diff --git a/.clinic/54343.clinic-doctor.html b/.clinic/54343.clinic-doctor.html
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+++ b/.clinic/54343.clinic-doctor.html
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+
+
+
+
+ Clinic Doctor
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+The process may have a memory management issue
+This can mean that your application might be spending more time than expected in memory allocations
+Diagnose: Use clinic heapprofiler to discover the functions which allocates more memory at heap – run clinic heapprofiler -h
+
+
+
+Understanding the analysis
+JavaScript is Garbage Collected language. Rather than manually freeing objects, they
+are simply "cleaned away" at some point after all references to an object have been removed.
+At a basic level, the Garbage Collector traverses the JavaScript objects at various intervals to find any
+"orphaned" objects (objects which no longer have any references). If there are too many
+objects, and/or too many orphaned objects this can cause performance issues – because the Garbage
+Collector uses the same thread as the JavaScript event loop. In other words, JavaScript execution
+pauses while the Garbage Collector clears away de-referenced objects.
+At a more detailed level, GC collection is triggered by memory activity, rather than time and
+objects are classified by the GC into young and old. "Young" objects are
+traversed (scavenged) more frequently, while "old" objects will stay in memory for longer. So there
+are actually two GC types, a frequent scavenge of new space (short lived objects) and a less regular traversal of
+old space (objects that survived enough new space scavenges).
+Several heuristics may trigger detection of a GC issue, but they all center around high
+memory usage.
+One possible cause of a detected GC issue is a memory leak, where objects are being accidentally
+allocated. However there are other (more common) cases where the is no leak but the memory strategy
+needs to be adapted.
+One such common case is when large objects (such as may be generated for big JSON payloads), are
+created during periods of high activity (e.g. under request load). This can cause the objects
+to be moved into old space – if they survive two (by default) GC scavenges – where they will live
+for longer due to the less frequent scavenges. Objects can then build up in "old space" and
+cause intermittent process stalling during Garbage Collection.
+Depending on the use case this may be solved in different ways. For instance if the goal is to write
+out serialized objects, then the output could be written to the response as strings (or buffers) directly
+instead of creating the intermediate objects (or a combined strategy where part of the object is written out
+from available state). It may just be a case that a functional approach (which is usually recommended) is
+leading to the repeated creation of very similar objects, in which case the logical flow between functions
+in a hot path could be adapted to reuse objects instead of create new objects.
+Another possibility is that a very high amount of short lived objects are created, filling up the
+"young" space and triggering frequent GC sweeps – if this case isn't an unintended memory leak,
+then then an object pooling strategy may be necessary.
+To solve Garbage Collection issues we have to analyse the state of our process in order to track down the
+root cause behind the high memory consumption.
+Next Steps
+
+If the system is already deployed, mitigate the issue immediately by implementing
+HTTP 503 Service Unavailable functionality (see Load Shedding in Reference )
+Use clinic heapprofiler to create a flamegraph of memory allocations in the application.
+See clinic heapprofiler --help for how to generate the memory profile.
+Visit the Heapprofiler walkthrough for a guide on how to use and interpret this output
+Look for "hot" blocks, those are functions that are observed to be at the top the stack per memory allocation sample – in other words, such functions are allocation more memory in the heap
+(In the case of a distributed bottleneck, start by looking for lots of wide tips at the top of the Flamegraph)
+
+Reference
+
+
+
+
+There may be one or more long running synchronous operations blocking the thread
+Mitigate: Implement HTTP 503 event-loop protection
+Diagnose: Use clinic flame to discover CPU intensive function calls – run clinic flame -h
+Use --trace-sync-io to track synchronous I/O operations
+
+
+
+Understanding the analysis
+JavaScript is a single-threaded event-driven non-blocking language.
+In Node.js I/O tasks are delegated to the Operating System, JavaScript functions (callbacks)
+are invoked once a related I/O operation is complete. At a rudimentary level, the process of
+queueing events and later handling results in-thread is conceptually achieved with the
+"Event Loop" abstraction.
+At a (very) basic level the following pseudo-code demonstrates the Event Loop:
+while (event) handle(event)
+The Event Loop paradigm leads to an ergonomic development experience for high concurrency programming
+(relative to the multi-threaded paradigm).
+However, since the Event Loop operates on a single thread this is essentially a shared
+execution environment for every potentially concurrent action. This means that if the
+execution time of any line of code exceeds an acceptable threshold it interferes with
+processing of future events (for instance, an incoming HTTP request); new events cannot
+be processed because the same thread that would be processing the event is currently
+blocked by a long-running synchronous operation.
+Asynchronous operations are those which queue an event for later handling, they tend to be
+identified by an API that requires a callback, or uses promises (or async/await).
+Whereas synchronous operations simply return a value. Long running synchronous operations are either
+functions that perform blocking I/O (such as fs.readFileSync) or potentially resource intensive
+algorithms (such as JSON.stringify or react.renderToString). The --trace-sync-io can help
+by printing a stack trace whenever synchronous I/O is detected after the first run of the event
+loop.
+To solve the Event Loop issue, we need to find out where the synchronous bottleneck is.
+This may (commonly) be identified as a single long-running synchronous function, or
+the bottleneck may be distributed which would take rather more detective work.
+Next Steps
+
+If the system is already deployed, mitigate the issue immediately by implementing
+HTTP 503 Service Unavailable functionality (see Load Shedding in Reference )
+This should allow the deployments Load Balance to route traffic to a different service instance
+In the worse case the user receives the 503 in which case they must retry (this is still preferable to waiting for a timeout)
+Use clinic flame to generate a flamegraph
+Run clinic flame --help to get started
+see "Understanding Flamegraphs and how to use 0x " article in the Reference section for more information
+Look for "hot" blocks, these are functions that are observed (at a higher relative frequency) to be at the top the stack per CPU sample – in other words, such functions are blocking the event loop
+(In the case of a distributed bottleneck, start by looking for lots of wide tips at the top of the Flamegraph)
+
+Reference
+
+
+
+
+There may be long-running asynchronous activities
+This can mean that the bottleneck is not the Node process at all, but rather an I/O operation
+Diagnose: Use clinic bubbleprof to explore asynchronous delays – run clinic bubbleprof -h to get started.
