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This is the fifth blog in our series helping you understand all about cloud, when you are in a dilemma to choose Azure or AWS or both, if needed.
Before we jumpstart on the actual comparison chart of Azure and AWS, we would like to bring you some basics on data analytics and the current trends on the subject.
If you would rather like to have quick look at the comparison table, Click here
This blog is intended to help you strategize your data analytics initiatives so that you can make the most informed decision possible by analyzing all the data you need in real time. Furthermore, we also will help you draw comparisons between Azure and AWS, the two leaders in cloud, and their capabilities in Big Data and Analytics as published in a handout released by Microsoft.
Beyond doubts, this is an era of data. Every touch point of your business generates volumes of data and these data cannot be simply whisked away, cast aside as valuable business insights can be unearthed with a little effort. Here’s where your Data Analytics infrastructure helps.
A 2017 Planning Guide for Data and Analytics published by Gartner written by the Analyst John Hagerty states that
The Key Findings as per the report are as follows:
Data and analytics must drive modern business operations, not just reflect them. Technical professionals must holistically manage an end-to-end data and analytics architecture to acquire, organize, analyze and deliver insights to support that goal.
Analytics are now infused in places where they never existed before.
Executives will seek strategies to better manage and monetize data for internal and external business ecosystems.
Data gravity is rapidly shifting to the cloud, with IoT, data providers and cloud-native applications leading the way. It is no longer a question of “if” for using cloud for data and analytics; it’s “how.”
The last point emphasizes on how cloud is playing a prominent role when it comes to Data Analytics and if you have thoughts on who and how, Gartner in its latest magic quadrant has said that AWS and Azure are the top leaders. Now, if you are in doubt whether to go the Azure way or AWS or should it be the both, here’s the comparison table showing their respective Big Data and Analytics Capabilities
Elastic data warehouse
A fully managed data warehouse that analyzes data using business intelligence tools.
Before we jumpstart on the actual comparison chart of Azure and AWS, we would like to bring you some basics on the database aspect of cloud strategy.
If you would rather like to have quick look at the database comparison table, click here
Through this blog, let’s understand the database aspect of your cloud strategy. As per the guide, Database services refers to options for storing data, whether it’s a managed relational SQL database that’s globally distributed or a multi-model NoSQL database designed for any scale.
When you decide cloud, one of the critical decisions you face is which database to use – SQL or NoSQL. Though SQL has an impressive track record, NoSQL is not far behind as it is gradually making notable gains and has many proponents. Once you have picked your database, the other big decision to make is which cloud vendor to choose amongst the many vendors.
Here’s where you consider Gartner’s prediction; the research company published a document that states
“Public cloud services, such as Amazon Web Services (AWS), Microsoft Azure and IBM Cloud, are innovation juggernauts that offer highly operating-cost-competitive alternatives to traditional, on-premises hosting environments.
Cloud databases are now essential for emerging digital business use cases, next-generation applications and initiatives such as IoT. Gartner recommends that enterprises make cloud databases the preferred deployment model for all new business processes, workloads, and applications. As such, architects and tech professionals should start building a cloud-first data strategy now, if they haven’t done so already”
Reinstating the trend, recently Gartner has published a new magic quadrant for infrastructure-as-a-service (IaaS) that – surprising nobody – has Amazon Web Services and Microsoft alone in the leader’s quadrant and a few others thought outside of the box.
Now, the question really is, Azure or AWS for your cloud data? Or should it be both? Here’s a quick comparison table to guide you.
SQL Database is a high-performance, reliable, and secure database you can use to build data-driven applications and websites, without needing to manage infrastructure.
In line with our latest blog series highlighting how common cloud services are made available via Azure and Amazon Web Services (AWS), as published by Microsoft, this third blog in the series helps you understand Cloud Networking and Content Delivery capabilities of both Azure and AWS.
Before we jumpstart on the actual comparison chart of Azure and AWS, we would like to bring you some basics on cloud content delivery networking and the current trends on the subject.
If you would rather like to have quick look at the comparison table, click here
When we talk about cloud Content Delivery Network (CDN) and the related networking capabilities it includes all the hardware and software that allows you to easily provision private networks, connect your cloud application to your on-premises datacenters, and more.
According to Gartner, Content delivery networks (CDNs) are a type of distributed computing infrastructure, where devices (servers or appliances) reside in multiple points of presence on multi-hop packet-routing networks, such as the Internet, or on private WANs. A CDN can be used to distribute rich media downloads or streams, deliver software packages and updates, and provide services such as global load balancing, Secure Sockets Layer acceleration and dynamic application acceleration via WAN optimization techniques.
In simpler terms, this highly distributed server platforms are optimized to deliver content in a way that improves customer experience. Hence, it is important to decrease latency by keeping the data closer to the users, protect it from security threats while ensuring rapid streamlined content delivery including general web delivery, content purge, content caching and tracking history as long as 90 days.
As per G2Crowd.com, most organizations use CDN services, such as web caching, request routing, and server-load balancing, to reduce load times and improve website performance. Further to qualify as a CDN provider, a service provider must:
Allow access to a geographically dispersed network of PoPs in multiple data centers
Help websites access this network to deliver content to website visitors
Offer services designed to improve website performance
Provide scalable Internet bandwidth allowances according to customer needs
Maintain data center(s) of servers to reduce the possibility of overloading individual instances
With this background, let’s look at the AWS vs Azure comparison chart in terms of Networking and Content Delivery Capabilities:
Cloud virtual networking
Provides an isolated, private environment in the cloud.
