At this year’s AWS reInvent, we heard Andy Jassy go on stage to announce a bunch of new services to help companies unleash the power of cloud. 27 new services to be exact - everything from Machine learning IDE, to code review tools to contact center offerings (see the full list here); last year, AWS announced another 30 new services ranging from machine learning to VR/AR to satellite data. So now AWS has over 175 services - a staggering count by any imagination.

A few blogs posts ago I wrote about new BI for digital companies and in that blog I alluded that quite a bit of that BI is based on log data. I wanted to follow up on the topic of logs, why they exist and why they contain so much data that is relevant to BI. As I said in that post, logs are an artifact of software development and they are not premeditated, they are generated by developers almost exclusively for the purpose of debugging pre-production code. So how is it that logs are so valuable for BI?

In this three-part series, we will take a hard look at Amazon’s Elastic Kubernetes Service: how it helps organizations run Kubernetes on AWS, what insights can be gained in EKS and how it’s monitored, and finally, how organizations can get the most out of EKS with the help of Sumo Logic. For the first installment, we’ll learn how it works and how organizations can get started with Amazon’s Elastic Kubernetes Service.

With 2020 around the corner, we’re entering a new decade in the cybersecurity landscape. What does the future hold for security professionals? We’d like to ring in the new year with good news, but the truth is that hackers will become smarter and breaches will grow in scale and number, creating an even greater pressure for security teams to keep up. Read our five predictions for 2020 to understand what to look out for and how to prepare for the new decade.

Kubernetes has become the de-facto solution for container orchestration. While it has, in some ways, simplified the management and deployment of your distributed applications and services, it has also introduced new levels of complexity. When maintaining a Kubernetes cluster, one must be mindful of all the different abstractions in its ecosystem and how the various pieces and layers interact with each other in order to avoid failed deployments, resource exhaustion, and application crashes.

If you are reading this, I don’t have to convince you any further of the powerful intelligence we can derive from logs and machine data. If you are anything like the many, many users, customers and prospects we have been talking to over the years, you might, however, have some level of that pesky modern condition commonly known as volume anxiety. The volume here, of course, is the volume of data––there is a lot of it, and it keeps growing.

Today's IT and DevOps teams have not one, but two, feature-rich open source Web servers to choose from: NGINX and Apache HTTP Server (which is often called simply "Apache"). At a high level, both platforms do the same core thing: Host and serve Web content. Both also offer comparable levels of performance and security. Yet when you dive into the details, you'll find that there are many differences between NGINX and Apache.

The last fifteen years have seen huge increases in developer productivity for several reasons, including the arrival of open source into the mainstream and the ability to better emulate target environments. In addition, the process of resetting a development environment back to the last known stable version has been vastly improved by Vagrant and then Docker.

For nearly 10 years, AWS and Sumo Logic have been the perfect pairing for businesses going through their digital transformation journey. AWS provides the best technology to help companies with their digital transformation, while Sumo Logic provides continuous intelligence and insights to monitor, run and secure those applications on AWS.

We are excited to announce the beta release of Sumo Logic’s Archive Intelligence Service, which enables customers to forward logs directly from Sumo Logic’s installed collector to their own, self-managed AWS S3 buckets. This service gives users the ability to reliably gather and economically store log data which may not be needed for immediate analysis or operations, but is still important to keep for later use.