Our team of Kubernetes Certified (KCSP) engineers has worked on all the major cloud platforms on projects ranging from cloud native applications, DevOps, data engineering, chatbots, natural language processing, machine learning all built on top of Kubernetes with a focus on data.
TEKStack Kubernetes Technology Stack is a collection of Kubernetes platform tools, best practices and processes driven by clients’ needs and requirements.
Supported by open source and production-ready.
TEKStack platform tools are built from the ground up to support your enterprise data-driven applications. Save time and money by using TEKStack tools for your next project. TEKStack can be used for your new project or expand your current offerings; support your entire data journey, from inception to insights to successful customer engagements.
TEKStack tools are built on the foundation of Kubernetes to make your business in the cloud faster, more secure, and scalable. TEKStack saves you money by delivering your application to the end user more quickly. Our DevOps features support your enterprise applications by monitoring and reacting to your application’s needs in real-time. With TEKStack, continuous integration and continuous delivery, we can integrate and automate pipelines.
Our TEKStack platform tools draw their strength from the people that support them. Our human expertise creates applications that best leverage your data while drawing on ML technologies – this approach puts your applications ahead of what the very best have to offer. The platform tools accommodate an end-to-end ML lifecycle, with a particular focus on data engineering, data ingestion and pre-processing smart data lake design, and lightweight ML pipelines. Our data journey expertise allows us to automate elements of the ML pipeline in ways that make it easier to create assets, which in turn allows us to address a greater range of customer challenges.
TEKStack applies natural language processing (NLP) technologies to our enterprise search solutions, with the goal of creating faster and improved database search. This allows for context-dependent search results, more informed insights, and faster business decision-making. We first process information from the databases we ingest into our platform, then tag information based on their type (name entity recognition). We then leverage this information to produce enterprise search solutions that are easier to use, and more informative than traditional full-text search options.
TEKStack platform tools include a scalable, multi-model data lake that supports any and every database best suited for the data type ingested into our platform. These databases are consolidated in a way that centralizes and simplifies data security and governance, and defines the source of truth for the datasets. The data lake is “smart”, in that it contains metadata that describes itself, which can be efficiently queried using a built-in data catalog. The data catalog allows users a greater ability to identify their data of interest across a number of different databases quickly, without the need to enlist help from a database expert.