For decades, information technology in the financial services industry meant deploying bulky applications onto monolithic systems like mainframes. These systems have a proven track record of reliability, but don’t offer the flexibility and scalability of more modern architectures such as microservices and cloud computing. During periods of unexpectedly high demand, this inflexibility can cause technical issues for organizations ranging from personal trading platforms to major banks.

Managed Service Providers (MSPs) in IT have the unenviable task of hastening the digital transformation in companies, especially during these trying times. It becomes even more onerous, considering that the hardest-hit segment of Small and Medium Businesses (SMBs) are their major customers. According to the Global State of the MSP report, cloud migrations and security are expected to be the top drivers of MSPs growth for MSPs in 2020.

Want to ensure a smooth migration to the cloud? Read on to learn about what you need to do before and after to chart a clear course for success.

Calico was designed from the ground up with a pluggable dataplane architecture. The Calico 3.13 release introduced an exciting new eBPF (extended Berkeley Packet Filter) dataplane targeted at those ready to adopt newer kernel versions and wanting to push the Linux kernel’s latest networking capabilities to the limit.

Today, we are excited to share the first in a series of Employee Experience (EX) focused eBooks, helping you understand how Catchpoint can be used to ensure you get the best digital performance for your employees. In this eBook, we focus on five use cases, demonstrating through examples, how to best utilize digital experience monitoring for G Suite.

When SUSE, the world’s largest independent open source company, announced its acquisition of Rancher Labs in early July 2020, the industry took notice. Clearly, the Kubernetes management industry is very much alive. But, the merger also raised the question of what this means for users? After all, a key value proposition of cloud native technologies, like SUSE, is that they are modular, interoperable, and flexible.

Pandora FMS has become well known as a reliable, flexible advanced network monitoring solution. It allows businesses of all sizes to monitor and manage network and hardware issues in real time, and integrates all of the monitored terminals, servers, and other entities into a centralized system. These features mean that Pandora FMS has become the go-to choice for small businesses looking to deploy advanced network monitoring technologies for the first time.

With the increasing popularity of Python web frameworks supporting asynchronous I/O like FastAPI, Starlette, and soon in Django 3.1, there has been a growing demand for native async I/O support in the Python Elasticsearch client. Async I/O is exciting because your application can use system resources efficiently compared to a traditional multi-threaded application, which leads to better performance on I/O-heavy workloads, like when serving a web application.

This post is the third in our Kubernetes observability tutorial series, where we explore how you can monitor all aspects of your applications running in Kubernetes, including: We’ll discuss using Elastic Observability to perform application performance monitoring (APM) with the Elastic APM.

Customers regularly ask me what types of data sources they should be sending to their SIEMs to get the most value out of the solution. The driver for these conversations is often because the customers have been locked into a SIEM product where they have to pay more for consumption. More log data equals more money and, as a result, enterprises have to make a difficult choice around what log sources and data are what they guess is the most important.