caching configuration microcaching nginx SSI module web-server

SSI module : Date wise caching in Nginx

Hi everyone, today we are going to see how to implement date wise caching in Nginx using SSI module. There happen to be time when we want to refresh the cache as soon as new date comes. That is, we need such caching when we have our content as static but only for a specific date and it changes with new date.

For the date-wise caching, it doesn’t need actually a lot of work. You just need to change the fastcgi_cache_key and append date as well. For the date, we can use $date_local variable in nginx. But the problem comes as $date_local contains time as well, it is in non readable format, just numbers, (we can’t rewrite it).

SSI module comes for the rescue here. SSI module is a great implementation in nginx which processes SSI(Server Side Include) commands in the response to be sent. We can format the $date_local variable using this, to a readble form and even modify it for just the date.

Then we can use $date_local variable and append it with cache_key. Please follow below to see some codes of how to achieve it.

server {

ssi on;

location ~ \.php$ {

fastcgi_cache_key $your_key|$date_local;



Now, in somewhere in your view(response to be sent) html tag include below ssi command,

less than html greater than

less than!–# config timefmt=”%A, %d-%b-%Y” –greater than

less than/html greater than

Now, above command will be executed by Nginx before it is sent to client. It changes the $date_local default format to the desired format. And so your cache_key will be generated date-wise. As soon as, new date comes a new cache will be generated, and for the same date, the response from the cache will be served.

So now with the help of SSI module of Nginx, date wise caching can be easily done.
Read my article here for how to install nginx from source, which is needed to install third party module(SSI module) for Nginx.

configuration install modules nginx source ubuntu

Install Nginx from Source in Ubuntu

Hello Everyone, the very handy command to ubuntu users installing nginx, sudo apt-get install nginx, that’s it. It does install nginx on your machine, with almost all the modules usually needed by the users, super awesome. The shortcoming of this method of installing nginx is that if you want to add more modules to the nginx, you just can’t do it. Currently, nginx installed from apt-get do not support adding custom modules to it. Now when you look over internet about how to add module in nginx, it suggests you to install nginx from source. Some times it gets so much confusing, there is something, which always holds developer back to install it this way(As they already had an easy way).

So here I will show you that installing nginx from source is as easy as the apt-get(almost) and interesting as well. Lets do it,

1. Find the stable version of Nginx (, current stable version) compatible with your custom module you need to add(if the module doesn’t support all versions of nginx) from its download page. (tar file used here)

2. open terminal

3. sudo apt-get install build-essential libpcre3 libpcre3-dev libssl-dev (install the tools required to compile nginx from source)

4. sudo su (get the super user privilege).

5. mkdir nginx (create a directory named nginx{not necessarily}, all the work will be done into this directory)

6. cd nginx (get into nginx directory)

7. wget (download your compatible version of nginx)

8. tar -xzvf nginx-1.10.2.tar.gz(extract the downloaded content)

9. cd nginx-1.10.2 (get into nginx directory)

10. ./configure (run the configure file)

11. make & make install (google to know about them at your will, I got to work for that or just run them)

12. sudo /usr/local/nginx/sbin/nginx -s stop (stop the nginx server if already running)

13. sudo /usr/local/nginx/sbin/nginx (start the nginx server)

14. enter the ip of your server, and you must be able to see the default nginx page.

So, that’s it. You have now installed your nginx from source.
Now, the commands for starting and stopping and the locations of the config files are different than /etc/nginx. The nginx files are kept in /usr/local/nginx.

Configuration file: /usr/local/nginx/conf/nginx.conf
Start server : /usr/local/nginx/sbin/nginx
Stop server: /usr/local/nginx/sbin/nginx -s stop
Reload server : /usr/local/nginx/sbin/nginx -s reload
Other commands you can find by tabbing after -s or reading the /usr/local/nginx/sbin/nginx file.

Now you can add any module to your nginx, by compiling nginx with the module. Go ahead and learn and test different great available modules of nginx. One with which I’m currently fascinated with is rtmp module.

1. Each time you are adding a module, make sure you add all other modules(which you earlier had compiled with and still need them) as well.

