Businesses around the world are increasingly moving their application hosting to the cloud to leverage its unique combination of flexibility, scalability and cost efficiency. And Amazon Web Services or AWS has come to personify the cloud for many companies.
As the first and the largest provider of all types of cloud hosting, AWS is a clear choice for many companies working to divest their internal data centers and IT-heavy corporate infrastructure.
While many new application development projects start off on AWS in the first place, most enterprises continue to have a large catalog of legacy applications still in active use. It’s time-consuming and resource-intensive to redevelop those apps from scratch. However, a better option may be to engage a professional consulting firm like Trianz to migrate quickly and effectively to the AWS platform.
AWS is so popular for cloud hosting that most executives do not require additional convincing. By moving day-to-day operations to the cloud, AWS hosting allows both IT and business leaders to focus on core processes and key differentiators. AWS makes it easier with a fully developed platform that addresses the full spectrum of technical issues required in the cloud services.
Services for every use case - AWS has been around for long enough to provide the full set of services in one package to handle all your IT needs. With the ability to keep both processing and data services in the same cloud infrastructure maintenance, management and future development are all simplified and accelerated on AWS.
Hybrid capabilities for dual hosting - For companies that do not want to or cannot move applications entirely into the cloud at once, AWS offers an expanded array of hybrid hosting options that allow you to mix the best of on-prem and cloud application hosting, however you see fit.
Best-in-class security services - With hosting services trusted by the Defense Department and U.S. Government agencies, Amazon has demonstrated at the highest level that their platform security for cloud-hosted applications is second to none. Your data and code will always remain safe in AWS instances.
Global presence and perspectives - Amazon has the most extensive array of global hosting zones for application computing power, which means that your apps run on-demand with minimal lag irrespective of the location of your employees. All the while, they can be centrally managed from your IT operations center for maximum coordination and efficiency.
Although both cloud services in general, and AWS in particular, are easy choices, the path to application migration may give some companies pause. That’s why it makes sense to find a trusted migration partner with hands-on AWS experience to lead you through the process.
Trianz starts the migration process with a big picture view. Our industry-focused professionals have extensive experience not only with the AWS platform itself but also with every industry vertical. We understand regulatory concerns, unique processes and category risks that specifically apply to your business and concerns.
Our consultants are AWS-certified with sound technical knowledge, communication skills and business competencies. That means you can always rely on us to keep you in the loop and base decisions off, both IT demands and business outcomes.
Our transformation framework can combine both, off-the-shelf code and native development to ensure the best possible fit for your applications in the AWS paradigm and you don’t have to make hard choices between custom development and total migration. get in touch to discuss your specific migration requirements.
Contact Us Today
Connecting more people to data has become imperative for organizations worldwide. In Top Trends in Data & Analytics for 2022, Gartner stated, “Connections between diverse and distributed data and people create truly impactful insight and innovation. These connections are critical to assisting humans and machines in making quicker, more accurate, trustworthy, and contextualized decisions while considering an increasing number of factors, stakeholders, and data sources.”Explore
Since the dawn of business, users have looked for three main components when it comes to data: Search | Secure| Share. Now let's talk about the evolution of data over the years. It's a story in itself if one pays attention. Back then, applications were created to handle a set of processes/tasks. These processes/tasks, when grouped logically, became a sub-function, a set of sub-functions constituted a function, and a set of functions made up an enterprise. Phase 1 – Data-AwareExplore
Practitioners in the data realm have gone through various acronyms over the years. It all started with "Decision Support Systems" followed by "Data Warehouse", "Data Marts", "Data Lakes", "Data Fabric", and "Data Mesh", amongst storage formats of RDBMS, MPP, Big Data, Blob, Parquet, Iceberg, etc., and data collection, consolidation, and consumption patterns that have evolved with technology.Explore
Enterprises have, over time, invested in a variety of tools, technologies, and methodologies to solve the critical problem of managing enterprise data assets, be it data catalogs, security policies associated with data access, or encryption/decryption of data (in motion and at rest) or identification of PII, PHI, PCI data. As technology has evolved, so have the tools and methodologies to implement the same. However, the issue continues to persist. There are a variety of reasons for the same:Explore
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore