Operations | Monitoring | ITSM | DevOps | Cloud

Edge computing has become a clear strategic goal for many enterprises, for some it is already an absolute necessity. As the demands of applications software and the capabilities of hardware continue to grow, containers and Kubernetes have become a compelling technology for edge computing. In just the past 5 years, the way that software is manufactured and maintained has changed dramatically with the introduction of Kubernetes container orchestration.

Cloud computing optimization is a growing priority, as engineering becomes more accountable for justifying growing AWS spend. Companies that are rapidly growing can be particularly vulnerable to large fluctuations in cloud spending, which often seem to strike without rhyme or reason. Getting a handle on cloud cost is a critical first step toward cloud computing optimization, and can result in more efficient and effective systems across the board.

Kubernetes is THE buzzword these days. Almost every IT organization is currently using it or is in the process of implementing it as part of their infrastructure. The transition to Kubernetes is complicated, whether a company is using an on-premises, cloud, hybrid, or managed solution, and it usually involves other changes in the codebase, such as shifting to a microservices architecture. While the implementation phase is led by the DevOps team, it requires the participation of the whole R&D group.

It’s 3am, and you’re woken up by frantic calls and messages from users at your company—this is the everyday life of a sysadmin. Constantly surrounded by numerous tickets and persistent users who require immediate solutions, the life of a sysadmin is not a bed of roses. Their tasks are not limited to server management, maintenance, and repair, but also completely supporting a smoothly running production environment with minimal or no complaints from end users.

Serverless computing is the latest, greatest thing in the technology world. Although the serverless concept has been around in one form or another for more than a decade, the introduction of serverless platforms from major cloud providers—starting with AWS Lambda in 2014—has brought serverless mainstream for the first time.

Application performance monitoring (APM) dovetails nicely with infrastructure monitoring, allowing you to monitor app performance and end-user satisfaction in context with the rest of your infrastructure. That’s why we unveiled Datadog APM to complement our infrastructure monitoring platform and provide full-stack observability.

Logs provide invaluable information about issues you need to troubleshoot. In some circumstances, that may mean that you have to look back at old logs. For example, you may be running a security audit and need to analyze months-old HTTP request logs for a list of specific IP addresses over a period of time. Or you might need to investigate why a scheduled service never occurred, or run an exhaustive postmortem on incidents that happened over a couple months but that you suspect are related.