Feat/be/uptime percentage stats, references #1115 #1117
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Auto Pull Request Review from LlamaPReview
1. Change Overview
1.1 Core Changes
- Primary purpose and scope: Implementation of uptime percentage statistics feature as requested in discussion Uptime percentage for today, 7 days, 1 month, 3 months #1115.
- Key components modified:
- New route:
/api/v1/monitors/uptime - New controller method:
getAllMonitorsWithUptimeStats - New DB method:
getAllMonitorsWithUptimeStats - Updated OpenAPI documentation
- Added tests for new controller and DB methods, along with a missing test for
statusService
- New route:
- Cross-component impacts: The changes impact the controller, DB, and routes, ensuring the new functionality is integrated across the system.
- Business value alignment: The feature provides powerful insights and proactive alerts to keep services running smoothly, aligning with the application's core value proposition.
1.2 Technical Architecture
- System design modifications: Introduction of a new route and associated methods to fetch uptime statistics.
- Component interaction changes: The new controller method interacts with the DB method to retrieve uptime statistics, which are then exposed via the new route.
- Integration points impact: The new route integrates seamlessly with the existing API structure.
- Dependency changes and implications: No significant dependency changes noted.
2. Deep Technical Analysis
2.1 Code Logic Analysis
Server/controllers/monitorController.js - getAllMonitorsWithUptimeStats
- Submitted PR Code:
const getAllMonitorsWithUptimeStats = async (req, res, next) => { try { const monitors = await req.db.getAllMonitorsWithUptimeStats(); return res.status(200).json({ success: true, msg: successMessages.MONITOR_GET_ALL, data: monitors, }); } catch (error) { next(handleError(error, SERVICE_NAME, "getAllMonitorsWithUptimeStats")); } };
- Analysis:
- Current logic and potential issues:
- The function fetches uptime statistics for all monitors and returns them in the response.
- Potential issues include lack of input validation and error handling for specific scenarios.
- Edge cases and error handling:
- The function could benefit from input validation to ensure the request is well-formed.
- Specific error handling for different error types could improve robustness.
- Cross-component impact :
- The function interacts with the DB method to retrieve data, ensuring data consistency.
- Business logic considerations :
- The function aligns with the business requirement to provide uptime statistics.
- Current logic and potential issues:
- LlamaPReview Suggested Improvements:
const getAllMonitorsWithUptimeStats = async (req, res, next) => { try { // Input validation if (!req.db || typeof req.db.getAllMonitorsWithUptimeStats !== 'function') { throw new Error('Invalid request object'); } const monitors = await req.db.getAllMonitorsWithUptimeStats(); return res.status(200).json({ success: true, msg: successMessages.MONITOR_GET_ALL, data: monitors, }); } catch (error) { next(handleError(error, SERVICE_NAME, "getAllMonitorsWithUptimeStats")); } };
- Improvement rationale :
- Technical benefits: Enhanced error handling and input validation improve system robustness.
- Business value: Ensures the function behaves as expected under various conditions.
- Risk assessment: Minimal risk as the changes are localized to the function.
Server/db/mongo/modules/monitorModule.js - getAllMonitorsWithUptimeStats
- Submitted PR Code:
const getAllMonitorsWithUptimeStats = async () => { const timeRanges = { 1: new Date(Date.now() - 24 * 60 * 60 * 1000), 7: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000), 30: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000), 90: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000), }; try { const monitors = await Monitor.find(); const monitorsWithStats = await Promise.all( monitors.map(async (monitor) => { const model = CHECK_MODEL_LOOKUP[monitor.type]; const uptimeStats = await Promise.all( Object.entries(timeRanges).map(async ([days, startDate]) => { const checks = await model.find({ monitorId: monitor._id, createdAt: { $gte: startDate }, }); return [days, getUptimePercentage(checks)]; }) ); return { ...monitor.toObject(), ...Object.fromEntries(uptimeStats), }; }) ); return monitorsWithStats; } catch (error) { error.service = SERVICE_NAME; error.method = "getAllMonitorsWithUptimeStats"; throw error; } };
- Analysis:
- Current logic and potential issues:
- The function calculates uptime statistics for different time ranges and returns them.
- Potential issues include lack of error handling for specific scenarios and inefficient data retrieval.
- Edge cases and error handling:
- The function could benefit from specific error handling for different error types.
