In theory, the default monitoring check settings should work in the majority of cases. However, everyday practice shows that our case does not belong to this majority. Therefore, it is necessary and worthwhile to dedicate some time to the optimal configuration of monitoring. It is also important to properly prepare the monitored website and the organization itself.
In order to have the most successful deployment, there are a few best practices that software development teams should be mindful of. First, following a continuous delivery approach allows software development teams to release in shorter cycles, so that building, testing, and releasing can be done with greater speed and reduced error rates.
Untangling a chaotic mess can be daunting. And that’s exactly the problem Alain Adler, the Head of Engineering at BetterHelp, faced.
Continuous Integration and Continuous Delivery (CI/CD) delivers services fast, effectively, and accurately. In doing so, CI/CD pipelines have become the mainstay of effective DevOps. But this process needs accurate, timely, contextual data if it’s to operate effectively. This critical data comes in the form of logs and this article will guide you through optimizing logs for CI/CD.
Microservice architecture is widely popular. The ease of building and maintaining apps, scaling CI/CD pipelines, as well as the flexibility it offers when it comes to pivoting technologies are some of the main reasons companies like Uber and Netflix are all in on this approach. As the amount of services in a microservice architecture rises, complexity naturally also rises.
Elasticsearch is a complex piece of software by itself, but complexity is further increased when you spin up multiple instances to form a cluster. This complexity comes with the risk of things going wrong. In this lesson, we’re going to explore some common Elasticsearch problems that you’re likely to encounter on your Elasticsearch journey.
The modern enterprise has expanded its reach by using the power of cloud computing. However, with that power comes complexity in leveraging the multiple platforms needed to provide rich functionality. To achieve a seamless integration that involves multiple cloud infrastructures you need insightful and actionable data. You also need the right team to bring the clouds together in a seamless, effective, and efficient manner.
Few industries have experienced such a disruptive whiplash as the financial services industry. With the dizzying encroachment of agile, innovative, and fearless fintechs coming to the fore, traditional banking institutions have had to completely rethink their business, revenue models, and customer engagement initiatives.
As organizations build out their serverless footprint, they might find themselves managing hundreds or thousands of individual components (e.g., Amazon S3 buckets, Amazon DynamoDB tables, AWS SQS queues) for just a single application. At the same time, performance issues can crop up at any of these points, which means that having access to detailed observability data from your serverless functions is crucial for effective troubleshooting.
