Azure Synapse: The Ultimate Cloud-Based Analytics Solution for Data-Driven Organizations

As data becomes more and more critical to business success, organizations need powerful tools to process, manage, and analyze large volumes of data from various sources. This is where Azure Synapse comes in – a cloud-based analytics solution that enables organizations to derive insights from their data in real-time. In this blog post, we will explore what Azure Synapse is, how it works, and how it can benefit your organization.

What is Azure Synapse? Azure Synapse is a cloud-based analytics service that combines data warehousing and big data analytics into a single solution. It allows organizations to ingest, prepare, and manage large amounts of data from various sources, including structured, semi-structured, and unstructured data. With Azure Synapse, organizations can process data in real-time or batch mode and then analyze it using various tools and languages.

How does Azure Synapse work? Azure Synapse is built on top of Azure Data Lake Storage Gen2 and Azure SQL Data Warehouse. It provides a unified experience for data ingestion, data preparation, and data analysis. Here is an overview of how Azure Synapse works:

Data Ingestion: Azure Synapse allows organizations to ingest data from various sources, including Azure Blob Storage, Azure Data Lake Storage Gen2, and Azure Event Hubs. It also supports a wide range of data formats, including structured data from databases, semi-structured data from sources such as JSON or XML files, and unstructured data such as text, images, and videos.

Data Preparation: After ingesting data, organizations can prepare it for analysis using various tools such as Apache Spark, SQL Server, or Power Query. Azure Synapse provides a data preparation experience that allows users to clean, transform, and join data using a familiar SQL or Python-based language.

Data Analysis: Once the data is prepared, organizations can analyze it using various tools and languages, including Azure Machine Learning, R, Python, and Power BI. Azure Synapse integrates with these tools, making it easy to build end-to-end data pipelines that can handle large-scale data processing and analytics workloads.

Security: Azure Synapse provides advanced security features, including data encryption at rest and in transit, role-based access control, and auditing and compliance tools. These features help organizations maintain data privacy and security, which is critical in today’s data-driven world.

Benefits of Azure Synapse: Azure Synapse provides several benefits to organizations, including:

  1. Scalability: With Azure Synapse, organizations can easily scale their analytics workloads to handle large volumes of data. They can pay only for the resources they need, making it a cost-effective solution.
  2. Integration: Azure Synapse integrates with other Azure services such as Azure Data Factory, Azure Machine Learning, and Power BI, allowing organizations to build end-to-end data pipelines.
  3. Real-time analytics: Azure Synapse allows organizations to perform real-time analytics on streaming data, enabling them to make decisions based on the most up-to-date information.
  4. Simplified data management: Azure Synapse provides a unified experience for data ingestion, preparation, and analysis, simplifying the data management process for organizations.

RBAC in AZURE and how to consulting the configuration

RBAC (Roled based access control) is a security feature used to control access based on user roles in an organization, that is, considering its functions within the organization. In large organizations is a classic way to organize permits, based on the competences, authority and responsibility of a job.

A RBAC attribute is the dynamism, because the access control function is given to a role and integration in that role of a person can change over time, like the permissions associated with a role. It is opposed to classical methods of access where access permissions are granted or revoked to a user object to object.

In AZURE we have a RBAC implementation for resources and a number of predefined roles. The roles in AZURE can be assigned to users, groups, and applications, and at the level of subscriptions, resource groups, or resources. As we see the options are vast.


There are three basic roles: owner, contributor or partner, and reader. The owner has full access to resources, including permissions to delegate access to others. The contributor is equal to the owner but can not grant access to others. The reader can only see resources.

Of these three roles inherit another set of roles for specific resources. In this link is a full list of roles based on Azure and its functions.

However you can generate as many roles with custom permissions as necessary. To create them can be done via Azure PowerShell, Azure client line interface (CLI), or the API REST. In this link you have more information and examples of how to do it.

Access to the list of permissions for each role

One way to check what permissions each role have, is through the portal AZURE. You enter into a subscription, resource group or resource, and you will see an icon like two peoples at the top right:


Selecting it, the users panel appears. Click Role:


And the list of available roles will appear:


Select the role that interests you to check their permissions, and the Members Role tab appears with a button to see the list of permissions:

20160524_RBAC_AZURE_Paso05Once on the list we can expand information for each group of actions by clicking on the corresponding entry:


And within it each individual action:


At this level is useful the information that provides the icon to learn more on each input with an explanation of each share representing:


To learn more about how to create, delete or consult the members of each roles, you can consult the following link.

