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.
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.
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.
When thinking about serverless applications, one thing that comes to mind immediately is efficiency. Running code that gets the job done as swiftly and efficiently as possible means you spend less money, which means good coding practices suddenly directly impact your bottom line. How does logging play into this, though? Every logging action your application takes is within the scope of that same performance evaluation.
Two years ago we introduced Splunk Insights for AWS Cloud Monitoring and Splunk Insights for Infrastructure on the AWS Marketplace as a Pay-As-You-Go Amazon Machine Image, where you could initiate an instance and pay hourly to use these products after a 15-day trial. Assessing our portfolio, we are discontinuing these offerings to focus on differentiating capabilities, namely the ability to search and apply machine learning to your data in addition to visualizing insights.
You may be surprised to learn that a particular malware is responsible for data theft in over 20% of financial institutions and other verticals in 2019. Watering hole attacks involve a web server that hosts files or applications where the website or files on the site become weaponized with malware. While recent news cycles have shined a spotlight on ransomware and crimeware, malware is not a new concept.
Cloud environments like AWS can be a challenge for security monitoring services to operate in since assets tend to dynamically appear and disappear. Making matters more challenging, some asset identifiers that are stable in traditional IT environments like IP addresses are less reliable due to their transient behavior in a cloud service like AWS. Amazon GuardDuty protects your AWS environment with intelligent threat detection and continuous monitoring.
Logging is a critical component of your cloud infrastructure and provides valuable insight into the performance of your systems and applications. On Google Cloud, Cloud Logging is a service that allows you to store, search, monitor, and alert on log data and events from your Google Cloud Platform (GCP) infrastructure services and your applications. You can view and analyze log data in real time via Logs Viewer, command line or Cloud SDK.
