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The latest News and Information on Log Management, Log Analytics and related technologies.

The 7 Essential Metrics for Amazon EC2 Monitoring

Amazon EC2 offers a flexible and convenient way to run virtual machines in the cloud. With dozens of EC2 instance types available, as well as multiple pricing options, it’s easy to use EC2 to configure the best cloud-based virtual machines for your needs and budget. One thing that EC2 doesn’t make very easy on its own, however, is monitoring.

Making the Collection of Centralised S3 Logs into Splunk easy with Lambda and SQS

Got multiple AWS data sources in the same S3 bucket but struggle with efficient SNS notifications based on prefix wildcards? Well, struggle no more, we’ve got your back. Many of our customers have a centralised S3 Bucket for log collection for multiple sources and accounts. For example, all Config, CloudTrail and Access Log logs may be routed into one central bucket for an organisation.

Why the CEO Cares About Splunk

Evolving business themes come at us in waves. So far this millennium we have had The New Economy, The Cloud, and now Digital Transformation. Underpinning these themes are real, economically significant dynamics that drown out the bleating voices of pundits and cynics alike. The Internet is not a bubble, the cloud is not a fad, and digital transformation is, well, transformative. Let’s take a look at what that last one means for Financial Services.

Reduce Monitoring Costs: How to Identify and Filter Unneeded Telemetry Data

To understand what’s going on in their environment, DevOps teams usually ship some combination of logs, metrics and traces—depending on which signals they’re hoping to monitor. Each data type will expose different information about what is happening in a system. However, not all of that information will be helpful on a day-to-day basis, which can rack up unnecessary data storage costs. That should require users start to filter telemetry data across their observability stacks.

See the Forest from Your Logs | IBM Logging Solution Log Analysis with LogDNA

IBM Log Analysis with LogDNA is an IBM Cloud service that provides hosted log management using LogDNA. It lets you collect, analyze, and manage logs in a central location without having to provision or maintain your own logging solution. You can forward logs from your IBM Cloud Kubernetes clusters, servers, and applications in as little as three steps. In addition, you can leverage the IBM Cloud to manage the service, set access controls via IAM, and even archive older logs to IBM Cloud Object Storage. When you provision an IBM Log Analysis with LogDNA instance, you get access to a LogDNA endpoint and web UI hosted on the IBM Cloud. Your logs are stored on the IBM Cloud itself, allowing you to colocate your logging service and applications for greater throughput and control. You get the full benefits of LogDNA—including fast log ingestion and searching, over 30 integrations and ingestion sources, and support for dozens of log formats—with the security and convenience of the IBM Cloud.