Everyone hates waiting in a queue. On the other hand, when you’re moving gigabytes of data around a cloud environment, message queues are your best friend. Enter Apache Kafka. Apache Kafka enables organisations to create message queues for large volumes of data. That’s about it – it does one simple but critical element of cloud-native strategies, really well.
The world has been on a tough break these past few months. With countries talking about defeating the COVID-19 Pandemic, but contemplating infection fears again, we are experiencing a new normal that has all of us second guessing what we know about life as-of-now. This ambiguity is most visible, when we are discussing business.
As companies decide whether or not to move ahead with an “everything in the cloud” strategy for providing consumer-facing applications, enterprise applications are also getting a new shape with web-based applications to support internal business operations. These applications live inside the private network of the organization and often have role-based access.
In a factory environment, collecting data to gain useful insights from various sources is challenging because it requires connecting to many different types of automation systems, plcs and devices that often speak different languages. This is the problem that German industrial software company, inray (specialized in data communication between software systems and components in Industry 4.0, IoT and IIoT) set out to solve for its customers.
More people than ever are working remotely, and about one-third say the coronavirus pandemic was their first chance to do so. As companies return to a new normal, they are considering how to manage workers who are not in the office, and mobile workers add a unique challenge. The term “remote worker” includes work-from-home employees and mobile workers. Most employees who work remotely do both.
You’ve created the perfect design for your indices and they are happily churning along. However, in the future, you may need to reconsider your initial design. Maybe you want to improve performance, change sharding settings, adjust for growth. Whatever the reason, Elasticsearch is flexible and allows you to change index settings to improve your Elasticsearch Performance Tuning. Let’s see how to do that!
AWS Lambda enables you to run serverless functions in the AWS cloud, by manually triggering functions or by creating trigger events. To ensure your Lambda functions are running smoothly, you can monitor metrics that measure performance, invocations, and concurrencies. However, even if you continuously monitor, once in a while you are going to run into what’s termed a Lamba cold start. There are various ways to prevent AWS Lambda cold starts.