+
+
+
+Understanding the analysis
+Node.js provides a platform for non-blocking I/O.
+Unlike languages that typically block for IO (e.g. Java, PHP), Node.js passes I/O operations
+to an accompanying C++ library (libuv) which delegates these operations to the Operating System.
+Once an operation is complete, the notification bubbles up from the OS, through libuv, which can then
+trigger any registered JavaScript functions (callbacks) for that operation. This is the typical
+flow for any asynchronous I/O (where as Sync API 's will block, but should never be used in a
+server/service request handling context).
+The profiled process has been observed is unusually idle under load, typically this means
+it's waiting for external I/O because there's nothing else to do until the I/O completes.
+To solve I/O issues we have to track down the asynchronous call(s) which are taking an
+abnormally long time to complete.
+I/O root cause analysis is mostly a reasoning exercise. Clinic.js Bubbleprof is a tool developed specifically to inform and ease this kind of reasoning.
+Next Steps
+
+Use clinic bubbleprof to create a diagram of the application's asynchronous flow.
+See clinic bubbleprof --help for how to generate the profile
+Visit the Bubbleprof walkthrough for a guide on how to use and interpret this output
+Explore the Bubbleprof diagram. Look for long lines and large circles representing persistent delays, then drill down to reveal the lines of code responsible
+Pay particular attention to "userland" delays, originating from code in the profiled application itself.
+Identify possible optimization targets using knowledge of the application's I/O touch points (the I/O to and from the Node.js process, such as databases, network requests, and filesystem access). For example:
+Look for operations in series which could be executed in parallel
+Look for slow operations that can be optimised externally (for example with caching or indexing)
+Consider if a large processes has good reasons for being almost constantly in the queue (for example, some server handlers)
+
+Reference
+
+
+
+
+
+
+
+There is a performance issue but Clinic.js could not accurately categorize it.
+Clinic.js may inadvertently be picking up system noise.
+Disable any CPU- or Memory-intensive applications.
+Use the --on-port flag to immediately begin load testing, this is known to reduce the chances of interference.
+If an unknown result is consistently produced it is still very likely that there is a performance issue.
+Undertake additional diagnosis with the clinic bubbleprof and/or clinic flame commands.
+For memory analysis use the --inspectMemory tab.
+
+
+
+Understanding the analysis
+An unknown issue occurs when Clinic.js' analysis algorithms are unable to categorize the sampling results but nevertheless an issue of some kind has been detected.
+This outcome can be attributed to one of two scenarios:
+
+Ambient noise – for instance, other applications using the CPU or memory – during the sampling period has polluted the results.
+There is a genuine performance issue but clinic doctor doesn't recognize it.
+
+In the case of ambient noise, there may still be a specific, categorizable performance issue.
+We can make eliminate the possibility of ambient noise and make it easier for Clinic.js to definitively recognize the issue by:
+
+Closing down as many applications as possible, especially applications that are CPU- or Memory- intensive.
+Using the --on-port flag. This can reduce the chances of unknown issues because there is no time gap nor additional system activity between the server starting and the load test beginning.
+
+By way of example, instead of running clinic -- node app.js in one terminal and autocannon localhost:3000 in another, it is preferable and recommended to trigger both in one command using the following command:
+clinic doctor --on-port="autocannon localhost:3000" -- node app.js
+An even simpler form of this is to use the --autocannon flag,
+clinic doctor --autocannon / -- node app.js
+If after taking these steps an unknown categorization continues to occur then we can instead attempt to infer the nature of the performance issue using specialist diagnostic tooling, such
+as clinic flame, clinic bubble or Node Inspector.
+Next Steps
+
+First eliminate the possibility of ambient noise
+Reduce noise by closing down as many other applications running on the system as possible - especially CPU or Memory intensive applications
+Ensure that the --on-port flag is being used to trigger load testing instead of initiating load testing independently
+Use clinic bubbleprof to create a diagram of the application's asynchronous flow (see clinic bubbleprof --help)
+Explore the Bubbleprof diagram. Look for long lines and large circles representing persistent delays, then drill down to reveal the lines of code responsible
+A common problem is the overuse or misuse of promises. clinic bubbleprof will visualize promise activity, make a point of looking out for it in the diagram.
+Use clinic flame to generate a flamegraph
+Run clinic flame --help to get started
+Look for "hot" blocks, these are functions that are observed (at a higher relative frequency) to be at the top the stack per CPU sample – in other words, such functions are blocking the event loop
+For memory analysis use the --inspectMemory tab.
+Run node --inspect <FILENAME>
+Open Chrome and navigate to chrome://inspect
+Under the Remote Target heading, there should be a target with the official Node.js icon
+Click the inspect link for that target – this will connect Chrome Devtools to the Node processes remote debug interface
+In Devtools, select the Memory tab
+Select the Take heap snapshot radio box, and then click Take snapshot
+Put the process under load (in the same way that the process was load tested for Clinic.js)
+Click Profiles in the left panel, then click Take snapshot again
+Under the HEAP SNAPSHOTS left panel, select the second Snapshot (it will be called Snapshot 2 )
+Locate the dropdown box just above the "Constructor" column (most likely the dropdown box says Summary )
+Click the dropdown, and select Comparison – this compares the before and after snapshots of the heap
+Click the # Delta and/or Size Delta columns to sort by the difference in object counts
+or object size, categorized by constructor type
+Use the interactive trees in the Constructor column to drill down into the specifics
+Use the Retainers panel to understand the chain of object references
+
+Reference
+
+
+
+
+Everything looks good!
