DevOps tools<\/a> and strategies to ensure that the client received a system that was not only efficient but also secure and scalable.<\/p>\nServerless is Great but Not Always Suitable<\/h2>\n
The client initially set their sights on a serverless architecture, an approach where code is executed in response to events without the need for traditional server management. Serverless is attractive because you only pay for what you use, a perfect fit for businesses with fluctuating workloads. However, as they dug deeper, a different story emerged.<\/p>\n
One of the main advantages of serverless computing is its inherent scalability. The burden of provisioning and managing servers falls on the cloud provider, allowing businesses to focus on development. However, for this client, the anticipated workload involved millions of function executions per month. While serverless scales automatically, the cost implications for such a high volume became a major concern. Each function invocation incurs a small cost, and with millions triggered monthly, the serverless bill could quickly balloon.<\/p>\n
Beyond the cost factor, operational complexity also started to outweigh the initial appeal. Managing a vast network of individual functions spread across the serverless landscape can be challenging. Debugging issues, monitoring performance, and maintaining consistent code deployments across these functions can become a time-consuming and resource-intensive task.<\/p>\n
Microservices are Efficient and on a Budget<\/h3>\n
A shift towards microservices \u2013 smaller, independent services working together \u2013 proved to be a game-changer in terms of costs:<\/p>\n
\n- Docker<\/strong> containers offer a more cost-effective way to deploy these microservices. Docker is a containerization technology that packages applications with all their dependencies into standardized units. These containers can be easily deployed across different environments, making them ideal for microservices architectures. Compared to the ever-growing serverless bill, deploying microservices within Docker containers provided a more predictable and manageable cost structure.<\/li>\n
- Microservices are inherently modular<\/strong>, with each service responsible for a specific functionality. This modularity promotes loose coupling, meaning changes in one microservice have minimal impact on others. This not only simplifies development and maintenance but also fosters independent scaling. If a particular service experiences a surge in demand, it can be scaled independently without affecting the entire system.<\/li>\n<\/ul>\n
The move to microservices wasn’t just about saving money. It opened the door to a robust security and monitoring strategy. Here are some of the key tools that were utilized to build such a strong and advanced system:<\/p>\n
\n- DefectDojo<\/strong>: This security scanner constantly checks both the front-end (user interface) and back-end (server-side logic) for vulnerabilities. DefectDojo prioritizes issues based on severity and provides recommendations for resolution. This continuous scanning process strengthens the system’s overall security posture.<\/li>\n
- Jaeger<\/strong>: Debugging got a major boost with Jaeger. This tool traces interactions between microservices, visualizing the flow of data across the system. Imagine a complex network of roads \u2013 Jaeger acts like a traffic monitoring system, highlighting bottlenecks and inefficiencies. With this visual representation, developers can pinpoint performance issues and optimize their microservices for smoother operation.<\/li>\n
- Sentry<\/strong>: Keeping an eye on user activity post-login became a breeze with Sentry. It provided real-time insights into user behavior, including device details, operating systems used, and performance metrics. This granular data empowers developers to identify user-facing issues and resolve them quickly, enhancing the overall user experience.<\/li>\n
- Errors, logs, and system availability were all detected with Grafana<\/strong>. This data visualization tool goes beyond just displaying raw data. Grafana allows users to create custom dashboards that present key system metrics in a clear and actionable format. It even integrated with IoT (Internet of Things) devices, giving them a holistic view of the system’s state, including factors like server room temperature or network latency.<\/li>\n
- Elasticsearch<\/strong> and AWS Logging<\/strong> were used to capture every system whisper. Elasticsearch is a powerful search and analytics engine, while AWS Logging provides centralized log management within the Amazon Web Services cloud platform. This combination ensures no data point goes unnoticed. Developers can use Elasticsearch to analyze logs and identify patterns that might indicate potential problems or security threats.<\/li>\n
- Standardized deployment<\/strong> processes ensured order. Each new feature had clear tasks and descriptions documented within a version control system like Git. Additionally, detailed release notes kept everyone informed about changes, potential security vulnerabilities addressed, and the impact on existing micros.<\/li>\n<\/ul>\n
Conclusion<\/h3>\n
This client’s journey proves that the ideal system architecture isn’t always a straight line. By carefully evaluating their needs and embracing a well-thought and analyzed approach, they achieved not just efficiency, but also bulletproof security and impressive scalability.<\/p>\n
The client\u2019s story serves as a valuable roadmap for any business seeking to build a system that thrives in today’s ever-evolving technological landscape.<\/p>\n
And, if you are looking for a reliable partner to help you construct a similar system that will cater to 100% of your business needs, Agiliway experts<\/a> are willing to show you how it\u2019s done.<\/p>\nREAD ALSO: Adoption of DevOps Practices Utilizing Ansible, Ansible Tower and Ansible Molecule<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Imagine building a system so efficient it practically runs itself. That’s the goal for many businesses, and this client was …<\/a><\/p>\n","protected":false},"author":11,"featured_media":13612,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[107,1,4,20],"tags":[187,64,135,31],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/posts\/13607"}],"collection":[{"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/comments?post=13607"}],"version-history":[{"count":5,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/posts\/13607\/revisions"}],"predecessor-version":[{"id":13613,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/posts\/13607\/revisions\/13613"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/media\/13612"}],"wp:attachment":[{"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/media?parent=13607"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/categories?post=13607"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/agiliway.com\/wp-json\/wp\/v2\/tags?post=13607"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}