OpenShift: Transforming the Way We Develop and Deploy Applications

In recent years, the demand for robust and flexible container platforms has grown exponentially, driven by the need for companies to deploy and manage their applications in an agile, secure, and efficient manner. In this scenario, OpenShift emerges as an interesting solution, offering not just container orchestration but a complete ecosystem for application development, deployment, and operation at scale.

The platform, developed by Red Hat, a partner of Objective, has stood out in the market due to its ability to simplify and automate processes ranging from initial deployment to dynamic scaling, through continuous integration, advanced monitoring, and strengthened cybersecurity.

A Forrester Consulting report highlights the economic and operational benefits of OpenShift, including improved speed of application development and deployment, as well as reduced operational costs. This article explores the various facets of OpenShift, from application deployment to real-world examples of its success in companies across different sectors, providing a great opportunity for you to learn more about the topic. Enjoy your reading!

What is OpenShift?

OpenShift is a cloud application platform developed by Red Hat, designed to facilitate the development, deployment, and management of containerized applications. Based on Kubernetes, OpenShift offers an enhanced experience by integrating additional tools that simplify container orchestration. With support for multiple programming languages and frameworks, the platform stands out for its flexibility, allowing developers to build, test, and scale applications efficiently. Additionally, OpenShift includes robust security features such as network isolation policies and role-based authentication, ensuring the protection of applications.

One of the main benefits of OpenShift is its ability to support multi-cloud and hybrid environments, providing portability and flexibility to applications. This means that companies can deploy their applications on public clouds, private clouds, or hybrid configurations without complications. The platform also facilitates the automation of continuous integration and delivery (CI/CD) pipelines, improving DevOps teams’ productivity by automating repetitive and complex tasks. With these functionalities, OpenShift not only modernizes IT infrastructure but also accelerates innovation and delivery of value to customers.

Application Deployment with OpenShift

This is an efficient and automated process that leverages Kubernetes’ advanced container orchestration features, combined with additional tools and resources provided by the OpenShift platform. Application deployment with OpenShift brings benefits such as ease of deployment, automatic scalability, efficient resource management, integrated monitoring, advanced security, portability, and team collaboration. These benefits contribute to greater efficiency, scalability, and security in the development and operations environment.

Here are some steps in the application implementation process with OpenShift:

Environment Configuration

The first step in deploying applications with OpenShift is environment configuration. This involves creating projects and defining necessary resources such as namespaces, resource quotas, and security policies.

Creating Container Images

Applications are packaged in Docker containers. OpenShift offers integrated tools to create and manage these container images, such as Source-to-Image (S2I), which facilitates converting source code into container images ready for deployment.

Image Registry

Container images are stored in an image registry. OpenShift has an integrated image registry but can also integrate with external registries like Docker Hub or private company registries.

Configuring Deployments

Deployments in OpenShift are configured using Kubernetes objects such as Deployments, StatefulSets, and DaemonSets. These objects define how and where containers should be deployed, ensuring scalability and high availability.

CI/CD Automation

OpenShift supports continuous integration and delivery (CI/CD) pipelines through tools like Jenkins, Tekton, and OpenShift Pipelines. This allows teams to automate the building, testing, and deployment of applications, improving efficiency and reducing delivery time.

Monitoring and Logging

After deployment, OpenShift offers monitoring and logging tools such as Prometheus and Grafana, which help track application performance and identify issues in real-time.

What is Autoscaling with OpenShift?

One of the main advantages of autoscaling is cost reduction. It allows companies to increase or decrease computing resources as needed, avoiding the need to provision excessive resources in advance. For example, Conflux Technologies managed to reduce IT costs by 40% by using AWS Auto Scaling to adjust capacity as needed.

Associating autoscaling with OpenShift is an efficient process as it automatically adjusts the number of replicas of an application in response to changes in workload. This feature is important to ensure that the application maintains adequate performance and availability even under varying loads.

Here are the main components and the functioning of autoscaling in OpenShift:

Horizontal Pod Autoscaler (HPA)

HPA is a Kubernetes feature that automatically adjusts the number of pods in a replication controller, deployment, or replica set based on observed metrics. In OpenShift, HPA is widely used to manage pod autoscaling.

Resource Metrics

HPA can scale pods based on resource metrics such as CPU and memory. It monitors these metrics in real-time and adjusts the number of replicas according to the configured limits.

Custom Metrics

In addition to standard resource metrics, HPA can be configured to use custom metrics such as response latency or the number of requests per second, allowing for more refined control over scaling.

Cluster Autoscaler

To scale the cluster’s resources itself, OpenShift can use Cluster Autoscaler, which adjusts the number of nodes in the cluster to meet the resource demands of the pods.

