July 2021 - Indium

Successful, thriving businesses rely on sound intelligence. As their decisions become increasingly driven by data, it is essential for all gathered data to reach the right destination for analytics. A high-performing cloud data warehouse is indeed the right destination.

Data warehouses form the basis of a data analytics program. They help enhance speed and efficiency of accessing various data sets, thereby making it easier for executives and decision-makers to derive insights that will guide their decision-making.

In addition, data warehouse platforms enable business leaders to rapidly access historical activities carried out by an organization and assess those that were successful or unsuccessful. This allows them to tweak their strategies to help reduce costs, improve sales, maximize efficiency and more.

AWS Redshift and Snowflake are among the powerful data warehouses which offer key options when it comes to managing data. The two have revolutionized quality, speed, and volume of business insights. Both are big data analytics databases capable of reading and analyzing large volumes of data. They also boast of similar performance characteristics and structured query language (SQL) operations, albeit with a few caveats.

Here we compare the two and outline the key considerations for businesses while choosing a data warehouse. (Remember, it is not so much about which one is superior, but about identifying the right solution, based on a data strategy.)

AWS Redshift

It offers lightning-quick performance along with scalable data processing without having to invest big in the infrastructure. In addition, it offers access to a wide range of data analytics tools, features pertaining to compliance and artificial intelligence (AI) and machine learning (ML) applications. It enables users to query and merge structured and semi-structured data across a data warehouse, data lake using traditional SQL and an operational database.

Redshift, though, varies from traditional data warehouses in several key areas. Its architecture has made it one of the powerful cloud data warehousing solutions. Agility and efficiency offered by Redshift is also not possible with any other type of data warehouse or infrastructure.

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Essential and key features of Redshift

Several of Redshift’s architectural features help it stand out.

Column-oriented databases

Data can be organized into rows or columns and is dictated by the nature of the workload.

Redshift is a column-oriented database, enabling it to accomplish large data processing tasks quickly.

Parallel processing

It is a distributed design approach with several processors employing a divide-and-conquer strategy to massive data tasks. Those are organized into smaller tasks which are distributed amongst a cluster of compute nodes. They complete the computations simultaneously rather than in a sequential manner. The result is a massive reduction in the duration of time Redshift requires to accomplish a single, mammoth task.

Data encryption

No organization or business is exempt from security and data privacy regulations. One of the pillars of data protection is encryption, which is particularly true in terms of compliance with laws such as GDPR, California Privacy Act, HIPAA and others.

Redshift boasts of robust and customizable encryption options, giving users the flexibility to configure the encryption standards that best suits their requirements.

Concurrency limits

It determines the maximum number of clusters or nodes that can be provisioned at a given time.

Redshift preserves concurrency limits similar to other data warehousing solutions, albeit with flexibility. It also configures region-based limits instead of applying one limit to all users.

Snowflake

It is one of prominent tools for companies that are looking to upgrade to a modern data architecture. It offers a more nuanced approach in comparison to Redshift, which comprehensively addresses security and compliance.

Cloud-agnostic

Snowflake is cloud-agnostic and a managed data warehousing solution available on all three cloud providers: Amazon Web Services (AWS), Azure and GCP. Organizations can seamlessly fit Snowflake into the existing cloud architecture and be able to deploy in regions that best suit their business.

Scalability

Snowflake has a multi-cluster shared data architecture, which allows it to separate out compute and storage resources. This feature helps users with the ability to scale up their resources when they require large data volumes to load faster and scale down once the process is complete.

To help with minimal administration, auto-scaling and auto-suspend features have been implemented by Snowflake.

Virtual-zero administration

Delivered as a Data Warehouse-as-a-Service, Snowflake enables companies to set up and manage the solution without needing significant involvement from the IT teams.

Semi-structured data

The Snowflake architecture enables the storage of structured and semi-structured data in the same destination with the help of a schema on a read data type known as Variant, which can store structure and semi-structured data.

Redshift vs Snowflake: which is right for you?

Features: Redshift bundles storage and compute to offer instant potential to scale to enterprise-level data warehouse. Snowflake, on the other hand, splits computation and storage and provides tiered editions. It thus offers businesses flexibility to buy only the required features while maintaining scaling potential.

JSON: In terms of JSON storage, Snowflake’s support is clearly the more robust. Snowflake enables to store and query JSON with built-in and native functions. On the flip side, when JSON’s loaded into Redshift, it splits into strings – making it challenging to query and work with.

Security: While Redshift consists of a set of customizable encryption options, Snowflake offers compliance and security features geared to specific editions. It thus provides a level of protection most suitable for an enterprise’s data strategy.

Data tasks: A more hands-on maintenance is necessary with Redshift, particularly for those tasks that cannot be automated, like compression and data vacuuming. Snowflake has a benefit here: it automates many of such issues, helping save substantial time in diagnosis and resolving of those issues.

