docs: address additional comments

Signed-off-by: mbshields <[email protected]>

.wordlist.txt

@@ -41,7 +41,6 @@ CRI
 crt
 CSS
 cURL
-curl
 cve
 CVE
 CVEs

docs/admin-guide/admin-configuration.md

@@ -314,18 +314,24 @@ zot supports a range of monitoring tools including the following:
 
 *  Metrics
 
-   Metrics data is available in a Prometheus format. A full zot image with extensions includes a node exporter. A minimal zot image can use an external node exporter such as `zxp`.
+    Metrics data is available in a Prometheus format. A full zot image with extensions includes a node exporter. A minimal zot image can use an external node exporter such as `zxp`.
 
 * Benchmarking
 
-  The zot project includes the `zb` tool, which allows you to benchmark a zot registry or any other container image registry that conforms to the [OCI Distribution Specification](https://github.com/opencontainers/distribution-spec).
+    The zot project includes the `zb` tool, which allows you to benchmark a zot registry or any other container image registry that conforms to the [OCI Distribution Specification](https://github.com/opencontainers/distribution-spec).
+
+* Performance profiling
+
+    Performance profiling capabilities within zot allow a zot [administrator](../articles/authn-authz.md) to collect and export a range of diagnostic performance data such as CPU intensive function calls, memory allocations, and execution traces. The collected data can then be analyzed using Go tools and a variety of available visualization tools.
 
 When zot is deployed in a Kubernetes setup, a site reliability engineering (SRE) operator can monitor service level indicators (SLI) such as metrics and logs. Metrics will appear in [Prometheus](https://prometheus.io/docs/guides/query-log/) using the zot `metrics` extension, while logs will appear in the Elasticsearch stack ([ELK stack](https://www.elastic.co/what-is/elk-stack)) using [Filebeat](https://www.elastic.co/beats/filebeat).
 
 For detailed information about the monitoring tools, see [Monitoring the registry](../articles/monitoring.md).
 
 For detailed information about benchmarking, see [Benchmarking zot with zb](../articles/benchmarking-with-zb.md).
 
+For detailed information about performance profiling, see [Performance Profiling in zot](../articles/pprofiling.md).
+
 <a name="cluster_config"></a>
 
 ## Clustering zot

docs/developer-guide/pprofiling.md → docs/articles/pprofiling.md

@@ -2,11 +2,15 @@
 
 > :point_right: Use zot's built-in profiling tools to collect and analyze runtime performance.
 
-The profiling capabilities within zot allow a zot [administrator](../articles/authn-authz.md) to collect and export a range of diagnostic performance data such as CPU intensive function calls, memory allocations, and execution traces. The collected data can then be analyzed using go tools and a variety of available visualization tools.
+The profiling capabilities within zot allow a zot [administrator](../articles/authn-authz.md) to collect and export a range of diagnostic performance data such as CPU intensive function calls, memory allocations, and execution traces. The collected data can then be analyzed using Go tools and a variety of available visualization tools.
+
+> :pencil2: If authentication is enabled, only a zot admin user can access the APIs for profiling.
+>
+> :pencil2: All examples in this article assume that the zot registry is running at `localhost:8080`.
 
 ## What data is available?
 
-The zot source code incorporates runtime analysis tools to collect data for the following performance-related profiles:
+The zot source code incorporates [golang's pprof package](https://pkg.go.dev/runtime/pprof) of runtime analysis tools to collect data for the following performance-related profiles:
 
 | Profile  | Description |
 | ------- | --------- |
@@ -20,7 +24,7 @@ The zot source code incorporates runtime analysis tools to collect data for the
 | threadcreate | Stack traces that led to the creation of new OS threads. |
 | trace | A trace of execution of the current program. You can specify the duration in the `seconds` URL query parameter. After you get the trace file, use the `go tool trace` command to investigate the trace. |
 
-To return an HTML-format profile list along with a count of currently available records for each profile, use the following API command: 
+To return a current HTML-format profile list along with a count of currently available records for each profile, use the following API command: 
 
     /v2/_zot/pprof/
 
@@ -30,80 +34,60 @@ To return an HTML-format profile list along with a count of currently available
 
 To collect and export any available profile, use the following API command format:
 