Functioning of OpenShift Autoscaling

Understanding the functioning of autoscaling is essential to optimize task distribution, ensure operational efficiency, improve team productivity, meet deadlines and priorities, and avoid resource overload or idleness.

Here’s how to do it:

HPA Configuration

The first step is to configure the Horizontal Pod Autoscaler. This involves defining a scaling policy that specifies the metrics to be monitored (e.g., CPU utilization) and the upper and lower limits for the number of replicas.

Continuous Monitoring

HPA continuously monitors the specified metrics. In the case of CPU utilization, it collects data on the current CPU usage of the application pods.

Replica Adjustment

Based on monitoring data, HPA automatically adjusts the number of pod replicas. If CPU utilization exceeds the specified target (e.g., 80%), HPA will increase the number of replicas to distribute the load. Similarly, if CPU utilization is below the target, HPA will reduce the number of replicas to save resources.

Node Scaling

If the cluster does not have enough capacity to accommodate new pods, Cluster Autoscaler can add more nodes to the cluster. Similarly, if the number of pods decreases and nodes are underutilized, Cluster Autoscaler can remove unnecessary nodes to optimize costs.

Security in OpenShift

Security is an important aspect when using OpenShift, and neglect can lead to serious problems. Although there are no records of scandals associated with the use of OpenShift, Red Hat, the company behind OpenShift, provides robust standard security policies covering various phases of the software lifecycle. These policies help identify and prevent the deployment of high-risk services and respond to security incidents in real-time.

Security can be ensured in OpenShift by adopting best practices such as:

Configuring Security Policies

Implement and follow strict security policies, such as those provided by Red Hat Advanced Cluster Security, to identify and mitigate risks.

Regular Updates and Patches

Keep OpenShift and its components always up to date to protect against known vulnerabilities.

Use of DevSecOps Security Practices

Integrate security into the software development lifecycle, ensuring that security is a continuous part of system development and operation.

Now that you know the importance of staying up to date with security recommendations, here’s how OpenShift helps against potential threats:

Data and Application Protection

Containers share the same host kernel, meaning a vulnerability in one container can potentially compromise other containers and the host system. OpenShift implements rigorous isolation measures using namespaces, control groups (cgroups), and SELinux to ensure containers operate in isolation, minimizing the risk of privilege escalation and unauthorized access.

Container Image Management

OpenShift allows the use of secure image registries and digital signatures to ensure only verified and trusted images are deployed in the environment. This prevents the introduction of malicious code through compromised images.

Compliance and Governance

OpenShift offers granular role-based access control (RBAC) and integrates with identity providers like LDAP and OAuth. This ensures that only authenticated and authorized users can access specific resources according to their responsibilities and operational needs.

Logging and Auditing

The ability to track and audit all activities in the cluster is essential to meet compliance requirements and investigate incidents. OpenShift provides detailed logs and auditing mechanisms that allow monitoring user actions, accesses, and system changes.

Incident Response and Recovery

OpenShift integrates with monitoring and threat detection tools like Prometheus and Grafana, enabling proactive identification of suspicious or anomalous activities. This allows for quick responses to security incidents, minimizing damage and downtime.

Backup and Recovery

Implementing effective backup and recovery strategies is crucial to ensure business continuity in case of attacks or failures. OpenShift supports backup solutions that ensure the quick and secure restoration of data and applications.

Software Supply Chain Security

OpenShift promotes the practice of DevSecOps, integrating security from the beginning of the software development lifecycle. This includes continuous vulnerability scanning during development, integration, and continuous delivery (CI/CD), ensuring security is embedded at every stage of the development process.

Why Invest in Continuous Integration with OpenShift?

Continuous Integration (CI) with OpenShift can be configured to automate the process of building, testing, and deploying applications. This ensures that each code change is quickly verified and integrated into the production environment, improving development efficiency and quality.

Investing in continuous integration with OpenShift has shown significant benefits for companies. Red Hat highlights that using OpenShift Pipelines, based on Tekton, helps automate deployments on multiple platforms and scale as needed, increasing the efficiency of decentralized teams working with microservices-based architectures. This facilitates the construction of images with Kubernetes tools like Source-to-Image (S2I), Buildah, Buildpacks, and Kaniko, which are portable on any Kubernetes platform, promoting more efficient and agile integration.

Here are the main steps and components for implementing CI with OpenShift:

OpenShift Configuration

Ensure you have a configured and functioning OpenShift cluster.

Version Control Tool

Use a version control tool like Git to manage the source code of your project.