+
+
+
+
+
+
+
+
+
+
+
diff --git a/.clinic/54343.clinic-doctor/54343.clinic-doctor-processstat b/.clinic/54343.clinic-doctor/54343.clinic-doctor-processstat
new file mode 100644
index 0000000..6964e73
Binary files /dev/null and b/.clinic/54343.clinic-doctor/54343.clinic-doctor-processstat differ
diff --git a/.clinic/54343.clinic-doctor/54343.clinic-doctor-systeminfo b/.clinic/54343.clinic-doctor/54343.clinic-doctor-systeminfo
new file mode 100644
index 0000000..62f5ccf
--- /dev/null
+++ b/.clinic/54343.clinic-doctor/54343.clinic-doctor-systeminfo
@@ -0,0 +1,36 @@
+{
+ "clock": {
+ "hrtime": [
+ 2051,
+ 419296161
+ ],
+ "unixtime": 1732694394584
+ },
+ "nodeVersions": {
+ "node": "20.18.1",
+ "acorn": "8.12.1",
+ "ada": "2.9.0",
+ "ares": "1.33.1",
+ "base64": "0.5.2",
+ "brotli": "1.1.0",
+ "cjs_module_lexer": "1.4.1",
+ "cldr": "45.0",
+ "icu": "75.1",
+ "llhttp": "8.1.2",
+ "modules": "115",
+ "napi": "9",
+ "nghttp2": "1.61.0",
+ "nghttp3": "0.7.0",
+ "ngtcp2": "1.1.0",
+ "openssl": "3.0.15+quic",
+ "simdutf": "5.5.0",
+ "tz": "2024b",
+ "undici": "6.20.0",
+ "unicode": "15.1",
+ "uv": "1.46.0",
+ "uvwasi": "0.0.21",
+ "v8": "11.3.244.8-node.23",
+ "zlib": "1.3.0.1-motley-71660e1"
+ },
+ "toolVersion": "11.0.0"
+}
\ No newline at end of file
diff --git a/.clinic/54343.clinic-doctor/54343.clinic-doctor-traceevent b/.clinic/54343.clinic-doctor/54343.clinic-doctor-traceevent
new file mode 100644
index 0000000..523d545
--- /dev/null
+++ b/.clinic/54343.clinic-doctor/54343.clinic-doctor-traceevent
@@ -0,0 +1 @@
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failure"}},{"pid":54343,"tid":54343,"ts":2066879026,"tts":881795,"ph":"X","cat":"v8","name":"V8.GCScavenger","dur":891,"tdur":891,"args":{}},{"pid":54343,"tid":54343,"ts":2066879961,"tts":882731,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":17079432}},{"pid":54343,"tid":54343,"ts":2068591369,"tts":957927,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":44,"tdur":42,"args":{}},{"pid":54343,"tid":54343,"ts":2068591396,"tts":957953,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":14,"tdur":14,"args":{}},{"pid":54343,"tid":54343,"ts":2070125034,"tts":1029988,"ph":"B","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeBefore":18076288,"type":"allocation failure"}},{"pid":54343,"tid":54343,"ts":2070125046,"tts":1029998,"ph":"X","cat":"v8","name":"V8.GCScavenger","dur":580,"tdur":567,"args":{}},{"pid":54343,"tid":54343,"ts":2070125671,"tts":1030610,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":17081272}},{"pid":54343,"tid":54343,"ts":2073705934,"tts":1162841,"ph":"B","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeBefore":18078728,"type":"allocation failure"}},{"pid":54343,"tid":54343,"ts":2073705947,"tts":1162852,"ph":"X","cat":"v8","name":"V8.GCScavenger","dur":583,"tdur":584,"args":{}},{"pid":54343,"tid":54343,"ts":2073706576,"tts":1163481,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":17086624}},{"pid":54343,"tid":54343,"ts":2077455894,"tts":1299558,"ph":"B","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeBefore":18082624,"type":"allocation failure"}},{"pid":54343,"tid":54343,"ts":2077455905,"tts":1299567,"ph":"X","cat":"v8","name":"V8.GCScavenger","dur":652,"tdur":640,"args":{}},{"pid":54343,"tid":54343,"ts":2077456602,"tts":1300251,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":17088712}},{"pid":54343,"tid":54343,"ts":2080501348,"tts":1391768,"ph":"B","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeBefore":17897048,"type":"task"}},{"pid":54343,"tid":54343,"ts":2080501351,"tts":1391770,"ph":"X","cat":"v8","name":"V8.GCScavenger","dur":140,"tdur":141,"args":{}},{"pid":54343,"tid":54343,"ts":2080501504,"tts":1391923,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":17061464}},{"pid":54343,"tid":54343,"ts":2051382896,"tts":3820,"ph":"M","cat":"__metadata","name":"process_name","dur":0,"tdur":0,"args":{"name":"node"}},{"pid":54343,"tid":54343,"ts":2051382898,"tts":3821,"ph":"M","cat":"__metadata","name":"version","dur":0,"tdur":0,"args":{"node":"20.18.1"}},{"pid":54343,"tid":54343,"ts":2051382898,"tts":3822,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"JavaScriptMainThread"}},{"pid":54343,"tid":54343,"ts":2051382918,"tts":3842,"ph":"M","cat":"__metadata","name":"node","dur":0,"tdur":0,"args":{"process":{"versions":{"node":"20.18.1","v8":"11.3.244.8-node.23","uv":"1.46.0","zlib":"1.3.0.1-motley-71660e1","brotli":"1.1.0","ares":"1.33.1","modules":"115","nghttp2":"1.61.0","napi":"9","llhttp":"8.1.2","uvwasi":"0.0.21","acorn":"8.12.1","simdutf":"5.5.0","ada":"2.9.0","undici":"6.20.0","cjs_module_lexer":"1.4.1","base64":"0.5.2","openssl":"3.0.15+quic","cldr":"45.0","icu":"75.1","tz":"2024b","unicode":"15.1","ngtcp2":"1.1.0","nghttp3":"0.7.0"},"arch":"x64","platform":"linux","release":{"name":"node","lts":"Iron"}}}},{"pid":54343,"tid":54346,"ts":2051383011,"tts":56,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"WorkerThreadsTaskRunner::DelayedTaskScheduler"}},{"pid":54343,"tid":54347,"ts":2051383139,"tts":38,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54348,"ts":2051383152,"tts":39,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54349,"ts":2051383163,"tts":21,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54350,"ts":2051383216,"tts":49,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54343,"ts":2051382896,"tts":3820,"ph":"M","cat":"__metadata","name":"process_name","dur":0,"tdur":0,"args":{"name":"node"}},{"pid":54343,"tid":54343,"ts":2051382898,"tts":3821,"ph":"M","cat":"__metadata","name":"version","dur":0,"tdur":0,"args":{"node":"20.18.1"}},{"pid":54343,"tid":54343,"ts":2051382898,"tts":3822,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"JavaScriptMainThread"}},{"pid":54343,"tid":54343,"ts":2051382918,"tts":3842,"ph":"M","cat":"__metadata","name":"node","dur":0,"tdur":0,"args":{"process":{"versions":{"node":"20.18.1","v8":"11.3.244.8-node.23","uv":"1.46.0","zlib":"1.3.0.1-motley-71660e1","brotli":"1.1.0","ares":"1.33.1","modules":"115","nghttp2":"1.61.0","napi":"9","llhttp":"8.1.2","uvwasi":"0.0.21","acorn":"8.12.1","simdutf":"5.5.0","ada":"2.9.0","undici":"6.20.0","cjs_module_lexer":"1.4.1","base64":"0.5.2","openssl":"3.0.15+quic","cldr":"45.0","icu":"75.1","tz":"2024b","unicode":"15.1","ngtcp2":"1.1.0","nghttp3":"0.7.0"},"arch":"x64","platform":"linux","release":{"name":"node","lts":"Iron"}}}},{"pid":54343,"tid":54346,"ts":2051383011,"tts":56,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"WorkerThreadsTaskRunner::DelayedTaskScheduler"}},{"pid":54343,"tid":54347,"ts":2051383139,"tts":38,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54348,"ts":2051383152,"tts":39,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54349,"ts":2051383163,"tts":21,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":54343,"tid":54350,"ts":2051383216,"tts":49,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}}]}