-    /v2/_zot/pprof/<profile-name>[?<query-parameters>]
-
-The following example shows an API request for the CPU usage profile named `profile` using a collection window of 10 seconds:
-
-    $ curl -s -v http://localhost:8080/v2/_zot/pprof/profile?seconds=10 > cpu10.prof
-    *   Trying 127.0.0.1:8080...
-    * Connected to localhost (127.0.0.1) port 8080 (#0)
-    > GET /v2/_zot/pprof/profile?seconds=10 HTTP/1.1
-    > Host: localhost:8080
-    > User-Agent: curl/8.1.2
-    > Accept: */*
-    > 
-    < HTTP/1.1 200 OK
-    < Content-Disposition: attachment; filename="profile"
-    < Content-Type: application/octet-stream
-    < X-Content-Type-Options: nosniff
-    < Date: Tue, 26 Sep 2023 17:01:28 GMT
-    < Content-Length: 107
-    < 
-    { [107 bytes data]
-    * Connection #0 to host localhost left intact
-
-This command creates an output data file named "cpu10.prof".
-
-- Using the query parameter `?seconds=<number>`, we specify the number of seconds to gather the profile data. If this parameter is not specified, the default is 30 seconds.
-- In this example, the raw output data is redirected to a file named "cpu10.prof". Alternatively, you can use `curl -O` to create a file with the default profile name (in this case, "profile"). If no output file is specified by either a cURL flag or an output redirection, the cURL command fails with "Failure writing output to destination". 
+    /v2/_zot/pprof/<profile-type>[?<query-parameters>]
+
+The following example shows an API request for the CPU usage profile named `profile` using a collection window of 30 seconds:
+
+    $ curl -s http://localhost:8080/v2/_zot/pprof/profile?seconds=30 > cpu.prof
+
+This command example creates an output data file named "cpu.prof".
+
+- The query parameter `?seconds=<number>` specifies the number of seconds to gather the profile data. If this parameter is not specified, the default is 30 seconds.
+- In this example, the raw output data is redirected to a file named "cpu.prof". Alternatively, you can use `curl -O` to create a file with the default profile name (in this case, "profile"). If no output file is specified by either a cURL flag or an output redirection, the cURL command fails with "Failure writing output to destination". 
 - The command output file is in a machine-readable format that can be interpreted by performance analyzers.
 
 
 ## Analyzing the CPU usage profile using `go tool pprof`
 
-The pprof package provides a variety of presentation formats for analyzing runtime performance.
+Go's pprof package provides a variety of presentation formats for analyzing runtime performance.
 
 For detailed information, see the [pprof documentation](https://pkg.go.dev/runtime/pprof).
 
 
 ### Generating a pprof web presentation
 
-When an HTTP port is specified as a command flag, the `go tool pprof` command installs and opens a local web server that provides a web interface for viewing and analyzing the profile data.  This example opens a localhost page at port 9090 for viewing the CPU usage data captured in the profile file named "cpu10.prof". 
+When an HTTP port is specified as a command flag, the `go tool pprof` command installs and opens a local web server that provides a web interface for viewing and analyzing the profile data.  This example opens a localhost page at port 9090 for viewing the CPU usage data captured in the profile file named "cpu.prof". 
 
-    $ go tool pprof -http=:9090 cpu10.prof
+    $ go tool pprof -http=:9090 cpu.prof
     Serving web UI on http://localhost:9090
 
-The pprof web view offers several options for viewing and interpreting the collected performance data.  Select VIEW to see the following options:
+The pprof web view offers several options for viewing and interpreting the collected performance data.  Select VIEW to see the available options:
 
 ![pprof-view.jpg](../assets/images/pprof-view.jpg){width="300"}
 
 A Flame Graph can be very useful for analyzing CPU usage:
 
-![flame.svg](../assets/images/flame.svg){width="300"}
+![profiling-flame.svg](../assets/images/profiling-flame.svg){width="300"}
 
 
 ### Generating a graphic image
 
-The pprof package can generate graphic representations of profile data in many formats. This example generates a GIF file representing the CPU usage in the "cpu10.prof" file.
-
-    $ go tool pprof -gif cpu10.prof
-    Generating report in profile001.gif
-
-![profile001.gif](../assets/images/profile001.gif){width="300"}
+The pprof package can generate graphic representations of profile data in many formats. This example generates a PNG file representing the CPU usage in the "cpu.prof" file.
 
