I was looking for a crontab replacement with a more robust UI and stumbled into Cronicle and decided to give it a try using AWS Lightsail. These steps are really more for my own reference but I figure someone might find them useful. Getting Cronicle on Lightsail is pretty straight forward but I did run into a few things that I didn’t want to have to Google in the future.
Here are the basic steps to get a working instance of Cronicle up and running followed by the action bash commands:
Through website work I’m doing I look at California Highway Patrol data and recently noticed an Apple Emergency SOS alert that was placed and found the content of the messaging interesting and offers some insight into how this system works in a real emergency.
[22:40:00 GMT-08:00 07 JAN 2023] (▪▪▪) ▪▪▪-▪▪▪▪: A USER IS REQUESTING EMERGENCY SERVICES FROM AN APPLE DEVICE VIA SATELLITE. TRANSMIT AND RECEIVE TIMES MAY BE LONGER THAN FOR CELLULAR SMS. USER RESPONSES MAY BE DELAYED DUE TO SATELLITE MOVEMENTS.THE USER CANNOT MAKE OR RECEIVE A VOICE CALL BECAUSE THEY ARE OUTSIDE CELLULAR COVERAGE.AT 06:39AM UTC, M▪▪▪▪▪ F▪▪▪▪ REQUESTED EMERGENCY SERVICES NEAR THESE COORDINATES: LATITUDE 40.7963 (N), LONGITUDE -123.4074 (W).[22:40:00 GMT-08:00 07 JAN 2023] (▪▪▪) ▪▪▪-▪▪▪: RESPONDERS MAY NEED TO SEARCH AN AREA EXTENDING AT LEAST 20 METERS IN ALL DIRECTIONS FOR A 95% CHANCE OF FINDING THE USER.THE USERS ESTIMATED ALTITUDE (HAE) IS 354 METERS. RESPONDERS MAY NEED TO SEARCH 20 METERS ABOVE AND BELOW THIS LEVEL FOR A 95% CHANCE OF FINDING THE USER.THE USER HAS CACHED ENHANCED EMERGENCY DATA WITH APPLE. QUERY ADDITIONAL DATA!THE USERS DEVICE BATTERY STATE IS 61-100%. THEIR VERIFIED PHONE NUMBER IS +1▪▪▪▪▪▪▪▪▪▪.THE USER REQUESTS HELP WITH A FIRE EMERGENCY.[22:40:00 GMT-08:00 07 JAN 2023] (▪▪▪) ▪▪▪-▪▪▪▪: THIS REQUEST IS FOR ME.NO ONE IS ON FIRE.NO ONE IS TRAPPED.THE SPECIFIC EMERGENCY IS A OTHER FIRE. THE USER DESCRIBES THE SPECIFIC EMERGENCY AS FOLLOWS: CAMPER ROLLING SMOKE FIRE THE USERS IPHONE HAS ITS REGION SET TO UNITED STATES. THE USERS IPHONE HAS ITS DEFAULT LANGUAGE SET TO ENGLISH. TCC OR PSAP SYSTEMS MAY GARBLE THIS LANGUAGES SCRIPT. RETURN MESSAGES TO THE USER WILL NOT BE GARBLED. THIS CONCLUDES THE INITIAL DATA. TWO-WAY TEXT WITH THE USER IS NOW AVAILABLE.[22:41:00 GMT-08:00 07 JAN 2023] K▪▪▪ M▪▪▪▪▪▪ HAS ENTERED THE CHAT[22:41:00 GMT-08:00 07 JAN 2023] K▪▪▪ M▪▪▪▪▪▪: WHAT IS ON FIRE CALL INITIATED: 22:39:59 GMT-08:00 07 JAN 2023 PHONE NUMBER: (▪▪▪) ▪▪▪-▪▪▪▪
With the imminent demise of Google Analytics Universal in July 2023 I’ve been searching for an alternative and found an Open Source project from Plausible.io. Slight warning, this post is largely for myself to remember what I did to get this going so YMMV.
I host a few sites on Amazon Lightsail and while I found a few great posts discussing self-hosting of Plausible I found these setups perhaps a bit more complicated that I think it needed to be. For example, Lightsail has instances that include both a web server and Bitnami’s Let’s Encrypt SSL tool already installed so starting from an OS-only instance type requires some unnecessary configuration.