\ No newline at end of file
diff --git a/.clinic/55805.clinic-doctor.html b/.clinic/55805.clinic-doctor.html
new file mode 100644
index 0000000..0d2c9d1
--- /dev/null
+++ b/.clinic/55805.clinic-doctor.html
@@ -0,0 +1,2881 @@
+
+
+
+
+ Clinic Doctor
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+The process may have a memory management issue
+This can mean that your application might be spending more time than expected in memory allocations
+Diagnose: Use clinic heapprofiler to discover the functions which allocates more memory at heap – run clinic heapprofiler -h
+
+
+
+Understanding the analysis
+JavaScript is Garbage Collected language. Rather than manually freeing objects, they
+are simply "cleaned away" at some point after all references to an object have been removed.
+At a basic level, the Garbage Collector traverses the JavaScript objects at various intervals to find any
+"orphaned" objects (objects which no longer have any references). If there are too many
+objects, and/or too many orphaned objects this can cause performance issues – because the Garbage
+Collector uses the same thread as the JavaScript event loop. In other words, JavaScript execution
+pauses while the Garbage Collector clears away de-referenced objects.
+At a more detailed level, GC collection is triggered by memory activity, rather than time and
+objects are classified by the GC into young and old. "Young" objects are
+traversed (scavenged) more frequently, while "old" objects will stay in memory for longer. So there
+are actually two GC types, a frequent scavenge of new space (short lived objects) and a less regular traversal of
+old space (objects that survived enough new space scavenges).
+Several heuristics may trigger detection of a GC issue, but they all center around high
+memory usage.
+One possible cause of a detected GC issue is a memory leak, where objects are being accidentally
+allocated. However there are other (more common) cases where the is no leak but the memory strategy
+needs to be adapted.
+One such common case is when large objects (such as may be generated for big JSON payloads), are
+created during periods of high activity (e.g. under request load). This can cause the objects
+to be moved into old space – if they survive two (by default) GC scavenges – where they will live
+for longer due to the less frequent scavenges. Objects can then build up in "old space" and
+cause intermittent process stalling during Garbage Collection.
+Depending on the use case this may be solved in different ways. For instance if the goal is to write
+out serialized objects, then the output could be written to the response as strings (or buffers) directly
+instead of creating the intermediate objects (or a combined strategy where part of the object is written out
+from available state). It may just be a case that a functional approach (which is usually recommended) is
+leading to the repeated creation of very similar objects, in which case the logical flow between functions
+in a hot path could be adapted to reuse objects instead of create new objects.
+Another possibility is that a very high amount of short lived objects are created, filling up the
+"young" space and triggering frequent GC sweeps – if this case isn't an unintended memory leak,
+then then an object pooling strategy may be necessary.
+To solve Garbage Collection issues we have to analyse the state of our process in order to track down the
+root cause behind the high memory consumption.
+Next Steps
+
+If the system is already deployed, mitigate the issue immediately by implementing
+HTTP 503 Service Unavailable functionality (see Load Shedding in Reference )
+Use clinic heapprofiler to create a flamegraph of memory allocations in the application.
+See clinic heapprofiler --help for how to generate the memory profile.
+Visit the Heapprofiler walkthrough for a guide on how to use and interpret this output
+Look for "hot" blocks, those are functions that are observed to be at the top the stack per memory allocation sample – in other words, such functions are allocation more memory in the heap
+(In the case of a distributed bottleneck, start by looking for lots of wide tips at the top of the Flamegraph)
+
+Reference
+
+
+
+
+There may be one or more long running synchronous operations blocking the thread
+Mitigate: Implement HTTP 503 event-loop protection
+Diagnose: Use clinic flame to discover CPU intensive function calls – run clinic flame -h
+Use --trace-sync-io to track synchronous I/O operations
+
+
+
+Understanding the analysis
+JavaScript is a single-threaded event-driven non-blocking language.
+In Node.js I/O tasks are delegated to the Operating System, JavaScript functions (callbacks)
+are invoked once a related I/O operation is complete. At a rudimentary level, the process of
+queueing events and later handling results in-thread is conceptually achieved with the
+"Event Loop" abstraction.
+At a (very) basic level the following pseudo-code demonstrates the Event Loop:
+while (event) handle(event)
+The Event Loop paradigm leads to an ergonomic development experience for high concurrency programming
+(relative to the multi-threaded paradigm).
+However, since the Event Loop operates on a single thread this is essentially a shared
+execution environment for every potentially concurrent action. This means that if the
+execution time of any line of code exceeds an acceptable threshold it interferes with
+processing of future events (for instance, an incoming HTTP request); new events cannot
+be processed because the same thread that would be processing the event is currently
+blocked by a long-running synchronous operation.
+Asynchronous operations are those which queue an event for later handling, they tend to be
+identified by an API that requires a callback, or uses promises (or async/await).
+Whereas synchronous operations simply return a value. Long running synchronous operations are either
+functions that perform blocking I/O (such as fs.readFileSync) or potentially resource intensive
+algorithms (such as JSON.stringify or react.renderToString). The --trace-sync-io can help
+by printing a stack trace whenever synchronous I/O is detected after the first run of the event
+loop.
+To solve the Event Loop issue, we need to find out where the synchronous bottleneck is.
+This may (commonly) be identified as a single long-running synchronous function, or
+the bottleneck may be distributed which would take rather more detective work.
+Next Steps
+
+If the system is already deployed, mitigate the issue immediately by implementing
+HTTP 503 Service Unavailable functionality (see Load Shedding in Reference )
+This should allow the deployments Load Balance to route traffic to a different service instance
+In the worse case the user receives the 503 in which case they must retry (this is still preferable to waiting for a timeout)
+Use clinic flame to generate a flamegraph
+Run clinic flame --help to get started
+see "Understanding Flamegraphs and how to use 0x " article in the Reference section for more information
+Look for "hot" blocks, these are functions that are observed (at a higher relative frequency) to be at the top the stack per CPU sample – in other words, such functions are blocking the event loop
+(In the case of a distributed bottleneck, start by looking for lots of wide tips at the top of the Flamegraph)
+
+Reference
+
+
+
+
+There may be long-running asynchronous activities
+This can mean that the bottleneck is not the Node process at all, but rather an I/O operation
+Diagnose: Use clinic bubbleprof to explore asynchronous delays – run clinic bubbleprof -h to get started.
+
+
+
+Understanding the analysis
+Node.js provides a platform for non-blocking I/O.
+Unlike languages that typically block for IO (e.g. Java, PHP), Node.js passes I/O operations
+to an accompanying C++ library (libuv) which delegates these operations to the Operating System.
+Once an operation is complete, the notification bubbles up from the OS, through libuv, which can then
+trigger any registered JavaScript functions (callbacks) for that operation. This is the typical
+flow for any asynchronous I/O (where as Sync API 's will block, but should never be used in a
+server/service request handling context).
+The profiled process has been observed is unusually idle under load, typically this means
+it's waiting for external I/O because there's nothing else to do until the I/O completes.
+To solve I/O issues we have to track down the asynchronous call(s) which are taking an
+abnormally long time to complete.
+I/O root cause analysis is mostly a reasoning exercise. Clinic.js Bubbleprof is a tool developed specifically to inform and ease this kind of reasoning.
+Next Steps
+
+Use clinic bubbleprof to create a diagram of the application's asynchronous flow.
+See clinic bubbleprof --help for how to generate the profile
+Visit the Bubbleprof walkthrough for a guide on how to use and interpret this output
+Explore the Bubbleprof diagram. Look for long lines and large circles representing persistent delays, then drill down to reveal the lines of code responsible
+Pay particular attention to "userland" delays, originating from code in the profiled application itself.
+Identify possible optimization targets using knowledge of the application's I/O touch points (the I/O to and from the Node.js process, such as databases, network requests, and filesystem access). For example:
+Look for operations in series which could be executed in parallel
+Look for slow operations that can be optimised externally (for example with caching or indexing)
+Consider if a large processes has good reasons for being almost constantly in the queue (for example, some server handlers)
+
+Reference
+
+
+
+
+
+
+
+There is a performance issue but Clinic.js could not accurately categorize it.
+Clinic.js may inadvertently be picking up system noise.
+Disable any CPU- or Memory-intensive applications.
+Use the --on-port flag to immediately begin load testing, this is known to reduce the chances of interference.
+If an unknown result is consistently produced it is still very likely that there is a performance issue.
+Undertake additional diagnosis with the clinic bubbleprof and/or clinic flame commands.
+For memory analysis use the --inspectMemory tab.
+
+
+
+Understanding the analysis
+An unknown issue occurs when Clinic.js' analysis algorithms are unable to categorize the sampling results but nevertheless an issue of some kind has been detected.
+This outcome can be attributed to one of two scenarios:
+
+Ambient noise – for instance, other applications using the CPU or memory – during the sampling period has polluted the results.
+There is a genuine performance issue but clinic doctor doesn't recognize it.
+
+In the case of ambient noise, there may still be a specific, categorizable performance issue.
+We can make eliminate the possibility of ambient noise and make it easier for Clinic.js to definitively recognize the issue by:
+
+Closing down as many applications as possible, especially applications that are CPU- or Memory- intensive.
+Using the --on-port flag. This can reduce the chances of unknown issues because there is no time gap nor additional system activity between the server starting and the load test beginning.
+
+By way of example, instead of running clinic -- node app.js in one terminal and autocannon localhost:3000 in another, it is preferable and recommended to trigger both in one command using the following command:
+clinic doctor --on-port="autocannon localhost:3000" -- node app.js
+An even simpler form of this is to use the --autocannon flag,
+clinic doctor --autocannon / -- node app.js
+If after taking these steps an unknown categorization continues to occur then we can instead attempt to infer the nature of the performance issue using specialist diagnostic tooling, such
+as clinic flame, clinic bubble or Node Inspector.
+Next Steps
+
+First eliminate the possibility of ambient noise
+Reduce noise by closing down as many other applications running on the system as possible - especially CPU or Memory intensive applications
+Ensure that the --on-port flag is being used to trigger load testing instead of initiating load testing independently
+Use clinic bubbleprof to create a diagram of the application's asynchronous flow (see clinic bubbleprof --help)
+Explore the Bubbleprof diagram. Look for long lines and large circles representing persistent delays, then drill down to reveal the lines of code responsible
+A common problem is the overuse or misuse of promises. clinic bubbleprof will visualize promise activity, make a point of looking out for it in the diagram.
