Enable debugging terraform

By default, a terraform plan or apply run only shows the resources to create, update or delete. It doesn’t give much detail on the activity terraform is doing behind the scene. All the debug logging would especially be helpful when you encounter an error.

Here is a typical terraform plan output, in this case it is a code for creating a firewall rule in Google cloud platform(GCP) –

$ terraform plan
Refreshing Terraform state in-memory prior to plan...
...
------------------------------------------------------------------------

An execution plan has been generated and is shown below.
Resource actions are indicated with the following symbols:
  + create

Terraform will perform the following actions:

# google_compute_firewall.glb-allow will be created
  + resource "google_compute_firewall" "glb-allow" {
      + creation_timestamp = (known after apply)
      + description        = "Allow GLB proxies"
      + destination_ranges = (known after apply)
      + direction          = (known after apply)
      + id                 = (known after apply)
      + name               = "allow-glb-access"
      + network            = "internal"
      + priority           = 1000
      + project            = "my-gcp-project"
      + self_link          = (known after apply)
      + source_ranges      = [
          + "130.211.0.0/22",
          + "35.191.0.0/16",
        ]
      + target_tags        = [
          + "webservers",
        ]

      + allow {
          + ports    = [
              + "80",
              + "443",
              + "8080",
              + "8443",
            ]
          + protocol = "tcp"
        }
    }

Plan: 1 to add, 0 to change, 0 to destroy.

Terraform supports an environment variable – TF_LOG – for detailed logging purposes. You can set the logging to different severity levels which includes – TRACE, DEBUG, INFO, WARN, and ERROR

$ TF_LOG=DEBUG terraform plan
2020/03/20 17:03:39 [WARN] Log levels other than TRACE are currently unreliable, and are supported only for backward compatibility.
  Use TF_LOG=TRACE to see Terraform's internal logs.
  ----
2020/03/20 17:03:39 [INFO] Terraform version: 0.12.20  
2020/03/20 17:03:39 [INFO] Go runtime version: go1.12.13
2020/03/20 17:03:39 [INFO] CLI args: []string{"/usr/local/bin/terraform", "plan"}
2020/03/20 17:03:39 [DEBUG] Attempting to open CLI config file: /home/daniel/.terraformrc
2020/03/20 17:03:39 [DEBUG] File doesn't exist, but doesn't need to. Ignoring.
2020/03/20 17:03:39 [INFO] CLI command args: []string{"plan"}
2020/03/20 17:03:39 [DEBUG] checking for provider in "." 
2020/03/20 17:03:39 [DEBUG] checking for provider in "/usr/local/bin"
2020/03/20 17:03:39 [DEBUG] checking for provider in ".terraform/plugins/linux_amd64"
2020/03/20 17:03:39 [DEBUG] found provider "terraform-provider-google_v3.13.0_x5"
....

Terraform also supports saving logs to a file with the TF_LOG_PATH environment variable.

$ TF_LOG=DEBUG TF_LOG_PATH=/tmp/terraform-debug.log terraform plan
...
$ ls -lh /tmp/terraform-debug.log
-rw-r--r-- 1 daniel daniel 15K Mar 20 17:06 /tmp/terraform-debug.log

References

https://www.terraform.io/docs/internals/debugging.html

Using curl to get help on Linux commands, programming languages and more. The most comprehensive cheat sheet.

If you are looking for a Linux and programming cheat sheet, please check
https://github.com/chubin/cheat.sh

It provides nicely colored help page, with plenty of examples in a CLI. Here are some sample runs I did.

Curl cheat sheet

daniel@hidmo:/tmp$ curl cheat.sh/curl
# Download a single file
curl http://path.to.the/file