To get started quickly browse to the Amazon Lightsail console and under Apps + OS select the NodeJS instance using Debian (as of this writing Feb 2023). You could use and “OS Only” option but then you’d be left installing a number of packages vs. using this pre-built instance.
You’ll want to setup a static IP address for this instance for your DNS entry (see below). Next, SSH into your instance and create an “apps” folder under /opt/bitnami:
NOTE: I added DISABLE_REGISTRATION as I’m the only user who needs access.
I use Cloudflare for my CDN/DNS and I created an A NAME DNS-only entry pointing to analytics.<domain>.com which I use for Plausible.
Next, again following the self-hosting guide I started up the server using docker-compose:
$ sudo docker-compose up -d
The docs weren’t super clear about getting the first user created but browse to your URL and register the first user directly on the site. Following that I would recommend disabling registrations in the plausible-conf.env using:
Finally, setup your Apache virtual host config by copying the existing sample HTTPS configuration:
$ cd /opt/bitnami/apache/conf/vhosts
$ sudo cp sample-https-vhost.conf.disabled plausible-https-vhost.conf
Here’s my Apache vhost file for Plausible (using X-Robots-Tag to prevent crawling):
<VirtualHost 127.0.0.1:443 _default_:443>
ServerName analytics.<domain>.com
ServerAlias *
SSLEngine on
Header Set X-Robots-Tag "noindex, noarchive, nosnippet"
SSLCertificateFile "/opt/bitnami/apache/conf/analytics.<domain>.com.crt"
SSLCertificateKeyFile "/opt/bitnami/apache/conf/analytics.<domain>.com.key"
DocumentRoot /opt/bitnami/apps/plausible
# BEGIN: Configuration for letsencrypt
Include "/opt/bitnami/apps/letsencrypt/conf/httpd-prefix.conf"
# END: Configuration for letsencrypt
# BEGIN: Support domain renewal when using mod_proxy without Location
<IfModule mod_proxy.c>
ProxyPass /.well-known !
</IfModule>
# END: Support domain renewal when using mod_proxy without Location
<Directory "/opt/bitnami/apps/plausible">
Options -Indexes +FollowSymLinks -MultiViews
AllowOverride All
Require all granted
</Directory>
ProxyPass / http://localhost:8000/
ProxyPassReverse / http://localhost:8000/
# BEGIN: Support domain renewal when using mod_proxy within Location
<Location /.well-known>
<IfModule mod_proxy.c>
ProxyPass !
</IfModule>
</Location>
# END: Support domain renewal when using mod_proxy within Location
</VirtualHost>
Following this suggestion, in /opt/bitnami/apps/plausible I created a robots.txt file with the following:
User-agent: *
Disallow: /
I then updated the docker-compose.yaml adding a volumes mapping to this local file under the plausible service.
Lastly, restarted both Plausible and Apache and you should be well on your way to getting your Google Analytics alternative running.
$ sudo docker-compose down --remove-orphans && sudo docker-compose up -d
$ sudo /opt/bitnami/ctlscript.sh restart apache
All in all, the above took me less than a hour to get a working instance of Plausible.io up and running, self-hosted for $20/month on a 4GB Lightsail instance.
So far, I’ve been running this instance for 6 days and it looks pretty good. I’m getting a 500 error trying to import my old GA data so not quite sure what’s going on there but I did manage to get Google Search Console enabled but I’m not see where that data might show up. I’ve also setup email reporting and I’m curious to see what those look like.
Lastly, this project lives on its paid subscriptions to its cloud hosted version and assuming it works out I’ll be sure to use their sponsorship page.
I’ve worked with a lot of DOT type data and I have to say Massachusetts takes the cake for a seemingly unnecessarily complicated authentication process. The processes is documented on their /auth-token API.
This endpoint is available to all authorized users. The content of the response is the same for all user groups. The Bearer signature generation that uses this token is performed as follows.
MADOT
Ok, here is the six, yes six step process to authenticate MASSDOT APIs:
Step 1: Concatenate the user’s secret key with the token provided herein, separated by a colon. (‘SecretKey:token’)
Step 2: Create a SHA256 hash of the concatenated string. (i.e. SHA256(secretKey:token))
Step 3: Convert the generated hash to a hexadecimal string representation
Step 4: Concatenate the user’s username with the hexadecimal hash, separated by a colon. (‘username:hexadecimalHash’)
Step 5: Create the base-64 string representation of the concatenation. (Base64(‘username:hexadecimalHash’))
Step 6: The result is the signature required for Bearer type authorization. (Authorization Bearer ‘generated signature’)
Btw, I provided this gist to MASSDOT in the event they want to link/share for other developers.