+Use clinic flame to generate a flamegraph
+Run clinic flame --help to get started
+Look for "hot" blocks, these are functions that are observed (at a higher relative frequency) to be at the top the stack per CPU sample – in other words, such functions are blocking the event loop
+For memory analysis use the --inspectMemory tab.
+Run node --inspect <FILENAME>
+Open Chrome and navigate to chrome://inspect
+Under the Remote Target heading, there should be a target with the official Node.js icon
+Click the inspect link for that target – this will connect Chrome Devtools to the Node processes remote debug interface
+In Devtools, select the Memory tab
+Select the Take heap snapshot radio box, and then click Take snapshot
+Put the process under load (in the same way that the process was load tested for Clinic.js)
+Click Profiles in the left panel, then click Take snapshot again
+Under the HEAP SNAPSHOTS left panel, select the second Snapshot (it will be called Snapshot 2 )
+Locate the dropdown box just above the "Constructor" column (most likely the dropdown box says Summary )
+Click the dropdown, and select Comparison – this compares the before and after snapshots of the heap
+Click the # Delta and/or Size Delta columns to sort by the difference in object counts
+or object size, categorized by constructor type
+Use the interactive trees in the Constructor column to drill down into the specifics
+Use the Retainers panel to understand the chain of object references
+
+Reference
+
+
+
+
+Everything looks good!
+
+
+
+
+
+
+
+
+
+
+
diff --git a/.clinic/55805.clinic-doctor/55805.clinic-doctor-processstat b/.clinic/55805.clinic-doctor/55805.clinic-doctor-processstat
new file mode 100644
index 0000000..2749484
Binary files /dev/null and b/.clinic/55805.clinic-doctor/55805.clinic-doctor-processstat differ
diff --git a/.clinic/55805.clinic-doctor/55805.clinic-doctor-systeminfo b/.clinic/55805.clinic-doctor/55805.clinic-doctor-systeminfo
new file mode 100644
index 0000000..1c16e45
--- /dev/null
+++ b/.clinic/55805.clinic-doctor/55805.clinic-doctor-systeminfo
@@ -0,0 +1,36 @@
+{
+ "clock": {
+ "hrtime": [
+ 2101,
+ 300867597
+ ],
+ "unixtime": 1732694444466
+ },
+ "nodeVersions": {
+ "node": "20.18.1",
+ "acorn": "8.12.1",
+ "ada": "2.9.0",
+ "ares": "1.33.1",
+ "base64": "0.5.2",
+ "brotli": "1.1.0",
+ "cjs_module_lexer": "1.4.1",
+ "cldr": "45.0",
+ "icu": "75.1",
+ "llhttp": "8.1.2",
+ "modules": "115",
+ "napi": "9",
+ "nghttp2": "1.61.0",
+ "nghttp3": "0.7.0",
+ "ngtcp2": "1.1.0",
+ "openssl": "3.0.15+quic",
+ "simdutf": "5.5.0",
+ "tz": "2024b",
+ "undici": "6.20.0",
+ "unicode": "15.1",
+ "uv": "1.46.0",
+ "uvwasi": "0.0.21",
+ "v8": "11.3.244.8-node.23",
+ "zlib": "1.3.0.1-motley-71660e1"
+ },
+ "toolVersion": "11.0.0"
+}
\ No newline at end of file
diff --git a/.clinic/55805.clinic-doctor/55805.clinic-doctor-traceevent b/.clinic/55805.clinic-doctor/55805.clinic-doctor-traceevent
new file mode 100644
index 0000000..9bfef3c
--- /dev/null
+++ b/.clinic/55805.clinic-doctor/55805.clinic-doctor-traceevent
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10213706,"ph":"E","cat":"devtools.timeline,v8","name":"MinorGC","dur":0,"tdur":0,"args":{"usedHeapSizeAfter":45843360}},{"pid":55805,"tid":55805,"ts":2111663604,"tts":10254279,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":15,"tdur":15,"args":{}},{"pid":55805,"tid":55805,"ts":2111663611,"tts":10254286,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":6,"tdur":6,"args":{}},{"pid":55805,"tid":55805,"ts":2111664113,"tts":10254789,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":6,"tdur":5,"args":{}},{"pid":55805,"tid":55805,"ts":2111664117,"tts":10254792,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":2,"tdur":2,"args":{}},{"pid":55805,"tid":55805,"ts":2111664184,"tts":10254859,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":22,"tdur":22,"args":{}},{"pid":55805,"tid":55805,"ts":2111664204,"tts":10254879,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":2,"tdur":2,"args":{}},{"pid":55805,"tid":55805,"ts":2111664256,"tts":10254931,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":6,"tdur":6,"args":{}},{"pid":55805,"tid":55805,"ts":2111664259,"tts":10254934,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":3,"tdur":2,"args":{}},{"pid":55805,"tid":55805,"ts":2111664272,"tts":10254947,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":3,"tdur":3,"args":{}},{"pid":55805,"tid":55805,"ts":2111664274,"tts":10254949,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":1,"tdur":1,"args":{}},{"pid":55805,"tid":55805,"ts":2111664547,"tts":10255222,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":4,"tdur":4,"args":{}},{"pid":55805,"tid":55805,"ts":2111664550,"tts":10255225,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":1,"tdur":1,"args":{}},{"pid":55805,"tid":55805,"ts":2111664565,"tts":10255240,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":5,"tdur":5,"args":{}},{"pid":55805,"tid":55805,"ts":2111664569,"tts":10255244,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":1,"tdur":1,"args":{}},{"pid":55805,"tid":55805,"ts":2111664977,"tts":10255653,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":7,"tdur":6,"args":{}},{"pid":55805,"tid":55805,"ts":2111664981,"tts":10255656,