# Download a file and specify a new filename
curl http://example.com/file.zip -o new_file.zip

# Download multiple files
curl -O URLOfFirstFile -O URLOfSecondFile

# Download all sequentially numbered files (1-24)
curl http://example.com/pic[1-24].jpg

# Download a file and follow redirects
curl -L http://example.com/file

# Download a file and pass HTTP Authentication
curl -u username:password URL 

# Download a file with a Proxy
curl -x proxysever.server.com:PORT http://addressiwantto.access

# Download a file from FTP
curl -u username:password -O ftp://example.com/pub/file.zip

# Get an FTP directory listing
curl ftp://username:password@example.com

# Resume a previously failed download
curl -C - -o partial_file.zip http://example.com/file.zip

# Fetch only the HTTP headers from a response
curl -I http://example.com

# Fetch your external IP and network info as JSON
curl http://ifconfig.me/all/json

# Limit the rate of a download
curl --limit-rate 1000B -O http://path.to.the/file

# POST to a form
curl -F "name=user" -F "password=test" http://example.com

# POST JSON Data
curl -H "Content-Type: application/json" -X POST -d '{"user":"bob","pass":"123"}' http://example.com

# POST data from the standard in / share data on sprunge.us
curl -F 'sprunge=<-' sprunge.us

Python lists cheat list

daniel@hidmo:/tmp$ curl cheat.sh/python/list
#  python - Why does += behave unexpectedly on lists?
#  
#  The general answer is that += tries to call the __iadd__ special
#  method, and if that isn't available it tries to use __add__ instead.
#  So the issue is with the difference between these special methods.
#  
#  The __iadd__ special method is for an in-place addition, that is it
#  mutates the object that it acts on. The __add__ special method returns
#  a new object and is also used for the standard + operator.
#  
#  So when the += operator is used on an object which has an __iadd__
#  defined the object is modified in place. Otherwise it will instead try
#  to use the plain __add__ and return a new object.
#  
#  That is why for mutable types like lists += changes the object's
#  value, whereas for immutable types like tuples, strings and integers a
#  new object is returned instead (a += b becomes equivalent to a = a +
#  b).
#  
#  For types that support both __iadd__ and __add__ you therefore have to
#  be careful which one you use. a += b will call __iadd__ and mutate a,
#  whereas a = a + b will create a new object and assign it to a. They
#  are not the same operation!

>>> a1 = a2 = [1, 2]
>>> b1 = b2 = [1, 2]
>>> a1 += [3]          # Uses __iadd__, modifies a1 in-place
>>> b1 = b1 + [3]      # Uses __add__, creates new list, assigns it to b1
>>> a2
[1, 2, 3]              # a1 and a2 are still the same list
>>> b2
[1, 2]                 # whereas only b1 was changed

#  For immutable types (where you don't have an __iadd__) a += b and a =
#  a + b are equivalent. This is what lets you use += on immutable types,
#  which might seem a strange design decision until you consider that
#  otherwise you couldn't use += on immutable types like numbers!
#  
#  [Scott Griffiths] [so/q/2347265] [cc by-sa 3.0]

Golang concurrency cheat sheet

daniel@hidmo:/tmp$ curl cheat.sh/go/concurrency
/*
 * go - When should I use concurrency in golang?
 * 
 * Not an expert in Go (yet) but I'd say:
 * 
 * Whenever it is easiest to do so.
 * 
 * The beauty of the concurrency model in Go is that it is not
 * fundamentally a multi-core architecture with checks and balances where
 * things usually break - it is a multi-threaded paradigm that not only
 * fits well into a multi-core architecture, it also fits well into a
 * distributed system architecture.
 * 
 * You do not have to make special arrangements for multiple goroutines
 * to work together harmoniously - they just do!
 * 
 * Here's an example of a naturally concurrent algorithm - I want to
 * merge multiple channels into one. Once all of the input channels are
 * exhausted I want to close the output channel.
 * 
 * It is just simpler to use concurrency - in fact it doesn't even look
 * like concurrency - it looks almost procedural.
 */

/*
  Multiplex a number of channels into one.
*/
func Mux(channels []chan big.Int) chan big.Int {
    // Count down as each channel closes. When hits zero - close ch.
    var wg sync.WaitGroup
    wg.Add(len(channels))
    // The channel to output to.
    ch := make(chan big.Int, len(channels))

    // Make one go per channel.
    for _, c := range channels {
        go func(c <-chan big.Int) {
            // Pump it.
            for x := range c {
                ch <- x
            }
            // It closed.
            wg.Done()
        }(c)
    }
    // Close the channel when the pumping is finished.
    go func() {
        // Wait for everyone to be done.
        wg.Wait()
        // Close.
        close(ch)
    }()
    return ch
}

/*
 * The only concession I have to make to concurrency here is to use a
 * sync.WaitGroup as a counter for concurrent counting.
 * 
 * Note that this is not purely my own work - I had a great deal of help
 * with this here (https:stackoverflow.com/q/19192377/823393).
 * 
 * [OldCurmudgeon] [so/q/19747950] [cc by-sa 3.0]
 */

Please check
https://github.com/chubin/cheat.sh for more information on installation and using its comprehensive features.

curl – use variables to show response times and other parameters

curl is a tool to interact with a server for transferring data. Although it supports various protocols, it is most commonly used with HTTP/S. It is sort of a browser for CLI folks and a go to tool when writing scripts to interact with servers.

