Systems | Development | Analytics | API | Testing

How To Build Scalable and Resilient Microservices | Microservices 101

Building scalable and resilient microservices requires an approach that eliminates the need to treat them as special. They should be treated as easily replaceable building blocks. This means eliminating bottlenecks and single points of failure but it can also mean changing from a pull-based approach to a push-based approach. CHAPTERS.

Confluent's Customer Zero: Building a Real-Time Alerting System With Confluent Cloud and Slack

We talk a lot about how customers can use Confluent as the data backbone for event streaming applications and enable a new class of event-driven microservices by completely decoupling services from one another. With Confluent, organizations can rapidly build and deploy business applications with greater flexibility, support larger scale, and be more responsive to customer demands. But we don’t just talk about it, we do it ourselves as Confluent’s “Customer Zero”!

From Reporting to Decision Science: Inside HP with Juergen

You’ve heard the term data science, but have you heard about decision science? Juergen Kallinger, VP of Data and Insights at HP, shares valuable insights and reflections from his 22-year journey at HP. In this episode, Juergen dives into HP’s pivotal shift from solely reporting, to the dynamic realm of decision science and how it’s aligned their data team.

How to Increase Data Reliability in Construction

Between soaring material costs and the impact of inflation, the construction industry has had to practice extra agility and resilience in recent years. Market upheaval, including skills shortages and supply chain disruptions have made financial reporting in the construction industry even more challenging. Manually exporting data into static spreadsheets adds another roadblock–when reports are manually exported or input, information grows stale quickly.

Top Data + AI Predictions for the Public Sector in 2024

Governments collect more data than any other type of entity on the planet, yet their ability to use data to serve citizens more effectively has always been limited. Regulatory compliance, budgetary constraints, reliance on legacy systems and internal resistance to change all play a role. That’s why when it comes to adopting new technologies, public agencies tend to lag behind the private sector by 18 to 24 months—and often longer.

Keboola Pronounced Leading Solution in Europe by G2

At Keboola, our aim has always been to put the customer first. We strive to be the best self-service data operations platform for companies, so they can get the most out of their data and grow their business fast and smart. Being perfectionists we tend to focus on what’s still not good enough and needs improving.

Easily Train, Manage, and Deploy Your AI Models With Scalable and Optimized Access to Your Company's AI Compute. Anywhere.

Now you can create and manage your control plane on-prem or on-cloud, regardless of where your data and compute are. We recently announced extensive new orchestration,scheduling, and compute management capabilities for optimizing control of enterprise AI & ML. Machine learning and DevOps practitioners can now fully utilize GPUs for maximal usage with minimal costs.

Choosing the Right API: REST vs. RESTful for Integration

Choosing between REST API vs RESTful API is pivotal for efficient and scalable business solutions in data integration. Application Programming Interfaces (APIs) are critical in data integration, enabling diverse systems to communicate and data exchange seamlessly. In this landscape, REST (Representational State Transfer) APIs have emerged as a standard, known for their simplicity and effectiveness in handling network requests.