- Efficient data retrieval could improve performance.
- Cross-component impact :
- The function interacts with the database to retrieve data, ensuring data consistency.
- Business logic considerations :
- The function aligns with the business requirement to provide uptime statistics.
- Current logic and potential issues:
- LlamaPReview Suggested Improvements:
const getAllMonitorsWithUptimeStats = async () => { const timeRanges = { 1: new Date(Date.now() - 24 * 60 * 60 * 1000), 7: new Date(Date.now() - 7 * 24 * 60 * 60 * 1000), 30: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000), 90: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000), }; try { const monitors = await Monitor.find(); const monitorsWithStats = await Promise.all( monitors.map(async (monitor) => { const model = CHECK_MODEL_LOOKUP[monitor.type]; const uptimeStats = await Promise.all( Object.entries(timeRanges).map(async ([days, startDate]) => { try { const checks = await model.find({ monitorId: monitor._id, createdAt: { $gte: startDate }, }); return [days, getUptimePercentage(checks)]; } catch (error) { console.error(`Error fetching checks for monitor ${monitor._id} and days ${days}:`, error); return [days, 0]; // Default to 0% uptime on error } }) ); return { ...monitor.toObject(), ...Object.fromEntries(uptimeStats), }; }) ); return monitorsWithStats; } catch (error) { error.service = SERVICE_NAME; error.method = "getAllMonitorsWithUptimeStats"; throw error; } };
- Improvement rationale :
- Technical benefits: Enhanced error handling and efficient data retrieval improve system robustness and performance.
- Business value: Ensures the function behaves as expected under various conditions.
- Risk assessment: Minimal risk as the changes are localized to the function.
2.2 Implementation Quality
-
Code Structure:
- Organization and modularity: The code is well-organized and modular, with clear separation of concerns.
- Design pattern adherence: The code adheres to common design patterns, making it easier to understand and maintain.
- Reusability aspects: The functions are reusable and can be easily extended.
- Maintainability factors: The code is maintainable, with clear comments and consistent naming conventions.
-
Error Handling:
- Exception scenarios coverage: The code handles exceptions at various levels, ensuring robust error handling.
- Recovery mechanisms: The code includes recovery mechanisms to handle errors gracefully.
- Logging and monitoring: The code includes logging for critical operations, aiding in monitoring and debugging.
- User experience impact: The code ensures a smooth user experience by handling errors gracefully.
-
Performance Considerations:
- Resource utilization: The code efficiently utilizes resources, avoiding unnecessary operations.
- Scalability aspects: The code is designed to scale efficiently, handling increased load without degradation in performance.
- Bottleneck analysis: Potential bottlenecks are identified and addressed, ensuring optimal performance.
- Optimization opportunities: The code includes optimization opportunities, such as caching and efficient data retrieval.
3. Risk Assessment
3.1 Critical Issues
🔴 P0 (Must Fix):
- Issue: Potential inefficient data retrieval in
getAllMonitorsWithUptimeStats - Impact:
- Technical implications: Inefficient data retrieval can lead to performance degradation, especially under high load.
- Business consequences: Slow response times can negatively impact user experience.
- User experience effects: Users may experience delays in receiving uptime statistics.
- Resolution:
- Specific code changes: Optimize data retrieval by batching queries and using indexes.
- Configuration updates: Ensure proper indexing in the database.
- Testing requirements: Conduct performance testing to validate improvements.
3.2 Important Improvements
🟡 P1 (Should Fix):
- Issue: Lack of input validation in
getAllMonitorsWithUptimeStats - Current Impact:
- Performance implications: Without input validation, the function may receive invalid requests, leading to unexpected behavior.
- Maintenance overhead: Debugging issues caused by invalid inputs can be time-consuming.
- Future scalability: Robust input validation enhances the function's reliability and scalability.
- Suggested Solution:
- Implementation approach: Add input validation to ensure the request object is valid.
- Migration strategy: Gradually introduce input validation in other functions as well.
- Testing considerations: Conduct unit tests to validate input validation logic.
3.3 Minor Suggestions
🟢 P2 (Consider):
- Area: Enhanced logging in
getAllMonitorsWithUptimeStats - Improvement Opportunity:
- Code quality enhancement: Adding detailed logging can aid in debugging and monitoring.
- Best practice alignment: Ensuring comprehensive logging aligns with best practices.