In addition to transferring data, how do we show request and response parameters with curl. The answer is using variables, the complete list of variables can be found here.

Example – use “time_total” to show the total time, in seconds, that the full operation lasted.

$ curl  -w %{time_total} https://www.gcplinux.com
1.149143

It is best to add the variables in a file and use curl to reference the file for better formatting. Here I have added several http request and response variables I am interested in, such as num_connects, size_download, size_header, time_namelookup, time_pretransfer etc.

daniel@hidmo:/tmp$ cat ccurl.txt 
      url_effective:  %{url_effective}\n
       content_type:  %{content_type}\n
          http_code:  %{http_code}\n
       http_version:  %{http_version}\n
       num_connects:  %{num_connects}\n
      num_redirects:  %{num_redirects}\n
          remote_ip:  %{remote_ip}\n
      size_download:  %{size_download}\n
        size_header:  %{size_header}\n
    time_namelookup:  %{time_namelookup}\n
       time_connect:  %{time_connect}\n
    time_appconnect:  %{time_appconnect}\n
   time_pretransfer:  %{time_pretransfer}\n
      time_redirect:  %{time_redirect}\n
 time_starttransfer:  %{time_starttransfer}\n
                    ----------\n
         time_total:  %{time_total}\n


daniel@hidmo:/tmp$ curl -H 'Cache-Control: no-cache' -L -w "@ccurl.txt" -o /dev/null -s https://www.gcplinux.com
      url_effective:  https://gcplinux.com/
       content_type:  text/html; charset=UTF-8
          http_code:  200
       http_version:  1.1
       num_connects:  2
      num_redirects:  1
          remote_ip:  162.247.79.246
      size_download:  71273
        size_header:  537
    time_namelookup:  0.008585
       time_connect:  0.082511
    time_appconnect:  0.264110
   time_pretransfer:  0.264293
      time_redirect:  1.287257
 time_starttransfer:  3.077526
                    ----------
         time_total:  3.177939

As far as time related parameters, listed below are the ones you will most likely use –

• time_appconnect The time, in seconds, it took from the start until the SSL/SSH/etc connect/handshake to the remote host was completed. (Added in 7.19.0)
• time_connect The time, in seconds, it took from the start until the TCP connect to the remote host (or proxy) was completed.
• time_namelookup The time, in seconds, it took from the start until the name resolving was completed.
• time_pretransfer The time, in seconds, it took from the start until the file transfer was just about to begin. This includes all pre-transfer commands and negotiations that are specific to the particular protocol(s) involved.
• time_redirect The time, in seconds, it took for all redirection steps including name lookup, connect, pretransfer and transfer before the final transaction was started. time_redirect shows the complete execution time for multiple redirections. (Added in 7.12.3)
• time_starttransfer The time, in seconds, it took from the start until the first byte was just about to be transferred. This includes time_pretransfer and also the time the server needed to calculate the result.
• time_total The total time, in seconds, that the full operation lasted.

References –

https://curl.haxx.se/docs/manpage.html

https://stackoverflow.com/questions/18215389/how-do-i-measure-request-and-response-times-at-once-using-curl

How to zip or compress a folder or directory in Linux

In Linux or similar Operating Systems, zip utility is used to package and compress (archive) files.

Let us get straight to action, we have a folder to compress with zip tool –

daniel@hidmo:/tmp/tutorial$ tree .
.
??? zip-tutorial
    ??? chapter-1
    ?   ??? content
    ??? chapter-2
    ?   ??? readme
    ??? zip.txt

daniel@hidmo:/tmp/tutorial$ zip -r tutorial.zip zip-tutorial/
  adding: zip-tutorial/ (stored 0%)
  adding: zip-tutorial/zip.txt (deflated 55%)
  adding: zip-tutorial/chapter-2/ (stored 0%)
  adding: zip-tutorial/chapter-2/readme (deflated 55%)
  adding: zip-tutorial/chapter-1/ (stored 0%)
  adding: zip-tutorial/chapter-1/content (deflated 57%)

Basically we use “zip -r DESTINATION-FILE.ZIP FOLDER-TO-COMPRESS” to compress directory. Or in short “zip -r DESTINATION-FILE DIRECTORY-TO-COMPRESS“, we can skip the .zip extension.

daniel@hidmo:/tmp/tutorial$ zip -r tutorial zip-tutorial/
updating: zip-tutorial/ (stored 0%)
  adding: zip-tutorial/zip.txt (deflated 55%)
  adding: zip-tutorial/chapter-2/ (stored 0%)
  adding: zip-tutorial/chapter-2/readme (deflated 55%)
  adding: zip-tutorial/chapter-1/ (stored 0%)
  adding: zip-tutorial/chapter-1/content (deflated 57%)