Install and Run SQL Server Docker Container on Mac
Like most people, I use Mac , Windows as well Linux OS for development and testing purposes. Primarily I use Mac for Development purpose. I have few projects which uses SQL Server as Data Storage Layer. Setting up Docker Container on Mac and Opening up the ports was pretty easy and doesn’t take more than 10 Minutes.
Steps followed :
Pull SQL Server Docker Image
Run SQL Server Docker Image
Install mssql Client
Open the Ports to connect to SQL Server from the network
Setup port forwarding to enable access outside the network
Open Up the Firewall to connect to SQL Server from outside the Host
Ensure your firewall is configured to allow the connections to the SQL Server. I turned of “Block all incoming connections” and enabled “Automatically allow downloaded signed software to receive incoming connections”. Without proper firewall configurations, you won’t be able to connect to the SQL Server outside the host.
Connecting from the Internet ( Port forwarding Setup )
Lets say you want to connect to the SQL Server you setup from outside the network or from anywhere via internet,you can setup port forwarding.
Get your public facing IP and setup the port forwarding for Port 1433 ( SQL Server port you have setup your docker container ). If its setup correctly , you should be able to telnet into that port to verify the connectivity.
telnet 188.8.131.52 1433
Unless you absolutely require it , its very bad idea to expose the SQL Server to internet. It should be behind the network , only your webserver should be accessible via internet.
While launching docker container , if you get the error saying that it doesn’t have enough memory to launch SQL Server Container, go ahead and modify the memory allocation for docker container.
At least 3.25 GB of RAM. Make sure to assign enough memory to the Docker VM if you’re running on Docker for Mac or Windows.
I have setup this way.
If you don’t provision enough memory, you will error like this.
Look into Docker logs
Following command ( docker ps -a and docker logs mcsqlserver ) shows list of running processes and docker logs.
$ docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
9ea3a24563f9 microsoft/mssql-server-linux:2017-latest "/bin/sh -c /opt/m..." About an hour ago Up About an hour 0.0.0.0:1433->1433/tcp macsqlserver
$ docker logs macsqlserver
2017-10-08 23:06:52.29 Server Setup step is copying system data file
'C:\templatedata\master.mdf' to '/var/opt/mssql/data/master.mdf'.
2017-10-08 23:06:52.36 Server Setup step is copying system data file
'C:\templatedata\mastlog.ldf' to '/var/opt/mssql/data/mastlog.ldf'.
2017-10-08 23:06:52.36 Server Setup step is copying system data file
'C:\templatedata\model.mdf' to '/var/opt/mssql/data/model.mdf'.
2017-10-08 23:06:52.38 Server Setup step is copying system data file
'C:\templatedata\modellog.ldf' to '/var/opt/mssql/data/modellog.ldf'.
I highly recommend to create least privileged accounts and disable SA login. If you are exposing your SQL Server to internet, there are ton of hacking and pentest tools which uses sa login for brute force attack.
Azure or AWS or Azure & AWS? What’s your cloud strategy for Storage?
This is our second blog, in our latest blog series helping you understand all about cloud, especially when you are in doubt whether to go Azure or AWS or both.
To read our first blog talking about Cloud strategy in general and Compute in particular, click here…
Moving on, in this blog let’s find what Azure or AWS offer when it comes to Storage Capabilities for your Cloud Infrastructure.
Globally CIOs are increasingly looking to cease running their own data centers and move to cloud which is evident when we read the projection made by a leading researcher, MarketsandMarkets. They had reported that the global cloud storage business sector to grow from $18.87 billion in 2015 to $65.41 billion by 2020, at a compound annual growth rate (CAGR) of 28.2 percent during the forecast period.
Reinstating the fact, 451 Research’s Voice of the Enterprise survey last year stated that Public cloud storage spending will double by next year (2017). “IT managers are recognizing the need for storage transformation to meet the realities of the new digital economy, especially in terms of improved efficiency and agility in the face of relentless data growth,” said Simon Robinson, research vice president at 451 and research director of the new Voice of the Enterprise: Storage service. “It’s clear from our Q4 study that emerging options, especially public cloud storage and all-flash array technologies, will be increasingly important components in this transformation” he added further.
As we see, many companies are in for Cloud Storage, undoubtedly. But the big question – Whom to choose from a gamut of leading public cloud players including big players like AZURE, AWS; Should it be AZURE alone for your cloud storage or AWS or a combination of both still prevails.
This needs a thorough understanding. To help you decide for good, we have decided to re-produce a guide, published by Microsoft that briefs Azure‘s capabilities in comparison to AWS when it comes to Cloud Strategy. And we will see the Storage part in this blog, but before, that a little backgrounder on Cloud Storage.
When we talk about cloud storage device mechanisms, we include all logical units of data storage covering from files, blocks, and datasets to objects and their relative storage interfaces. These instances of virtual storage devices are designed specifically for cloud-based provisioning and can be scaled as per need. It is to be noted that different cloud service consumers utilize different technologies to interface with virtualized cloud storage devices.
Object storage service for use cases including cloud apps,
content distribution, backup, archiving, disaster recovery,
and big data analytics.
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