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Final thoughts

Whether it is Redshift or Snowflake, when it comes to business intelligence (BI), both are very good options as cloud data warehouses. Irrespective of the choice of data warehouse, getting all the data to the destination as quickly as possible is essential to provide the background required for sound BI.

In the years gone by, managing the IT infrastructure was a challenging, or even a hard, job. For example, all the hardware and software essential for the applications to run had to be manually configured and managed by system administrators. Servers would be put in place physically before being configured. And only when the machines had been configured correctly, would the application be deployed. Unsurprisingly, a slew of problems ensued the manual process.

That scenario has, however, transformed lately.

Trends such as cloud computing have helped revolutionize and enhance the way enterprises design, manage, and maintain their IT infrastructure. It has freed companies from building and maintaining their data centers, not to mention reduce the high costs typically associated with them. Cloud computing has also helped improve the speed of setting up infrastructure needs and thus resolve issues such as availability and scalability.

Infrastructure as a Code is also one of the trends that has been critical in sprucing up organizations’ IT infrastructure, helping meet organizational goals and gain a competitive edge in the market.

A well-implemented IT infrastructure helps organizations in several ways, including:

Build and launch applications to the market with speed
Collect data in real-time to make timely decisions
Improve employee productivity
Offer positive customer experience by ensuring uninterrupted access to website, online store and other resources

What is Infrastructure as a Code (IaC)?

It is an IT practice which codifies and manages any IT infrastructure as software. The purpose of IaC is to help operations or developer teams to automatically monitor, provision and manage resources instead of manually organizing discrete operating systems and hardware devices.

The concept of IaC is similar to programming scripts which help automate IT processes. It, however, has one key difference: it uses descriptive or high-level language to code versatile, adaptive provisioning and deployment processes.

How does Infrastructure as a Code work?

The IaC tools can differ in terms of the details of how they work, but they can be fundamentally divided into two types: those following the imperative approach and those that follow the declarative approach.

As the name suggests, the imperative approach provides orders and defines a set of commands and instructions to ensure the infrastructure achieves the end result.

On the flip side, the declarative approach declares the ideal outcome. Rather than provide a clear sequence of steps required for the infrastructure to reach the end result, the declarative approach demonstrates how the final result may look like.

Best practices

To gain maximum value from IaC strategy, here is a short list of best practices:

Code – the single source of truth: All infrastructure specifications in configuration files must be clearly coded. The config files must be the single source of truth for all concerns pertaining to infrastructure management.
Version control all configuration files: All configuration files must be put under source control.
Little to no documentation for infrastructure specifications: Because all configuration files must be the single source of truth, no more documentation is necessary. Also, external documentation may be out of sync with real configurations, which will not be the case with the configuration files.
Test and monitor configurations: Like all code, IaC can and must be tested. With the help of testing and monitoring tools, errors and inconsistencies in the servers can be checked before they are deployed to production.

Key benefits of IaC

Adopting the Infrastructure as a Code offers several key benefits to enterprises.

Speed

IaC enables to set up the entire infrastructure within a short turnaround time by running a script. This can be accomplished for every environment from development up to the stage of production. It goes through staging, quality assurance (QA) and more. It also helps improve the efficiency of the complete software development lifecycle.

Accountability

Because one can version their IaC configuration files like a source code file, they get complete traceability of the changes suffered by each configuration. This eliminates any chance of guessing who did what and when they did it.

Consistency

Manual infrastructure management has the potential to result in discrepancies. Infrastructure as a Code helps resolve the issue by having configuration files be the single source of truth. By doing so, the same configurations are going to be deployed time and again, thus eliminating any chance for discrepancy.

In addition, infrastructure deployments with IaC are repeatable and also help avoid runtime issues caused by missing dependencies or configuration drift.

Efficiency during software development cycle

By employing IaC, the infrastructure architecture can be deployed in multiple stages. This improves the efficiency of the entire software development cycle, thus improving the team’s productivity as well.

Programmers could leverage IaC to build and release sandbox environments, enabling them to build in isolation securely. Likewise, QA professionals would have accurate copies of production environments to run their tests.

And, when it’s time for deployment, infrastructure and code can be pushed to production in one step.

Low cost

Reducing the costs associated with infrastructure management is one of the key benefits of Infrastructure as a Code. Costs are also greatly reduced by employing cloud computing with IaC because organizations don’t have to spend on hardware, hire people to manage it, or rent out a physical space to store it.

Organizations can also save costs by employing effective automation strategies that free up engineers from performing manual, error-prone tasks.

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Conclusion

Infrastructure as a Code is a critical part of the DevOps movement, too. DevOps teams can work with an integrated set of practices and tools to launch applications and offer their supporting infrastructure quickly, securely and scale. If cloud computing is deemed to be the first step in solving the issues pertaining to manual IT management, IaC is perhaps the next step. IaC also helps realize the full potential of cloud computing, freeing developers and others from performing manual, laborious tasks. In addition, it reduces costs and improves the efficiency of the overall software development cycle.

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Month: July 2021

Infrastructure As A Code: All You Need To Know