In the webinar, Expert Insights: Navigating Outages Like a Pro, Howard Beader, VP of Product Marketing at Catchpoint, interviewed Howard Holton, the CTO and Lead Analyst at GigaOm. The two Howards delved deep into the critical subject of Internet Resilience and its significance in today’s digital age. Here’s a recap of the key takeaways.

Software development, agility and efficiency are paramount. Continuous Integration and Continuous Deployment (CI/CD) practices have revolutionised the way we build, test, and deploy software. When coupled with the power of Kubernetes, an open-source container orchestration platform, organisations can achieve a level of deployment excellence that was once only a dream.

When it comes to choosing the right AWS container optimization solution, building a DIY suite of free optimizer tools may seem like a great idea, but will it provide everything you need? The hidden, total cost of ownership (TCO) for open-source tools can quickly build up, making it a less manageable option when compared to a third-party optimizer. Our helpful list of what you need to consider will help you decide which AWS container optimization solution is right for you: a DIY toolset or a managed suite.

Syslog is a standard for sending and receiving notification messages–in a particular format–from various network devices. The messages include time stamps, event messages, severity, host IP addresses, diagnostics and more. In terms of its built-in severity level, it can communicate a range between level 0, an Emergency, level 5, a Warning, System Unstable, critical and level 6 and 7 which are Informational and Debugging. Moreover, Syslog is open-ended.

Do you want to build software faster and release it more often without the risks of negatively impacting your user experience? Imagine a world where there is not only less fear around testing and releasing in production, but one where it becomes routine. That is the world of feature flags. A feature flag lets you deliver different functionality to different users without maintaining feature branches and running different binary artifacts.

Technological advancements in telecommunications are keeping everyone on their toes, as communication service providers (CSPs) obsess over the next big thing to roll out and change the way the world communicates, stays informed, manages its daily lives, and more.

Amazon SageMaker is a fully managed service that enables data scientists and engineers to easily build, train, and deploy machine learning (ML) models. Whether you are integrating a personalized recommendation system into your video streaming application, creating a customer service chatbot, or building a predictive business analytics model, Amazon SageMaker’s robust feature set can simplify your ML workflows.

To find out more about cloud migrations, the pitfalls that await the unwary, and what the security implications are, I recently sat down with Dustin Dorsey, Systems & Data Architect at Biobot Analytics, based in Cambridge, MA. In the first post in this series, we talked about cloud providers being responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud.

Apache Tomcat, developed by Sun Systems way back in the late 1990s, is a popular choice for developers who need to build and deploy Java-based web applications. It’s a collaboratively created platform that, since 2005, has become an accredited top-level Apache project with highly experienced developers volunteering support and resources for it. A 2022 survey shows that 48% of developers now utilize Apache Tomcat for deploying Java web applications.

When people think about reliability, it’s easy to focus on incident response and moving fast to fix outages. This reactive approach to reliability can very quickly lead to burnout as you bounce from incident to incident. But that’s not the only way to think about reliability.