2. Each time after the module is added, restart the nginx i.e., stop and start, rather than reload.

analytics chat chatting google google-analytics javascript live live-users long-polling nginx node.js performance persistent persistent-connection php5-fpm Proxy real-time response reverse-proxy socket socks tcp upstream web-server websocket websocket-handshake

How To Make Your Own Analytics Tool?

An analytics tool is a tool that you can use to get the information about how is your website performance, how are the users using it, what are the number of users at anytime(live users), live users for different urls, and other infos. One such example of the tool is the google analytics.

Analytics tool

Analytics tool gives a lot of information about your website with the nice looking graphs and all. In this blog, we will be discussing how we can make such analytics tool(digging the data).

Question 1: Why should we make such thing if it already exists?

Answer : One reason is that it is not free for always. The other reason is that the process of making it is very sexy and you learn technologies that you can use to make your own other real time apps like chatting app. Now that is more a valid reason.

Question 2: What are we talking about?

Answer : This is an example of a real time application. You see, you are tracking live users’ data. The data can be anything like total number of users anytime or number of users for different urls or different referral or different user agent or different visited ips, or anything. The other example of a real time application is a chatting application where a lot of users are communicating at the same time.

Question 3: What technologies are used for such an application?

Answer : So we need a continuous stream of response from the server about their performance as only servers know what is hitting them. It can only be achieved if there is some persistent connection between client and server so that server can continuously push data to the client. With persistent connection I would mean one for literally persistent connection(web sockets) or else timed persistent connection(long polling) or else chunk persistent connection(polling). By timed persistent connection, I mean persistent connection only for certain time interval after which it is closed and again opened. And by chunk persistent connection, I mean lots of request with no persistency, but the requests are so frequent that altogether they seem persistent(my bad).

Among all, I prefer web sockets, as I can’t logically satisfy myself why to use others and more of it that they are the outdated styles and only existed when sockets were not there.

So in this tutorial we will be using library with node.js to create web sockets. Below are the other libraries with other language which I found from here.

Analytics tool

And yes, we are going to use Nginx as a reverse proxy for web sockets. A very great tutorial regarding this can be found here. You can skip Nginx if you wish and directly test for your node.js server.

For Nginx configuration, as mentioned in tutorial,

server {
    location / {
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_http_version 1.1;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header Host $host;
        proxy_pass http://socket_nodes;

Proper explanation is given in that tutorial for how this will work for sockets. Now we setup our Node server(server.js), a very nice tutorial can be found here.

var data = {};
var http = require(“http”);
var url = require(‘url’);
var fs = require(‘fs’);
var io = require(‘‘);
var path;
var server = http.createServer(function(request, response){
        console.log(‘Request Accepted’);
        path = url.parse(request.url).pathname;
            case ‘/’:
                response.writeHead(200, {‘Content-Type’: ‘text/html’});
                response.write(‘hello world’);
            case ‘/live’:
                fs.readFile(__dirname + ‘/socket_io.html’, function(error, data){
                    if (error){
                        response.write(“opps this doesn’t exist – 404”);
                        response.writeHead(200, {“Content-Type”: “text/html”});
                        response.write(data, “utf8”);
                response.write(“opps this doesn’t exist – 404  –“+path);
 var listener = io.listen(server);
 listener.sockets.on(‘connection’, function(socket){
    console.log(‘Socket Made.’);
        socket.emit(‘showdata’, {‘data’: data});
    }, 1000);
 socket.on(‘disconnect’, function(){
    console.log(“Socket Closed.”);

Load on the client side in your socket_io.html which will be used to create event to create a persistent connection. (Please don’t bang your head for how would it find


     var socket = io.connect(); // your initialization code here.
     socket.on('showdata', function(data){

Now you can see all the data in your browser’s console. You can put this data at the right place of your analytics html. Now you can easily send continuous data from node server to your client.

Are you still wondering how would we gather data? Suppose we want to track number of live users, for that we will use a key “live” in data variable and initialize with 0. We will increment it as soon as there is a socket made and decrement it as soon as the socket is closed(Make sure io.connect() is called once and only once for a page load). So the data[‘live’] will determine the number of live users.