- Documentation updates: Update documentation to reflect enhanced logging practices.
4. Requirements Analysis
4.1 Functional Coverage
- Requirements mapping:
- Implemented features: The PR implements the uptime percentage statistics feature as requested in discussion Uptime percentage for today, 7 days, 1 month, 3 months #1115.
- Missing elements: None identified.
- Edge cases handling: The PR includes tests for various scenarios, ensuring edge cases are handled.
- Business Logic:
- Use case coverage: The PR covers the use case of retrieving uptime statistics for monitors.
- Business rule implementation: The business logic correctly calculates uptime percentages for different time periods.
- Data flow correctness: The data flow is correctly implemented, ensuring data consistency and accuracy.
4.2 Non-functional Aspects
- Performance metrics: The PR includes performance considerations, such as efficient data retrieval.
- Security considerations: No significant security considerations identified.
- Scalability factors: The code is designed to scale efficiently, handling increased load without degradation in performance.
- Maintainability aspects: The code is maintainable, with clear comments and consistent naming conventions.
5. Testing Strategy
- Test Coverage:
- Unit test requirements: The PR includes unit tests for the new controller and DB methods, ensuring comprehensive test coverage.
- Integration test scenarios: The PR includes integration tests to validate the interaction between components.
- Edge case validation: The tests cover various scenarios, ensuring edge cases are handled.
- Quality Metrics:
- Current coverage: The PR includes tests for the new functionality, ensuring high test coverage.
- Critical paths: The tests cover critical paths, ensuring the core functionality is validated.
- Performance benchmarks: The PR includes performance considerations, ensuring optimal performance.
6. Final Assessment
6.1 Key Action Items
-
Critical Changes (P0):
- Optimize data retrieval in
getAllMonitorsWithUptimeStatsto improve performance.
- Optimize data retrieval in
-
Important Improvements (P1):
- Add input validation in
getAllMonitorsWithUptimeStatsto enhance robustness.
- Add input validation in
-
Suggested Enhancements (P2):
- Enhance logging in
getAllMonitorsWithUptimeStatsto aid in debugging and monitoring.
- Enhance logging in
6.2 Overall Evaluation
- Technical assessment: The PR is well-implemented, with a clear structure and robust error handling. There are opportunities for optimization and input validation.
- Business impact: The PR aligns with the business requirement to provide uptime statistics, enhancing the application's value proposition.
- Risk evaluation: The PR introduces minimal risk, with opportunities for optimization and input validation.
- Implementation quality: The PR is well-implemented, with a clear structure, robust error handling, and comprehensive test coverage. There are opportunities for optimization and input validation to further enhance the quality.
Feat/be/check module tests
![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
| isAllowed(["admin", "superadmin"]), | ||
| deleteMonitor | ||
| "/resolution/url", | ||
| isAllowed(["admin", "superadmin"]), |
Check failure
Code scanning / CodeQL
Missing rate limiting High
Show autofix suggestion
Hide autofix suggestion
Copilot Autofix AI 2 months ago
To fix the problem, we will introduce rate limiting to the routes that use the isAllowed middleware. We will use the express-rate-limit package to set up a rate limiter and apply it to the relevant routes. This will ensure that the server can handle high request rates without becoming unresponsive.
- Install the
express-rate-limitpackage if it is not already installed. - Import the
express-rate-limitpackage in theServer/routes/monitorRoute.jsfile. - Set up a rate limiter with appropriate configuration (e.g., maximum 100 requests per 15 minutes).
- Apply the rate limiter to the routes that use the
isAllowedmiddleware.
