Qlik Sense Enterprise on Windows deployed to AWS
In an Amazon Web Services (AWS) deployment, you install Qlik Sense Enterprise on an Amazon virtual private cloud infrastructure that is flexible, high performance, and quick to set up.
Deploying Qlik Sense Enterprise on AWS will enable you to quickly add new applications in a simple and scalable manner. You can do this with a basic knowledge of AWS security and scalability options but without the need to follow complex on-premise installation and configuration procedures. Using AWS will enable you to get your Qlik Sense infrastructure up and running in fraction of the time required for an on-premise deployment, and will enable you to scale your deployment quickly and easily, regardless of unexpected changes in demand.
You can deploy Qlik Sense to AWS manually, or you can use an Amazon Machine Image (AMI) available in the AWS Marketplace that includes Qlik Sense preinstalled. However, predefined images do not include a file share, so can only support single node Qlik Sense deployments.
Benefits of using AWS cloud
- A quick and effective way of deploying Qlik Sense to the cloud.
- Simple and cost-effective, reducing overall deployment times.
- Quick and easy to deploy Qlik Sense applications.
- Fewer hardware management overheads.
- Scalable, elastic storage that can be expanded and contracted on demand.
- Geographic deployment to multiple regions around the world makes lower latency possible.
- A reliable and high performance platform.
To successfully deploy Qlik Sense on AWS cloud you need a basic understanding of the architecture and services available in an AWS deployment. As part of a Qlik Sense deployment on AWS, you need the following components:
- An Amazon AWS account
- Amazon Management Console - available when you log in to your AWS account.
- VPC - Amazon Virtual Private Cloud
- EC2 - Amazon Elastic Cloud instance running on a VPC. Lets you scale your deployment by adding or removing servers as your requirements change.
You should also have a basic understanding of other AWS services that you can use for managing resources and as data stores for your Qlik Sense applications:
- RDS - Managed relational database service as an alternative to a PostgreSQL repository database. Provides high availability without the same complexity.
- S3 - Simple Storage Service. Scalable, object-based cloud storage.
- Dynamo DB - NoSQL database service
- Elastic IP - remapping of IP addresses
- EMR - Elastic MapReduce. Managed Hadoop service
- Redshift - Data warehouse
- Cloud formation - for managing resources automatically
For more information about AWS services, see the Amazon AWS website.
Microsoft Windows versions
Your AWS instance needs to be running a Microsoft operating system onto which you can install a Qlik Sense instance. Qlik Sense supports the following Windows operating systems for an AWS deployment:
- Microsoft Windows Server 2012 R2
- Microsoft Windows Server 2016
- Microsoft Windows Server 2019
- Microsoft Windows Server 2022
Qlik Sense Enterprise
Install a single-node Qlik Sense server on your EC2 instance.
Qlik Sense Enterprise configuration:
Use the QMC to configure the following:
- Tokens (only token-based license)
- User access (token-based license) or Professional access (user-based license)
- CPU cores
- Security groups
Create a proxy setup for allowing HTTP access.
When you deploy Qlik Sense to AWS for the first time you should also consider the following.
To configure security on an AWS deployment you need a good understanding of how to set up AWS security groups, key pairs, and also security groups in Qlik Sense. You use the Amazon Management Console to configure AWS security and the QMC to configure all security and authentication settings in Qlik Sense Server.
For more information about security, see AWS and Azure security, and for more on Qlik Sense security, see Qlik Sense Enterprise on Windows security
AWS web services that you can use as data stores for Qlik Sense applications to retrieve data from when building applications:
- Amazon DynamoDB – NoSQL database
- Amazon RDS – managed relational database service
- Amazon Redshift – data warehouse as a service
- Amazon Simple Storage Service (S3) – scalable, object-based cloud storage
- AWS Elastic Map Reduce (EMR) – managed Hadoop service
In an AWS deployment you can use the following connectivity mechanisms to connect to different data sources:
- ODBC connection
- OLE DB connection
- REST API connection
- Native connector to a specific source
- Qlik Sense instance that uses both data stored in Amazon RDS and Amazon Redshift.
- Qlik Sense instance that uses data coming from an AWS data source as well as a combination between flat files and web based data sources (i.e. a web service data feed).
- Hybrid Qlik Sense instance - uses data stored in AWS data sources as well as data stored on premise.
For more information about connectivity, see Connecting to data sources.
As environments grow in terms of number of users, number and size of applications, and number of data sources it is important to understand how to size the environment correctly and how to scale the environment accordingly. You need to create a multi-node environment to effectively scale up or down, by creating dedicated servers for different purposes. You can then allocate resources correctly across the following Qlik Sense services.
- Engine Service – The QIX engine, provides in-memory Associative Data Indexing and calculation supporting analysis
- Proxy Service – Manages authentication, handles user sessions and load balancing
- Repository Service –Manages Qlik Sense applications, controls access, and handles configuration
- Scheduling Service – Manages reloads of Qlik Sense applications and other scheduled tasks
- Service Dispatcher – Launch and manage the data profiling service for the data load model
For more information about scalability, see the Qlik Sense Performance Benchmark technical brief.