A seketon playbook for install nodejs repo (https://github.com/quiknode-labs/interview-q-1) to multiple nodes.
Ensure you have Ansible installed on your control machine, and then run the playbook wil:
ansible-playbook -i inventory/hosts.ini deploy.ymlScalability of Application Nodes: By separating the application layer from the database, you can independently scale the number of application servers based on demand without affecting the database server. This makes it easier to handle increases in load by simply adding more application nodes.
Centralized Data Management: Having a single PostgreSQL database simplifies data management, backup, and recovery processes. It ensures data consistency and integrity across all application instances.
Automated Deployment: Using Ansible and Jenkins for deployment automates the setup and configuration processes, reducing the potential for human error and speeding up the deployment and scaling processes.
Monitoring and Maintenance: Centralizing the database makes it easier to monitor its performance and health, apply updates, and perform maintenance without impacting the application layer directly.
Resource Optimization: Distributing the application across multiple servers allows for efficient use of resources, as each server can be optimized for specific tasks (application processing or data management).
Database Bottleneck: As the single point of interaction for data queries and updates, the centralized database could become a bottleneck, especially under high load or during complex data operations.
Single Point of Failure: Despite the advantages of centralized management, having one database server introduces a risk of a single point of failure. If the database goes down, it affects the entire network of application servers.
Network Latency and Bandwidth: Depending on the physical or virtual distances between the application nodes and the database server, network latency can impact performance. This needs careful network planning and possibly the use of dedicated network resources.
Security Risks: Centralizing the database also centralizes the risk. If security is compromised on the database server, all data could potentially be at risk. Implementing robust security measures is critical.
Complex Disaster Recovery: While backups might be simpler, the disaster recovery process can be more complex due to the centralized nature of the database. A failure requires restoration that impacts all application nodes.
Capacity Planning: What are the expected loads, and how will the database handle these? What metrics will be used to determine when scaling is needed?
Failover and Redundancy: How will database failover be handled? Is there a plan for setting up a standby database or a replica to ensure high availability?
Security Measures: What specific security measures and protocols will be put in place to protect the database and the data transmission between the application nodes and the database?
Performance Monitoring: What tools and strategies will be used for monitoring the performance of both the application nodes and the database? How will performance bottlenecks be identified and addressed?
Compliance and Data Governance: Are there any compliance requirements for data storage and processing that must be considered? How will data governance be handled?
Backup and Recovery: What strategies will be implemented for data backups? How frequently should backups occur, and what is the strategy for quick data recovery?
Geographical Considerations: If deploying in a cloud environment, what are the geographical considerations for the placement of VMs in relation to the database to minimize latency?
Cost Management: What will be the cost implications of scaling the number of machines and the central database? How can costs be optimized?