Are you taking a leap of faith and anticipating the best by defining your data migration scheme?
Imprecise evaluation has led to the overproduction of several data migration projects. Mountain climbers would know that no two mountains are alike with reference to the course of path and movement. Similarly, no two migrations are the same. Hence, initializing with a data migration strategy is crucial for any enterprise to ensure seamless movement throughout their project.
Are the two complementing each other or is one found as a substitute for another?
The usage of the data collected increases as the type and volume of data accumulated from all enterprises inflate.
However, majority of the collected data are a possible set of interactions among the systems and stakeholders, out of which very few have been identified by the enterprises as they have not had a chance to experiment the data.
Hence, the concept of data lake has been chosen to concentrate in such a scenario. This blog emphasizes on the comparison between data lake and data warehouse…
A case study where we implemented CI/CD with Kubernetes.
Continuous building, testing and delivery of iterative codes increases the speed of the Software Development Lifecycle (SDLC), i.e., when a developer writes a code, it is automatically deployed to the respective environments enabling them to test the functionality themselves, and submit the build to the testing team for an elaborated testing. Notably, with the advent of a new release the entire process recurs.
There are three primary steps involved in continuous software development, i.e., from the source code to production:
· Continuous Integration (CI)
· Continuous Deployment (CD)
· Continuous Delivery…
Kubernetes, an open-source extensile platform used to manage the workloads and services that are containerized, is known for its service discovery, load balancing, automated mounting of storage system, automatic roll outs, and bin packing, self-healing and sensitive configuration management.
The version of the Kubernetes to be run on the control plane nodes and the worker nodes is to be known while creating a novel Kubernetes cluster using the Container Engine. Kubernetes version is generally represented as x.y.z where, x refers to a major release, y to a minor release, and z to a patch release. The latest minor release of…
The data warehouse architecture as we know it today will wither in the coming years and be replaced by a new architectural pattern, the Lakehouse, which will be based on open direct-access data formats, such as Apache Parquet, have first- class support for machine learning and data science, and offer state-of-the-art performance.
The history of data warehousing started with helping business leaders get analytical insights by collecting data from operational databases into centralized warehouses, which then could be used for decision support and business intelligence (BI). …
As we travel through the AI era, efficient handling of data has been time-consuming and unmanageable. Notably, a process oriented automated methodology, named as DataOps, has aided the data and analytic teams with quality data and quicker data analytics. DataOps, which is a prerequisite for the success of an enterprise, has also proven to assure security, repeatability and scalability.
A data management methodology that controls the agile, seamless and fast processing of data from the input to the results is referred to as DataOps or Data operations. DataOps combines Agile methodologies, DevOps and statistical process controls (SPC), and applies them…
Kubernetes or K8s is an open-source system used to automate deployment, management of containerized applications, and scaling. This system aims to group containers to make an application into logical units that allow for easier management and discovery. With 15 years of experience running production workloads at Google, Kubernetes gives you the accessibility of utilizing on-premises, hybrid, or public cloud infrastructure. As useful as Kubernetes is, actually using it is tricky, which is why one must know the most efficient way of deploying and managing it to optimize the value it can bring to your organization.
While you can use other…
Mohan is the co-founder and director of engineering at HiFX, helping organizations leverage the power of cloud and big data analytics.