I’ve been exploring the Apollo stack for developing with GraphQL and find the documentation a bit outdated so I decided to make some notes for myself and start collecting them here. The first thing I wanted to do is experiment with the apollo client codegen for TypeScript and understand how this tool works and leverage it for creating a TypeScript Apollo client. I started by using this Starwars sample Apollo server so I could focus on the client-side code gen which was quick and easy to stand up.
$ git clone https://github.com/apollographql/starwars-server.git
...
$ cd starwars-server
$ yarn && yarn start
yarn run v1.15.2
$ nodemon ./server.js --exec babel-node
[nodemon] 1.19.0
[nodemon] to restart at any time, enter `rs`
[nodemon] watching: *.*
[nodemon] starting `babel-node ./server.js`
🚀 Server ready at http://localhost:8080/graphql
🚀 Subscriptions ready at ws://localhost:8080/websocket
Next, I tested a simple GraphQL query to make sure the server is working by browsing here:
http://localhost:8080/graphql
I installed the Apollo CLI and started experimenting with codegen. Unfortunately, as of this writing the CLI documentation is outdated and refers to apollo-codegen and the parameters and configuration appear to have changed. To play with newer apollo CLI and client-side codegen I created a new “project” folder and just wanted to get some code generated without any other project dependencies/files etc. So, I created a folder to get started:
$ mkdir starwars-client
$ cd starwars-client
Next, I ran the apollo CLI to download the server’s schema with –endpoint parameter pointing to the running instance of the starwars-server sample:
$ ➜ starwars-client apollo client:download-schema --endpoint=http://localhost:8080/graphql
⚠️ It looks like there are 0 files associated with this Apollo Project. This may be because you don't have any files yet, or your includes/excludes fields are configured incorrectly, and Apollo can't find your files. For help configuring Apollo projects, see this guide: https://bit.ly/2ByILPj
✔ Loading Apollo Project
✔ Saving schema to schema.json
$ ls
schema.json
$
As you can see, this created a schema.json file containing details from my starwars-server. The next step is generating TypeScript code for a single GraphQL query using the downloaded schema. For good measure I’ll include a few of the issues I ran into along the way as I didn’t fine a lot on Google related to the various error messages.
➜ starwars-client apollo client:codegen
› Error: Missing required flag:
› --target TARGET Type of code generator to use (swift | typescript | flow | scala)
› See more help with --help
Ok, so I’m missing –target, that’s easy enough to add…
➜ starwars-client apollo client:codegen --target typescript
Error: No schema provider was created, because the project type was unable to be resolved from your config. Please add either a client or service config. For more information, please refer to https://bit.ly/2ByILPj
at Object.schemaProviderFromConfig (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/node_modules/apollo-language-server/lib/providers/schema/index.js:29:11)
at new GraphQLProject (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/node_modules/apollo-language-server/lib/project/base.js:31:40)
at new GraphQLClientProject (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/node_modules/apollo-language-server/lib/project/client.js:33:9)
at Generate.createService (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/lib/Command.js:114:28)
at Generate.init (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/lib/Command.js:37:14)
➜ starwars-client
Again, unfortunately the bitly short link provided by the tool points back to the outdated apollo-codegen documentation which is inaccurate. So I added –localSchemaFile pointing to my newly downloaded schema.json:
➜ starwars-client apollo client:codegen --localSchemaFile=schema.json --target=typescript
⚠️ It looks like there are 0 files associated with this Apollo Project. This may be because you don't have any files yet, or your includes/excludes fields are configured incorrectly, and Apollo can't find your files. For help configuring Apollo projects, see this guide: https://bit.ly/2ByILPj
✔ Loading Apollo Project
✖ Generating query files with 'typescript' target
→ No operations or fragments found to generate code for.