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":3,"tdur":3,"args":{}},{"pid":55805,"tid":55805,"ts":2111684535,"tts":10256756,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":12,"tdur":11,"args":{}},{"pid":55805,"tid":55805,"ts":2111684543,"tts":10256763,"ph":"X","cat":"v8","name":"V8.DeoptimizeCode","dur":3,"tdur":3,"args":{}},{"pid":55805,"tid":55805,"ts":2101270076,"tts":3289,"ph":"M","cat":"__metadata","name":"process_name","dur":0,"tdur":0,"args":{"name":"node"}},{"pid":55805,"tid":55805,"ts":2101270077,"tts":3291,"ph":"M","cat":"__metadata","name":"version","dur":0,"tdur":0,"args":{"node":"20.18.1"}},{"pid":55805,"tid":55805,"ts":2101270078,"tts":3291,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"JavaScriptMainThread"}},{"pid":55805,"tid":55805,"ts":2101270094,"tts":3307,"ph":"M","cat":"__metadata","name":"node","dur":0,"tdur":0,"args":{"process":{"versions":{"node":"20.18.1","v8":"11.3.244.8-node.23","uv":"1.46.0","zlib":"1.3.0.1-motley-71660e1","brotli":"1.1.0","ares":"1.33.1","modules":"115","nghttp2":"1.61.0","napi":"9","llhttp":"8.1.2","uvwasi":"0.0.21","acorn":"8.12.1","simdutf":"5.5.0","ada":"2.9.0","undici":"6.20.0","cjs_module_lexer":"1.4.1","base64":"0.5.2","openssl":"3.0.15+quic","cldr":"45.0","icu":"75.1","tz":"2024b","unicode":"15.1","ngtcp2":"1.1.0","nghttp3":"0.7.0"},"arch":"x64","platform":"linux","release":{"name":"node","lts":"Iron"}}}},{"pid":55805,"tid":55808,"ts":2101270156,"tts":46,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"WorkerThreadsTaskRunner::DelayedTaskScheduler"}},{"pid":55805,"tid":55809,"ts":2101270305,"tts":79,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55811,"ts":2101270316,"tts":74,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55810,"ts":2101270318,"tts":84,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55812,"ts":2101270323,"tts":45,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55805,"ts":2101270076,"tts":3289,"ph":"M","cat":"__metadata","name":"process_name","dur":0,"tdur":0,"args":{"name":"node"}},{"pid":55805,"tid":55805,"ts":2101270077,"tts":3291,"ph":"M","cat":"__metadata","name":"version","dur":0,"tdur":0,"args":{"node":"20.18.1"}},{"pid":55805,"tid":55805,"ts":2101270078,"tts":3291,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"JavaScriptMainThread"}},{"pid":55805,"tid":55805,"ts":2101270094,"tts":3307,"ph":"M","cat":"__metadata","name":"node","dur":0,"tdur":0,"args":{"process":{"versions":{"node":"20.18.1","v8":"11.3.244.8-node.23","uv":"1.46.0","zlib":"1.3.0.1-motley-71660e1","brotli":"1.1.0","ares":"1.33.1","modules":"115","nghttp2":"1.61.0","napi":"9","llhttp":"8.1.2","uvwasi":"0.0.21","acorn":"8.12.1","simdutf":"5.5.0","ada":"2.9.0","undici":"6.20.0","cjs_module_lexer":"1.4.1","base64":"0.5.2","openssl":"3.0.15+quic","cldr":"45.0","icu":"75.1","tz":"2024b","unicode":"15.1","ngtcp2":"1.1.0","nghttp3":"0.7.0"},"arch":"x64","platform":"linux","release":{"name":"node","lts":"Iron"}}}},{"pid":55805,"tid":55808,"ts":2101270156,"tts":46,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"WorkerThreadsTaskRunner::DelayedTaskScheduler"}},{"pid":55805,"tid":55809,"ts":2101270305,"tts":79,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55811,"ts":2101270316,"tts":74,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55810,"ts":2101270318,"tts":84,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}},{"pid":55805,"tid":55812,"ts":2101270323,"tts":45,"ph":"M","cat":"__metadata","name":"thread_name","dur":0,"tdur":0,"args":{"name":"PlatformWorkerThread"}}]}
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..b11b48e
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,20 @@
+# Use an official Node.js runtime as a base image
+FROM node:18-alpine
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy package files to the container
+COPY package*.json ./
+
+# Install dependencies
+RUN npm install
+
+# Copy all application files
+COPY . .
+
+# Expose the port the app runs on
+EXPOSE 3000
+
+# Command to run the application
+CMD ["node", "index.js"]
diff --git a/controllers/metricsController.js b/controllers/metricsController.js
new file mode 100644
index 0000000..f173318
--- /dev/null
+++ b/controllers/metricsController.js
@@ -0,0 +1,33 @@
+const client = require('prom-client');
+
+// Create a Registry to register metrics
+const register = new client.Registry();
+client.collectDefaultMetrics({ register });
+
+// Custom metric: HTTP request counter
+const httpRequestCounter = new client.Counter({
+ name: 'http_requests_total',
+ help: 'Total number of HTTP requests',
+ labelNames: ['method', 'path', 'status'],
+});
+register.registerMetric(httpRequestCounter);
+
+// Middleware to count requests
+const trackRequests = (req, res, next) => {
+ res.on('finish', () => {
+ httpRequestCounter.inc({
+ method: req.method,
+ path: req.route ? req.route.path : req.path,
+ status: res.statusCode,
+ });
+ });
+ next();
+};
+
+// Metrics endpoint handler
+const getMetrics = async (req, res) => {
+ res.set('Content-Type', register.contentType);
+ res.send(await register.metrics());
+};
+
+module.exports = { trackRequests, getMetrics };
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 0000000..04023f1
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,31 @@
+version: '3.8'
+
+services:
+ node-api:
+ build:
+ context: .
