OutSoft /
The current database infrastructure relies on Oracle AWS RDS, which poses challenges such as high licensing costs, vendor lock-in, and limited flexibility in integrating with modern, open-source technologies. There is a need to migrate to a more cost-effective, scalable, and open-source solution without compromising data integrity and application performance.
AWS
Before implementing the DevSecOps approach, our software development pipeline lacked integrated security measures, leading to potential vulnerabilities being detected late in the development cycle. This delayed releases, increased remediation costs, and posed significant security risks to our applications and data. Additionally, the lack of automated security checks meant that the development and operations teams had to manually handle security issues, leading to inefficiencies and potential oversight.
Jenkins
Previously, Development, Test, and Production environments were all located within a single AWS account. This setup led to several issues including difficulty in managing and isolating resources, challenges with enforcing security and access controls, and increased risk of accidental changes impacting production systems.
AWS
Сloudfront
Сloudflare
The software delivery process was slow and error-prone due to manual steps and lack of automation. This inefficiency led to longer development cycles and delayed releases, impacting the team’s ability to quickly respond to market needs and deliver features in a timely manner.
Gitlab
Previously, there was no formal disaster recovery plan in place, leaving the organization vulnerable to prolonged downtime and data loss in the event of unexpected incidents such as system failures, natural disasters, or cyberattacks. This lack of a structured approach risked significant business disruptions and could have resulted in extended recovery times and data integrity issues.
AWS
Digital
MSK
Redis
Open Search
Сloudflare
Before implementing CI/CD, the software development process was manual and fragmented, leading to slow release cycles, inconsistent deployments, and frequent integration issues. This lack of automation caused delays in delivering updates and introduced risks of errors during the deployment process, impacting overall productivity and product quality.
Jenkins
The organization needed to establish a new, scalable, and secure infrastructure from scratch to support both development and production environments. The lack of a clear separation between these environments led to challenges in managing and scaling resources effectively, increased risks of impacting production with development changes, and difficulties in maintaining consistent and secure infrastructure setups.
AWS
Сloudfront
Сloudflare
The existing infrastructure management process was manual, leading to inefficiencies, inconsistencies, and difficulty in scaling or replicating environments. This approach increased the risk of errors and slowed down deployment times.
AWS
Terraform
Ansible
The existing monolithic application architecture was limiting scalability and agility, causing challenges in handling increased traffic and making it difficult to deploy new features or updates. The application’s performance and responsiveness were impacted as the user base and demand grew.
Kuberneres
The existing monitoring system was insufficient for detecting and responding to performance issues and outages in a timely manner. The lack of effective alerting and monitoring led to delays in identifying critical issues, impacting system reliability and user satisfaction.
Prometheus
Integration with Slack
Building a robust and scalable infrastructure for a game streaming platform was crucial for delivering real-time, low-latency streaming services to an audience. The platform must have handled large spikes in traffic during live cyber sport events, ensured seamless streaming quality, and allowed users to interact with the platform without interruptions.
AWS
Сloudfront
Java
C
Websockets
Dynamodb
Prometheus
Redis