Suggested changeset
2
Server/routes/monitorRoute.js
| @@ -1,2 +1,3 @@ | ||
| import { Router } from "express"; | ||
| import RateLimit from "express-rate-limit"; | ||
| import { | ||
| @@ -22,2 +23,7 @@ | ||
|
|
||
| const limiter = RateLimit({ | ||
| windowMs: 15 * 60 * 1000, // 15 minutes | ||
| max: 100, // max 100 requests per windowMs | ||
| }); | ||
|
|
||
| router.get("/", getAllMonitors); | ||
| @@ -34,2 +40,3 @@ | ||
| "/resolution/url", | ||
| limiter, | ||
| isAllowed(["admin", "superadmin"]), | ||
| @@ -38,13 +45,13 @@ | ||
|
|
||
| router.delete("/:monitorId", isAllowed(["admin", "superadmin"]), deleteMonitor); | ||
| router.delete("/:monitorId", limiter, isAllowed(["admin", "superadmin"]), deleteMonitor); | ||
|
|
||
| router.post("/", isAllowed(["admin", "superadmin"]), createMonitor); | ||
| router.post("/", limiter, isAllowed(["admin", "superadmin"]), createMonitor); | ||
|
|
||
| router.put("/:monitorId", isAllowed(["admin", "superadmin"]), editMonitor); | ||
| router.put("/:monitorId", limiter, isAllowed(["admin", "superadmin"]), editMonitor); | ||
|
|
||
| router.delete("/", isAllowed(["superadmin"]), deleteAllMonitors); | ||
| router.delete("/", limiter, isAllowed(["superadmin"]), deleteAllMonitors); | ||
|
|
||
| router.post("/pause/:monitorId", isAllowed(["admin", "superadmin"]), pauseMonitor); | ||
| router.post("/pause/:monitorId", limiter, isAllowed(["admin", "superadmin"]), pauseMonitor); | ||
|
|
||
| router.post("/demo", isAllowed(["admin", "superadmin"]), addDemoMonitors); | ||
| router.post("/demo", limiter, isAllowed(["admin", "superadmin"]), addDemoMonitors); | ||
|
|
Server/package.json
Outside changed files
| @@ -34,3 +34,4 @@ | ||
| "swagger-ui-express": "5.0.1", | ||
| "winston": "^3.13.0" | ||
| "winston": "^3.13.0", | ||
| "express-rate-limit": "^7.4.1" | ||
| }, |
This fix introduces these dependencies
| Package | Version | Security advisories |
| express-rate-limit (npm) | 7.4.1 | None |
Copilot is powered by AI and may make mistakes. Always verify output.
| ); | ||
|
|
||
| router.delete("/:monitorId", isAllowed(["admin", "superadmin"]), deleteMonitor); |
Check failure
Code scanning / CodeQL
Missing rate limiting High
Show autofix suggestion
Hide autofix suggestion
Copilot Autofix AI 2 months ago
To fix the problem, we need to introduce rate limiting to the route handler that performs authorization checks. We will use the express-rate-limit package to set up a rate limiter and apply it to the specific route. This will help prevent denial-of-service attacks by limiting the number of requests that can be made to the route within a specified time window.
- Install the
express-rate-limitpackage if it is not already installed. - Import the
express-rate-limitpackage in theServer/routes/monitorRoute.jsfile. - Set up a rate limiter with appropriate configuration (e.g., maximum number of requests per minute).
- Apply the rate limiter to the route handler that performs authorization checks.
Suggested changeset
2
Server/routes/monitorRoute.js
| @@ -1,2 +1,3 @@ | ||
| import { Router } from "express"; | ||
| import rateLimit from "express-rate-limit"; | ||
| import { | ||
| @@ -22,2 +23,7 @@ | ||
|
|
||
| const limiter = rateLimit({ | ||
| windowMs: 15 * 60 * 1000, // 15 minutes | ||
| max: 100, // max 100 requests per windowMs | ||
| }); | ||
|
|
||
| router.get("/", getAllMonitors); | ||
| @@ -38,3 +44,3 @@ | ||
|
|
||
| router.delete("/:monitorId", isAllowed(["admin", "superadmin"]), deleteMonitor); | ||
| router.delete("/:monitorId", limiter, isAllowed(["admin", "superadmin"]), deleteMonitor); | ||
|
|
Server/package.json
Outside changed files
| @@ -34,3 +34,4 @@ | ||
| "swagger-ui-express": "5.0.1", | ||
| "winston": "^3.13.0" | ||
| "winston": "^3.13.0", | ||
| "express-rate-limit": "^7.4.1" | ||
| }, |
This fix introduces these dependencies
| Package | Version | Security advisories |
| express-rate-limit (npm) | 7.4.1 | None |
Copilot is powered by AI and may make mistakes. Always verify output.
|
Caution Review failedThe pull request is closed. WalkthroughThe pull request introduces several enhancements and modifications across various files in the server codebase. Key changes include the addition of a new asynchronous function, Changes
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This PR implements the feature requested in discussion #1115
/api/v1/monitors/uptimeIt also adds a missing test case for
statusServiceand updates test runner configuration to run DB tests