May 29, 2020 When you have millions of customers dependent on your connectivity & communication services performing with best possible efficiency, having network downtime because of any device failure is totally unacceptable. One of our customers is a proprietary global telecommunications vendor which designs, builds as well as manages data networks for telecoms all around the world.
The shift to cloud infrastructure does not remove the need for infrastructure management and administrators but rather necessitates a shift in their responsibilities. Cloud infrastructure has grown to be a ubiquitous part of the modern software industry. This is an amazing growth when you realize that Amazon did not announce Amazon Web Services, starting with Elastic Cloud Computing (EC2), until 2006.
If you want to jump straight to installing the marketplace extension, you can find it here. Performance issues can quickly turn expensive. Reasons can vary from unexpected traffic surges, pieces of non-performant code acting as bottlenecks, or misconfigured network components. Integrating load- and performance testing into your CI pipeline will allow you to know about performance degradations early, in most cases, even before it has any impact on your users in the production environment.
On July 15th the Codefresh registry that is part of all Codefresh accounts will be removed from service. The removal is part of a big round of improvements to our native integration with Docker registries. We have invested significant efforts in using Codefresh as a unified platform for Docker images and the way they are used inside CI/CD pipelines. More details on the migration actions for the Codefresh registry can be found in our timeline announcement.
Cybersecurity incidents are the norm of the day. No organization has impunity. When a cybersecurity incident occurs, incident responders have to immediately respond to contain the incident and mitigate the damage. To this end, they have to execute the Incident Response Processes (IRP). Doing it manually is expensive and time-consuming and also less effective if your organization is facing too many incidents on a weekly or monthly basis.
As a manager handling a team of employees who go on-site and resolve customer issues related to your product/service, buying field service management (FSM) software to help you manage the workload of your team is critical—especially as your business scales and the team grows. However, such a purchase decision will often require management buy-in. The management needs to completely understand the ROI associated with such a product.
It’s probably true to say that if you asked an average user what makes a great web application, they’d probably say “speed.” But speed is the probably the least important aspect of an extensive rundown of elements. Factors like application development and rendering in the program are probably higher on that list. And what makes up a great performing application? And when something goes wrong, how do you know?
Alert management is no longer a manageable task, given the growth in applications, cloud environments and point monitoring tools. Too much time is spent filtering and making sense of alert data and determining where to route incidents. All of these steps slow down critical issue identification and resolution. In this article, I want to discuss a more sensible, modern way to deal with IT alerts, through machine learning intelligence and automation.