Error: No operations or fragments found to generate code for.
at write (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/lib/commands/client/codegen.js:61:39)
at Task.task (~/.nvm/versions/node/v10.15.3/lib/node_modules/apollo/lib/commands/client/codegen.js:86:46)
➜ starwars-client
What this error is actually saying is that the tool is expecting to find either .graphql or .ts files that have GraphQL “operations” aka queries, or mutations defined within my project folder which I haven’t created yet. Turns out there are a few options, 1) create .ts files with gql constants or 2) create a .graphql file(s) that contain named queries. I started with a simple query.graphql file for testing like this:
query {
heros(episode: NEWHOPE) {
name
}
}
I then ran the command again:
➜ starwars-client apollo client:codegen --localSchemaFile=schema.json --target=typescript
…and this yielded the same error as above because the CLI defaults to looking in ./src although you can change this using the –includes parameter. So I created the folder, moved the query.graphql file and re-ran the tool:
➜ starwars-client apollo client:codegen --localSchemaFile=schema.json --target=typescript
✔ Loading Apollo Project
✖ Generating query files with 'typescript' target
→ Apollo does not support anonymous operations
GraphQLError: Apollo does not support anonymous operations
Basically, this is telling me didn’t “name” the query so back to editing the query.graphql file and adding “heros”:
query heros {
hero(episode: NEWHOPE) {
name
}
}
Ok, now let’s try that again:
➜ starwars-client apollo client:codegen --localSchemaFile=schema.json --target=typescript
✔ Loading Apollo Project
✔ Generating query files with 'typescript' target - wrote 2 files
Success! I now have a few new folders and files added to my “project”:
In the above example I use command-line options although the apollo CLI supports a config file which looks like the following located in apollo.config.js which points to a remote schema from my starwars-server instance:
Here’s a simple example of calling the vSphere REST API using curl. These commands first authenticate to the API which creates a vmware-api-session-id cookie which is stored to cookie-jar.txt then makes a request to get a list of VMs:
I’m building a React Native application and recently updated to v0.31.0 and at first things were working well debugging on the device benefiting from a feature of the react-native-xcode.sh script. The script copies your Dev machine’s IP address to a text file called ip.txt which is used for establishing the connection to your machine from your device since localhost points to the wrong place. Here’s the line of code in ./node_modules/react-native/packager/react-native-xcode.sh:
In my previous post I wrote about the process that lead me to build a dashboard but first I want to talk a bit about the structure of the data in the Google Sheet where the whole process started. I first started by looking to quickly create a few charts to visualize some of our KPI‘s. To source the data I created a text file containing the SQL statements and used psql to fetch Postgres data which I dumped it to data into .CSV files for import into separate “data” only tabs in Google Sheets.
The first tab was the “primary” dataset which contained a wide (A to AX) set of columns with a blend of content from the various linked “data” tabs and is where I derived all of the pivot tables with a primary key in the first column and with this initial set of at I was able to start building charts to help visualize the data.
Of course, once you’ve answered one question it leads to follow-on questions which require more data leading to more questions. Before long I was querying a dozen tables from Postgres and MSSQL and importing the data into these “data” tabs. For data tabs with a 1-1 relationship based on primary key I would aggregate the data onto the main sheet with a formula like “Imported Data’!B4” or in cases where not all keys were present via a lookup like =IFERROR(VLOOKUP($A:$A,”Data Sheet”!$A:$E,3,FALSE),0) setting the result accordingly when the primary key wasn’t found.
Ultimately, flattening the data made it easy to construct pivot tables for aggregate totals, averages, counts, and median values etc. from which I could build a variety of charts a sampling of which I’ve included below.Here’s a small sample of the kinds of charts built from pivot tables. Yes, I’ve clipped/changed some of the legends knowingly obscuring the underlying meaning of the chart.
Here’s a small sample of the kinds of charts built from pivot tables. Yes, I’ve clipped/changed some of the legends knowingly obscuring the underlying meaning of the chart.
I built a variety of pivot tables for the Wanderful Marketing team (sans charts) for easy analysis of Cash Dash campaigns from a variety of angles such as by a given retailer by offer type, amount, reward, launch day of the week and a variety of campaign performance metrics that I’d calculated within the sheet. Ultimately, the usefulness of this data caught on and a number of teams were not only reviewing the data but asking for additional analysis and updates.
While I was able to automate some portions of updating this sheet, its associated tabs etc. Google Sheet’s charts and pivot tables don’t automatically expand as the size of your data grows which made it a laborious task to “re-scope” them as more data was added not to mention I knew the 2M cell limit was looming in the distance.
In a follow-on post I’ll talk about how I began the shift to automating this using R and a Shiny Dashboard running on an OSX Mac mini.
