The latest News and Information on Log Management, Log Analytics and related technologies.
Over the past few years, we’ve seen an almost obsession with developing and adopting CI/CD tools throughout the DevOps community. There are thousands of “how-to’s”, “top x tools”, and “tool x vs tool y” type articles, and it has gotten to the point where it’s quite difficult to figure out how and which one to pick as your own.
Like everyone else, my life for the last few months has become a never-ending stream of video calls. With Zoom calls, and the occasional Skype, Google Meet, or Microsoft Teams, becoming the norm I’ve noticed that the fans on my Macbook have been kicking in and sounding like a tiny jet trying to take off.
Isn’t all logging pretty much the same? Logs appear by default, like magic, without any further intervention by teams other than simply starting a system… right? While logging may seem like simple magic, there’s a lot to consider. Logs don’t just automatically appear for all levels of your architecture, and any logs that do automatically appear probably don’t have all of the details that you need to successfully understand what a system is doing.
In this post, we will cover some of the main use cases Filebeat supports and we will examine various Filebeat configuration use cases. Filebeat, an Elastic Beat that’s based on the libbeat framework from Elastic, is a lightweight shipper for forwarding and centralizing log data. Installed as an agent on your servers, Filebeat monitors the log files or locations that you specify, collects log events, and forwards them either to Elasticsearch for indexing or to Logstash for further processing.
More people than ever are working remotely, and about one-third say the coronavirus pandemic was their first chance to do so. As companies return to a new normal, they are considering how to manage workers who are not in the office, and mobile workers add a unique challenge. The term “remote worker” includes work-from-home employees and mobile workers. Most employees who work remotely do both.
AWS Lambda enables you to run serverless functions in the AWS cloud, by manually triggering functions or by creating trigger events. To ensure your Lambda functions are running smoothly, you can monitor metrics that measure performance, invocations, and concurrencies. However, even if you continuously monitor, once in a while you are going to run into what’s termed a Lamba cold start. There are various ways to prevent AWS Lambda cold starts.