To view the contents of the compressed folder without uncompressing it –

daniel@hidmo:/tmp/tutorial$ unzip -l tutorial.zip 
Archive:  tutorial.zip
  Length      Date    Time    Name
---------  ---------- -----   ----
        0  2019-10-07 21:45   zip-tutorial/
     1202  2019-10-07 21:45   zip-tutorial/zip.txt
        0  2019-10-07 21:45   zip-tutorial/chapter-2/
     1202  2019-10-07 21:45   zip-tutorial/chapter-2/readme
        0  2019-10-07 21:44   zip-tutorial/chapter-1/
      722  2019-10-07 21:44   zip-tutorial/chapter-1/content
---------                     -------
     3126                     6 files

References –

https://linux.die.net/man/1/zip

https://superuser.com/questions/216617/view-list-of-files-in-zip-archive-on-linux

Linux – how to avoid running an alias command in shell

In some cases, you might have multiple binaries, scripts or aliases with the same name in your system. Under certain circumstances you want to run only a built-in shell command, but no an alias of the command. Here are some ways to do it.

The “ls” command is usually aliased to color the output, for instance –

$ type ls
ls is aliased to `ls --color=auto'

Precede the command with “command” or “\”

$ command ls /tmp/tutorial/
chapter-one  readme

$ \ls /tmp/tutorial/
chapter-one  readme

References –

https://www.tldp.org/LDP/abs/html/aliases.html

https://www.gnu.org/software/bash/manual/html_node/Bash-Builtins.html

Linux – Cannot assign requested address

While running a performance test on a local web service, I encountered below error –

$ ab -n 600000 -c 10000 http://localhost:8080/test
...
Benchmarking localhost (be patient)

Test aborted after 10 failures

apr_socket_connect(): Cannot assign requested address (99)

Clearly the number of concurrent requests(-n) and concurrent connections(-c) is high. But would it be possible to tweak my system so that it can handle this? Apparently yes. Doing some reading no Ephemeral port range. For a typical TCP connection, a 4-tuple of source IP/port and destination IP/port is required. In our case, the source and destination IP is fixed (127.0.0.1) as well as the destination port (8080). How many source port range do we have?

$ cat /proc/sys/net/ipv4/ip_local_port_range 
32768	60999

$ echo $((60999-32768))
28231

By increasing this port range, the system will accept more concurrent connections. Run below command under root –

root@lindell:~# echo "16000 65535" > /proc/sys/net/ipv4/ip_local_port_range
root@lindell:~# cat /proc/sys/net/ipv4/ip_local_port_range
16000	65535

The performance test now runs successfully –

$ ab -n 600000 -c 10000 http://localhost:8080/test
This is ApacheBench, Version 2.3 <$Revision: 1706008 $>
Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Licensed to The Apache Software Foundation, http://www.apache.org/

Benchmarking localhost (be patient)
Completed 60000 requests
Completed 120000 requests
Completed 180000 requests
Completed 240000 requests
Completed 300000 requests
Completed 360000 requests
Completed 420000 requests
Completed 480000 requests
Completed 540000 requests
Completed 600000 requests
Finished 600000 requests


Server Software:        
Server Hostname:        localhost
Server Port:            8080

Document Path:          /test
Document Length:        13 bytes

Concurrency Level:      10000
Time taken for tests:   122.307 seconds
Complete requests:      600000
Failed requests:        0
Total transferred:      78000000 bytes
HTML transferred:       7800000 bytes
Requests per second:    4905.69 [#/sec] (mean)
Time per request:       2038.449 [ms] (mean)
Time per request:       0.204 [ms] (mean, across all concurrent requests)
Transfer rate:          622.79 [Kbytes/sec] received

Connection Times (ms)
              min  mean[+/-sd] median   max
Connect:      308  848 180.0    833    3955
Processing:   293 1175 198.5   1190    1967
Waiting:       88  882 210.3    946    1738
Total:        932 2023 208.9   2018    5146

Percentage of the requests served within a certain time (ms)
  50%   2018
  66%   2085
  75%   2115
  80%   2138
  90%   2216
  95%   2298
  98%   2411
  99%   2961
 100%   5146 (longest request)


$ netstat -talpn |grep '127.0.0.1:8080' |wc -l
34241

References –

https://www.ncftp.com/ncftpd/doc/misc/ephemeral_ports.html

https://httpd.apache.org/docs/2.4/programs/ab.html