Articles tagged with
gcp
19 Dec 2024
Many companies face the challenge of efficiently processing large datasets for analytics.
Using an operational database for such purposes can lead to performance issues or, in extreme cases, system failures.
This highlights the need to transfer data from operational databases to data warehouses.
This approach allows heavy analytical queries without overburdening transactional systems and supports shorter retention periods in production databases.
10 Mar 2023
Hardware is always hard. The amount of operations, maintenance and planning that goes into supporting a data center
is a daunting challenge for any enterprise. Though often unseen, without hardware there is no software.
28 Jun 2021
Some time ago, our team faced the issue of moving an existing Apache Spark job from an on-premise Hadoop cluster to public cloud.
While working on the transition we came across another way to process data that is Apache Beam. We were curious whether this tool had
more advantages in comparison to traditional Apache Spark. We wanted to find the answer relatively quickly with minimal effort. Hence, we built two projects to
process the same data using these technologies. Below you can get to know the architecture of the jobs written in Apache Spark and Apache Beam.
04 Nov 2020
We are excited to announce that we have just released BigFlow 1.0 as open source.
It’s a Python framework for big data processing on the Google Cloud Platform.
27 Jan 2020
Configuration management is one of the key challenges you have to face when you decide to build an application as a distributed system based on microservices
deployed to the Cloud. There are multiple ways of addressing different aspects of this problem, using several tools such as Spring Cloud Config Server
or Hashicorp Consul. However, this article will focus on the tools that Google Cloud Platform offers
out of the box. The approaches mentioned should be seen as complementary rather than mutually exclusive.