-!!! note "Documentation comments"
+    $ go tool pprof -png cpu.prof
+    Generating report in profile001.png
 
-    Is this section helpful?  Need a more interesting illustration (maybe Flame?)
+![profile001.png](../assets/images/profile001.png){width="300"}
 
 
 ### Opening a pprof interactive session
 
 This example opens an interactive session with pprof and executes the pprof `top` command, which displays the top ten modules by CPU usage during the profiling capture window.
 
-    $ go tool pprof cpu10.prof
+    $ go tool pprof cpu.prof
     Type: cpu
     Time: Sep 26, 2023 at 10:01am (PDT)
-    Duration: 10s, Total samples = 10ms (  0.1%)
+    Duration: 30s, Total samples = 10ms (  0.1%)
     Entering interactive mode (type "help" for commands, "o" for options)
     (pprof) top
     Showing nodes accounting for 10ms, 100% of 10ms total
@@ -118,29 +102,28 @@ This example opens an interactive session with pprof and executes the pprof `top
             0     0%   100%       10ms   100%  runtime.semawakeup
     (pprof)
 
-!!! note "Documentation comments"
-
-    Is this section helpful?  If so, it would be better to have more realistic data.
 
 ## Analyzing the trace profile using `go tool trace`
 
-!!! note "Documentation comments"
-
-    Is this section helpful? 
-
 You can collect trace data with the `trace` profile, as in this example:
 
-      $ curl -s -v http://localhost:8080/v2/_zot/pprof/trace?seconds=10 > trace10.prof
+      $ curl -s -v http://localhost:8080/v2/_zot/pprof/trace?seconds=30 > trace.prof
 
-Using the `go tool trace` package, you can analyze the trace data captured in the "trace10.prof" example file:
+Using the `go tool trace` package, you can analyze the trace data captured in the "trace.prof" example file:
 
-    $ go tool trace trace10.prof
+    $ go tool trace trace.prof
     2023/09/21 16:58:58 Parsing trace...
     2023/09/21 16:58:58 Splitting trace...
     2023/09/21 16:58:58 Opening browser. Trace viewer is listening on http://127.0.0.1:62606
 
 The `go tool trace` command installs and opens a local web server that provides a web interface for viewing and analyzing the trace data.
 
-> :bulb: As an alternative, you can generate a pprof-like profile from the trace file using the following command:
+As an alternative, you can generate a pprof-like profile from the trace file using the following command:
+
+    $ go tool trace -pprof=[net|sync|syscall|sched] <filename>
+
+For example:
+
+    $ go tool trace -pprof=net trace.prof
+
 
-    go tool trace -pprof=[net|sync|syscall|sched] trace10.prof

docs/developer-guide/onboarding.md

@@ -102,6 +102,12 @@ Delve is a powerful open-source debugger for the Go programming
 language. Downloads and documentation for Delve are available on GitHub
 at <https://github.com/go-delve/delve>.
 
+## Performance profiling
+
+Performance profiling capabilities within zot allow a zot [administrator](../articles/authn-authz.md) to collect and export a range of diagnostic performance data such as CPU intensive function calls, memory allocations, and execution traces. The collected data can then be analyzed using Go tools and a variety of available visualization tools.
+
+For detailed information about performance profiling, see [Performance Profiling in zot](../articles/pprofiling.md).
+
 ## Code Organization
 
 The zot project codebase is organized as follows:

mkdocs.yml

@@ -110,7 +110,6 @@ nav:
   - Developer Guide: 
     - Onboarding: developer-guide/onboarding.md
     - Extensions: developer-guide/extensions-dev.md
-    - Performance Profiling: developer-guide/pprofiling.md
     - Contributing: developer-guide/contributing.md
   - Articles:
     - CI/CD Pipeline: articles/building-ci-cd-pipeline.md
@@ -122,6 +121,7 @@ nav:
     - Clustering: articles/clustering.md
     - Monitoring: articles/monitoring.md
     - Benchmarking with zb: articles/benchmarking-with-zb.md
+    - Performance Profiling: articles/pprofiling.md
     - Using kind for Deployment Testing: articles/kind-deploy.md
 extra_css:
   - stylesheets/custom.css