+ dockerfile: Dockerfile
+ ports:
+ - "3000:3000"
+ environment:
+ - NODE_ENV=development
+
+ prometheus:
+ image: prom/prometheus
+ volumes:
+ - ./prometheus.yml:/etc/prometheus/prometheus.yml
+ ports:
+ - "9090:9090"
+
+ grafana:
+ image: grafana/grafana
+ ports:
+ - "3001:3000"
+ environment:
+ - GF_SECURITY_ADMIN_USER=admin
+ - GF_SECURITY_ADMIN_PASSWORD=admin
+ volumes:
+ - grafana-storage:/var/lib/grafana
+
+volumes:
+ grafana-storage:
diff --git a/index.js b/index.js
index d3c81b6..01f3874 100644
--- a/index.js
+++ b/index.js
@@ -10,6 +10,8 @@ const loginRoutes = require('./routes/loginRoutes');
const errorHandler = require('./middleware/errorHandler');
const swaggerJsDoc = require('swagger-jsdoc');
const { swaggerUi, swaggerSpec } = require('./config/swagger'); // Import Swagger UI
+const metricsRoutes = require('./routes/metricsRoutes');
+const { trackRequests } = require('./controllers/metricsController');
dotenv.config();
@@ -22,6 +24,7 @@ app.use(express.json());
app.use(helmet());
app.use(bodyParser.json());
app.use(bodyParser.urlencoded({ extended: true }));
+app.use(trackRequests);
// Rate Limiting
const globalLimiter = rateLimit({
@@ -51,6 +54,9 @@ app.use('/users', userRoutes);
// Use login routes
app.use('/', loginRoutes);
+// Use metrics routes
+app.use('/metrics', metricsRoutes);
+
// Error Handler
app.use(errorHandler);
diff --git a/package-lock.json b/package-lock.json
index 65d8427..276741a 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -23,6 +23,7 @@
"multer": "^1.4.5-lts.1",
"nodemailer": "^6.9.16",
"pg": "^8.12.0",
+ "prom-client": "^15.1.3",
"redis": "^4.7.0",
"swagger-jsdoc": "^6.2.8",
"swagger-ui-express": "^5.0.1",
@@ -2249,6 +2250,15 @@
"integrity": "sha512-4JQNk+3mVzK3xh2rqd6RB4J46qUR19azEHBneZyTZM+c456qOrbbM/5xcR8huNCCcbVt7+UmizG6GuUvPvKUYg==",
"license": "MIT"
},
+ "node_modules/@opentelemetry/api": {
+ "version": "1.9.0",
+ "resolved": "https://registry.npmjs.org/@opentelemetry/api/-/api-1.9.0.tgz",
+ "integrity": "sha512-3giAOQvZiH5F9bMlMiv8+GSPMeqg0dbaeo58/0SlA9sxSqZhnUtxzX9/2FzyhS9sWQf5S0GJE0AKBrFqjpeYcg==",
+ "license": "Apache-2.0",
+ "engines": {
+ "node": ">=8.0.0"
+ }
+ },
"node_modules/@redis/bloom": {
"version": "1.2.0",
"resolved": "https://registry.npmjs.org/@redis/bloom/-/bloom-1.2.0.tgz",
@@ -2826,6 +2836,12 @@
"url": "https://github.com/sponsors/sindresorhus"
}
},
+ "node_modules/bintrees": {
+ "version": "1.0.2",
+ "resolved": "https://registry.npmjs.org/bintrees/-/bintrees-1.0.2.tgz",
+ "integrity": "sha512-VOMgTMwjAaUG580SXn3LacVgjurrbMme7ZZNYGSSV7mmtY6QQRh0Eg3pwIcntQ77DErK1L0NxkbetjcoXzVwKw==",
+ "license": "MIT"
+ },
"node_modules/body-parser": {
"version": "1.20.3",
"resolved": "https://registry.npmjs.org/body-parser/-/body-parser-1.20.3.tgz",
@@ -6968,6 +6984,19 @@
"node": ">=8"
}
},
+ "node_modules/prom-client": {
+ "version": "15.1.3",
+ "resolved": "https://registry.npmjs.org/prom-client/-/prom-client-15.1.3.tgz",
+ "integrity": "sha512-6ZiOBfCywsD4k1BN9IX0uZhF+tJkV8q8llP64G5Hajs4JOeVLPCwpPVcpXy3BwYiUGgyJzsJJQeOIv7+hDSq8g==",
+ "license": "Apache-2.0",
+ "dependencies": {
+ "@opentelemetry/api": "^1.4.0",
+ "tdigest": "^0.1.1"
+ },
+ "engines": {
+ "node": "^16 || ^18 || >=20"
+ }
+ },
"node_modules/prompts": {
"version": "2.4.2",
"resolved": "https://registry.npmjs.org/prompts/-/prompts-2.4.2.tgz",
@@ -7897,6 +7926,15 @@
"express": ">=4.0.0 || >=5.0.0-beta"
}
},
+ "node_modules/tdigest": {
+ "version": "0.1.2",
+ "resolved": "https://registry.npmjs.org/tdigest/-/tdigest-0.1.2.tgz",
+ "integrity": "sha512-+G0LLgjjo9BZX2MfdvPfH+MKLCrxlXSYec5DaPYP1fe6Iyhf0/fSmJ0bFiZ1F8BT6cGXl2LpltQptzjXKWEkKA==",
+ "license": "MIT",
+ "dependencies": {
+ "bintrees": "1.0.2"
+ }
+ },
"node_modules/test-exclude": {
"version": "6.0.0",
"resolved": "https://registry.npmjs.org/test-exclude/-/test-exclude-6.0.0.tgz",
diff --git a/package.json b/package.json
index daadb19..96f6324 100644
--- a/package.json
+++ b/package.json
@@ -19,6 +19,7 @@
"multer": "^1.4.5-lts.1",
"nodemailer": "^6.9.16",
"pg": "^8.12.0",
+ "prom-client": "^15.1.3",
"redis": "^4.7.0",
"swagger-jsdoc": "^6.2.8",
"swagger-ui-express": "^5.0.1",
diff --git a/prometheus.yml b/prometheus.yml
new file mode 100644
index 0000000..3934b77
--- /dev/null
+++ b/prometheus.yml
@@ -0,0 +1,7 @@
+global:
+ scrape_interval: 5s
+
+scrape_configs:
+ - job_name: 'node-api-postgres'
+ static_configs:
+ - targets: ['localhost:3000'] # Adjust this if running Docker Desktop
diff --git a/routes/metricsRoutes.js b/routes/metricsRoutes.js
new file mode 100644
index 0000000..0b2f2ed
--- /dev/null
+++ b/routes/metricsRoutes.js
@@ -0,0 +1,9 @@
+const express = require('express');
+const { getMetrics } = require('../controllers/metricsController');
+
+const router = express.Router();
+
+// Metrics endpoint
+router.get('/', getMetrics);
+
+module.exports = router;