In server.js,

listener.sockets.on(‘connection’, function(socket){
    console.log(‘Socket Made.’);
    data[‘live’] +=1;
        socket.emit(‘showdata’, {‘data’: data});
    }, 1000);
 socket.on(‘disconnect’, function(){
    console.log(“Socket Closed.”);

As simple as that. It is just the logics in node to be done and you can achieve any data. Now for temporary data(by temporary I mean the machine hosting node server is until rebooted), we don’t need any extra storage.

If we want to use some durable data, or store some information, we can choose database of our choice and send data from node to database.

Now we are also using Nginx as a reverse proxy which is helpful in load handling and better scaling. We can extract other information like user ip, upstream responses(php), and other valuable information and send to node.

So yes, it is really interesting to make such tool, I told you so. You are surely going to stuck in somewhere or make it up or for any suggestion or for confusion, we can always discuss.

Great to see you people with your own analytics tool. 🙂

access-log aws elasticsearch elk filter grok grok-debugger gui input kibana log-format logging logrotate logstash monitoring nginx optimization output s3 webbrowser

ELK : Configure Elasticsearch, Logstash, Kibana to visualize and analyze the logs.

This is about how to configure elasticsearch, logstash, kibana together to visualize and analyze the logs. There are situations when you want to see whats happening on your server, so you switch on your access log. Of course you can tail -f from there or grep from that, but I tell you that it is real cumbersome to analyze the logs through that log file.

What if I told you there is a super cool tool, Kibana, which lets you analyze your logs, gives all kind of information in just clicks.   Kibana is a gui tool designed for the purpose to analyze the large log files which when used properly with logstash and elasticsearch(configure elasticsearch, logstash and kibana together) can be a boon for developers.

Now, logstash is a tool which is used to move logs from one file or storage(s3) to another. Elasticsearch is a search server which is used to store the logs in some format.

Now, here is the picture in short, Logstash will bring logs from s3, formatize them and send them to elasticsearch. Kibana will fetch logs from elasticsearch and show it to you. With that lets see the actual thing which matters, the code. I assume you everything installed, ELK, and s3 as the source of our logs(why?).

So first we configure our Logstash. There are mainly three blocks in logstash, input, filter, output. In input, we specify the source of the log file, in filter block, we format the logs the way we want it to be stored in elastic search, in output block we specify the destination for the output.

Code :

open up terminal

nano /etc/logstash/conf.d/logstash.conf

edit it for the following code,

input {

s3 {

bucket => “bucket_name_containing_logs”

credentials => [“ACCESS_KEY”, “SECRET_KEY”]

region_endpoint => “whichever_probably_us-east-1”

codec => json {

charset => “ISO-8859-1”




filter {

grok {

match => {“message” => “grok_pattern”}



output {

#stdout {

#codec =>json


elasticsearch_http {

host => “localhost”

port => “9200”

codec => json {

charset => “ISO-8859-1”




Explanation :

In input block, we specify that our log comes from s3. We provide necessary credentials to access the s3 bucket. We specify the charset for the input.

In filter block, we use grok tool to create custom fields in kibana by making proper pattern for the input logs. You can use grokdebugger to debug your pattern for a given input.

In output block, we specify the destination for output as elasticsearch, its address. We also specify the charset for the output.

You can uncomment the stdout block in output block to print data on to console.


We don’t need to change anything for elasticsearch configuration for now. Though if curious you can find it at /etc/elasticsearch/elasticsearch.yml . One thing which we should keep in mind that we need high configuration machine for this ELK system, otherwise, you might encounter different errors when elasticsearch gets full. One workaround that can be done for that whenever your elasticsearch is full, clear it out.

The following command will remove all index and bring elasticsearch to its initial state.

curl -XDELETE ‘ http://localhost:9200/_all/ ‘

You can read here to optimize elastic search for memory.


You don’t have to do much here in its configuration file, just make sure its listening to the correct port number. You can find its configuration file at /opt/kibana/config/kibana.yml

Now go ahead and enter the ip of the machine wherever the kibana is setup and port number or whatever url you specified in kibana.yml into the browser.

Now you can see something like thisconfigure elasticsearch

You can now explore a lot of things from here, visualize logs, compare fields. Go ahead check out different settings in kibana.

That’s it for now.

Welcome and do let me know when you configure elasticsearch, logstash, kibana combo pack.

Cheerio 🙂