Load balancing two Azure WebAPP with nginx

In the previous post we saw how to install a ngin-x server. One of the capabilities that have ngin-x is to be a powerful proxy server, used as a load balancer. In this post we will see how to use it to balance the load of two WebAPPs (could be as many as were necessary). This scenario presents a feature that requires slightly modify the normal procedure for this operation.

We start from a linux machine with NGIN-x installed, as seen in the previous post.

In addition we will create two simple WebAPPs, with a message that differentiates each of them, for example, as shown in the following images:



Then we will set up ngin-x following the normal guidelines. We entered the linux server console and edit the configuration file with nano for example:

sudo nano /etc/nginx/nginx.conf

And modify the script so it looks like the following code:

user www-data;
worker_processes auto;
pid /run/;

events {
     worker_connections 768;
     # multi_accept on;

http {
     upstream bloqueprimerproxy {

     server {
          listen 80;
          server_name   localhost;

          location / {
               proxy_pass http://bloqueprimerproxy;
               proxy_set_header  X-Real-IP  $remote_addr;

Where and are the URLs of the two WebAPPs to balance.

We save the code and restart the NGIN-x service:

sudo service nginx restart

The above script would be the normal way to balance two WEBs with ngin-x. But if we tried now we get the following error:


This is because Azure App Service uses cookies to ARR (Application Request Routing). You need to ensure that the proxy passes the header correctly to the WebAPP so that it identifies the request correctly.

For this we edit again the configuration file and leave it as follows:

user www-data;
worker_processes auto;
pid /run/;

events {
     worker_connections 768;
     # multi_accept on;

http {
     upstream bloqueprimerproxy {
         server localhost:8001;
         server localhost:8002;

     upstream servidor1 {

     upstream servidor2 {

     server {
          listen 80;
          server_name   localhost;

          location / {
               proxy_pass http://bloqueprimerproxy;
               proxy_set_header    X-Real-IP    $remote_addr;

     server {
          listen 8001;
          server_name   servidor1;

          location / {
               proxy_set_header Host;
               proxy_pass http://servidor1;

     server {
          listen 8002;
          server_name   servidor2;

          location / {
               proxy_set_header Host;
               proxy_pass http://servidor2;

Where as before and are the URLs of the two webapps to balance.

In this script we apply a double proxy, so that we balance the input against the same ngin-x, attacking the ports 8001 and 8002, which headed to the webapps, but adding to the header the real WebAPP url.

After recording the script and restart the ngin-x service, if we navigate to the ngin-x server, we see that we are balanced from one to another web without problem.

To learn more about balancing modes available on ngin-x you can see this link.


Installing Nginx on an Azure Linux Ubuntu 16.04 VM

In this post we will see how to install nginx on a Ubuntu Linux 16.04 LTS virtual machine on Azure. This is one of the best HTTP servers and reverse proxy, and also an IMAP/POP3 proxy. It is open source.

Let’s assume that we have deployed the Linux virtual machine on a basic state. Otherwise, as summary, the steps are:

– Create a virtual machine from the gallery with Ubuntu 16.04. You can see my post about creating Linux VM.
– Change the default ssh port. You have instructions to do it in Azure in my post about it.
– Upgrading the system, connecting to a console session and running:

sudo apt-get update
sudo apt-get upgrade

This step is always recommended before installing a package (except production servers with previous production packages, that you have to consider whether or not it is convenient).

As we will install an HTTP server, if you have got a previous http server like Apache, you have to uninstall it to prevent conflicts.

Once the machine is ready to install nginx, from the ssh console run:

sudo apt-get install nginx

And finally we start the nginx service with:

sudo systemctl start nginx

Check that the service is active with:

sudo service nginx status

It provides service information that will be similar to the following screen:


Now, we have installed nginx, with its default settings to port 80. If we go to the machine, trhought that port, the next page appears:


For more information about nginx you can find it on this link.

Changing SSH and XRDP ports in a Azure Linux virtual machine


A basic safety recommendation is to change the default connection ports of a system for the various available communications services. Let’s see how to change the ssh and xrdp ports on a Azure Linux virtual machine.