Continuous Integration Server

Choose a CI/CD tool like Jenkins, GitLab CI/CD, CircleCI, among others, to automate the continuous integration process.

CI/CD Pipeline

Create a CI/CD pipeline that includes steps such as build, automated tests, static code analysis, artifact construction, deployment in test and production environments, among others.

Docker and Kubernetes

Use Docker containers to package your application and Kubernetes to orchestrate and manage the containers in OpenShift.

Deployment Automation

Automate the process of deploying new application versions in OpenShift, ensuring consistency and reliability.

Monitoring and Logging

Implement monitoring and logging tools to track application performance and identify potential issues.

Feedback and Continuous Improvement

Analyze test results, performance metrics, and user feedback to continuously improve the CI/CD process.

Application Monitoring in OpenShift

Application monitoring in OpenShift is crucial to ensure the health, performance, and availability of applications. OpenShift provides a range of integrated tools and best practices for effective monitoring.

Here are the main aspects and tools involved:

Prometheus

An open-source system monitoring and alerting toolkit, Prometheus is used to collect real-time metrics from OpenShift resources. It offers a flexible query language (PromQL) to explore these metrics and create alerts based on specific conditions.

Grafana

An open-source software used for metrics analysis and visualization, Grafana can be integrated with Prometheus to create interactive dashboards that help monitor the health of applications and infrastructure in real-time.

Elasticsearch, Fluentd, and Kibana (EFK) Stack

The EFK stack is a popular solution for log collection, storage, and visualization. Fluentd collects logs from applications and the system, Elasticsearch stores these logs, and Kibana allows for the creation of dashboards and queries on these log data.

Thanos

A long-term storage solution for Prometheus, Thanos allows the aggregation of multiple Prometheus instances and provides long-term data storage, enabling historical metrics analysis.

Best Practices for Application Monitoring in OpenShift

Defining proactive alerts is essential for efficient system management. Using Prometheus to configure alerts based on specific conditions, such as high CPU or memory usage, application failures, or network issues, allows for rapid problem detection. Additionally, configuring Alertmanager to send notifications via email, Slack, or other channels when an alert is triggered ensures that responsible teams are immediately informed, enabling a quick response.

For log collection and analysis, using the EFK (Elasticsearch, Fluentd, and Kibana) stack is highly effective. Configuring Fluentd to capture logs and Elasticsearch to store them efficiently facilitates the management of large data volumes. With Kibana, it is possible to create visualizations that allow real-time log monitoring and investigation, helping to identify and resolve issues quickly.

In monitoring distributed applications such as microservices, using distributed tracing tools like Jaeger is crucial. These tools allow for monitoring transactions between services and identifying bottlenecks or failures, providing a clear view of application performance and health.

Finally, automation and scalability are fundamental for handling large data volumes. Automating the collection of metrics and logs using ConfigMaps and Secrets to manage configurations simplifies system maintenance and operation. Additionally, horizontally scaling monitoring components ensures that the system can efficiently handle increased demand, ensuring stable and consistent performance.

Success Stories

OpenShift has been an interesting solution for many organizations across various sectors, helping them overcome challenges and achieve their digital transformation goals.

Here are some examples of success with the use of OpenShift:

Superintendency of Industry and Commerce of Colombia (SIC)

The Superintendency of Industry and Commerce of Colombia faced the challenge of modernizing consumer protection and market control processes, all of which were paper-based. With the COVID-19 pandemic, the need to digitize these processes became critical. SIC implemented OpenShift to build a new digital platform that simplified operations, improved citizen access, and met strict electronic record regulations. This implementation allowed the agency to operate efficiently even during lockdowns, facilitating the electronic submission of complaints and cases.

Credit Europe Bank

Credit Europe Bank sought a solution to accelerate its integrations and adopt a cloud-based microservices approach. By implementing OpenShift, the bank managed not only to modernize its infrastructure but also to ensure flexibility and quick market responses. OpenShift helped create an agile development environment with clusters for development, testing, pre-production, and disaster recovery, improving the bank’s resilience and operational efficiency.

Porsche Informatik

Porsche Informatik, an IT service provider for the Volkswagen Group, used OpenShift to migrate its legacy infrastructure to a platform supporting cloud-native application development. The company accelerated the development and delivery of applications, staying competitive in a fast-paced global market. Using OpenShift provided a stable environment for end-user applications and supported continuous integration and delivery (CI/CD) pipelines for development teams.

Objective is a partner of Red Hat, a leader in open-source and cloud software solutions. The alliance aims to offer robust and innovative solutions, integrating Objective’s expertise with Red Hat’s technology. Relying on these two partners is a smart way for your company to access best practices in software development, modern IT infrastructure, and excellent technical support.

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