the build server for information purposes only-they feel little obligation to fix a broken build immediately, and builds may stay broken on the build server for some time.

Phase 3 - Nightly Builds and Basic Automated Tests

The team is now starting to take Continuous Integration and automated testing more seriously. The build server is configured to kick off a build whenever new code is committed to the version control system, and team members are able to easily see what changes in the source code triggered a particular build, and what issues these changes address. In addition, the build script compiles the application and runs a set of automated unit and/or integration tests. In addition to email, the build server also alerts team members of integration issues using more proactive channels such as Instant Messaging. Broken builds are now generally fixed quickly.

Phase 4 - Enter the Metrics

Automated code quality and code coverage metrics are now run to help evaluate the quality of the code base and (to some extent, at least) the relevance and effectiveness of the tests. The code quality build also automatically generates API documentation for the application. All this helps teams keep the quality of the code base high, alerting team members if good testing practices are slipping. The team has also set up a "build radiator," a dashboard view of the project status that is displayed on a prominent screen visible to all team members.

Phase 5 - Getting More Serious About Testing

The benefits of Continuous Integration are closely related to solid testing practices. Now, practices like Test-Driven Development are more widely practiced, resulting in a growing confidence in the results of the automated builds. The application is no longer simply compiled and tested, but if the tests pass, it is automatically deployed to an application server for more comprehensive end-to-end tests and performance tests.

Phase 6 - Automated Acceptance Tests and More Automated Deployment

Acceptance-Test Driven Development is practiced, guiding development efforts and providing high-level reporting on the state of project. These automated tests use Behavior-Driven Development and Acceptance-Test Driven Development tools to act as communication and documentation tools and documentation as mush as testing tools, publishing reports on test results in business terms that non-developers can understand. Since these high-level tests are automated at an early stage in the development process, they also provide a clear idea of what features have been implemented, and which remain to be done. The application is automatically deployed into test environments for testing by the QA team either as changes are committed, or on a nightly basis; a version can be deployed(or "prompted") to UAT and possibly production environments using a manually-triggered build when testers consider it ready. The team is also capable of using the build server to back out a release, rolling back to a previous release, if something goes horribly wrong.

Phase 7 - Continuous Deployment