Change ssh port

Immediately after creating the virtual machine, the default port is 22. You can connect to the machine through its public IP or DNS with a client like Putty through that port. Edit the configuration file with nano for example:

sudo nano /etc/ssh/sshd_config

And we change where it says port 22 by the value we want (eg I put 40167):


Now to restart the ssh service, run:

sudo service ssh restart

We close the remote session that we are running, that still go through the port 22. Now we need to edit the security rule in the control panel of the virtual machine to reflect the change in port. To do this, we look for the machine in our Azure subscription, for example, in my case it is called f23uh4733:


Click on the entry safety rules option:


And we double click on the current rule for port 22:


And you must modify the value of the port 22 to port defined in the configuration file:


Pressing save after modification. The rule will take a few seconds to be applied.

Installing a remote desktop and xrdp port change

Now we will install a remote desktop. This will be necessary if Linux is a server image for example. Keep in mind that xrdp since Ubuntu 12.04LTS does not support Gnome Desktop, so we’ll use xfce.

First we install xrdp, executing the following command at the terminal:

sudo apt-get install xrdp


After the installation of xrdp, we must install xfce, running the command:

sudo apt-get install xfce4


The next step is to configure xrdp to use xfce. Run the following command:

echo xfce4-session >~/.xsession


Once installed the desktop, we will change the default port for remote connection. We use an editor, for example nano, to modify the xrdp configuration file. Run the command:

sudo nano /etc/xrdp/xrdp.ini

And modify the port with the desired value, in this case for example the port 40168:


We record the changes and restart the xrdp service to take effect, using the following command:

sudo service xrdp restart


Once you have configured the port, as before, we need to create the security rule that allows us to access. To do this we return to the list of rules of entry, and click the add button:


And we add a rule indicating the destination port that we have set in the previous step:


Press save button and wait for the rule to apply. After, we can open a remote desktop connection to the machine by the port:


We have to identify us with a UNIX user. If you have not created any, the administrator user serve us:


And we access the Linux desktop machine:



Azure VM’s public direction

Each virtual machine we deploy in Azure, by default, has assigned a public IP, through which we can access it. You can later modify both access ports as restrict, in certain cases, public access.

IP and DNS of a virtual machine

To access the public IP of a virtual machine created in ARM model, open the panel of the machine from the list of virtual machines:


In the main panel the public IP appears, and if it was configured, your DNS. If the DNS appears undefined, you can specify one by clicking on the link:


In the Public IP panel, we can see the address and easily copy both IP and DNS.


If you click Settings, you will access to specific IP options. We can establish a static IP to the virtual machine (default is dynamic) and define a DNS domain within our geographic region domain:


Una vez guardados los cambios, en segundos que se habían aplicado y estarán a disposición del público.



Creating a Linux VM in Azure

Within the Azure marketplace we have multiple images ready to deploy. Among them are several distributions of Linux created by several companies, with several preinstalled packages if necessary.

Creating a Linux virtual machine

Let’s see the entire process of provisioning a virtual machine (IaaS) with an image of Canonical Ubuntu Server 15.10.

Step 1

We entered our Azure subscription and click on virtual machines:


Step 2

Click on add new virtual machine:


Step 3

We search and select the image Ubuntu Ubuntu Server 15.10 Canonical:


Step 4

The description of the VM image is showed, and we can choose whether we want in classic mode or resource manager. We will choose resource manager. You can see the differences on this link. Press create to start the process of provision:


Step 5

Now, you can fill the basic data of the virtual machine, with special attention to the geographical area of deployment and the resource group to which to assign. Select the location closest to where you want to give the service or one where you have all your virtual data center.

With regard to the resource group, remember that everything you bring inside will not restart simultaneously in the mantenimience operations, so its use is for high availability situations.

In this step you will define the root user and password, so please assure that the data is correct.

After filling all press accept.


Step 6

You must now select the size, which defines the cost of the machine. Choose the one you needed depending on the estimated use. The DS series, with SSDs are suitable for LAMP services for example.


Step 7

In this step you will configure additional options, such as network, storage type and others. When you finish, please press accept. If you do not yet know these concepts in Azure, the default options will be fine to start.


Step 8

A summary of the process is presented and a final confirmation is requested. If all is well, press accept and begin to supply the machine. If not, you can go back to correct it.

Creación VM Ubuntu

In the notification area you will have a notice of the process progress, as well in the main panel.

Once the deployment is complete, which may take about 5 to 10 minutes, you can connect via SSH with a client like Putty, using the public IP of the machine and against port 22, with root user that was defined in the basic options in step 5.

However this default setting is not the safest. In a next post we will see how to change the default ports and install a desktop for remote access. Later we will see how to configure the server to make a LAMP stack.