Operations | Monitoring | ITSM | DevOps | Cloud

The Elastic Common Schema (ECS) defines a common set of fields for ingesting data into Elasticsearch. A common schema helps you correlate data from sources like logs and metrics or IT operations analytics and security analytics. Further information on ECS can be found in the official Elastic documentation, GitHub repository, or the Introducing Elastic Common Schema article.

In 2010, cloud computing just started to lead the IT revolution. It’s 2020 and the cloud is already mainstream. If you’re not running your business in virtual yet, you’re missing out on huge profit opportunities and capabilities that the cloud has to offer. Adopting a cloud strategy brings better security, increased stability and overall greater flexibility for your organization.

Howdy Splunkers, I’m back and this time I’m packin’ a serious punch. I’m so excited to announce the availability of my new IT Service Intelligence (ITSI) Content Pack for Monitoring and Alerting.

When an application in a Docker container emits logs, they are sent to the application’s stdout and stderr output streams. The container’s logging driver can access these streams and send the logs to a file, a log collector running on the host, or a log management service endpoint. In this post, we’ll explain how the driver you choose—and how you configure it—influences the performance of your containerized application and the reliability of your Docker logging.

Elastic Cloud on Kubernetes (ECK) is an operator that allows you to automate the deployment of the Elastic Stack — including Elasticsearch, Kibana, and Elastic APM, Elastic SIEM, and more — using Kubernetes. By using this ECK, you can quickly and easily deploy Elasticsearch clusters with Kubernetes, as well as secure and upgrade your Elasticsearch clusters. It is the only official Elasticsearch operator.

When talking about log management, search history is overlooked more often than not. Past searches can be used as part of log analysis and forensic analysis, but the main issue with this data is the speed of search which gets compromised as data volume gets greater. We will discuss some ways to get the best out of your saved searches and to speed up the search process.

AWS has a lot of services, and they all generate logs. A lot of logs. We’ve worked hard to make sure you can capture logs from every source and service on AWS, and today we’re happy to announce the final piece of our AWS logging puzzle: LogDNA’s S3 Collector integration. It’s an easy-to-use Lambda function that lets you ingest any AWS logs that get dumped to S3 – like logs from CloudFront and ELB.

This is the one post I hope you’ll never need. However, should you ever need it, this is your one-stop shop for understanding how to proceed with DevOps incident management. Have you just been attacked? Did the commit go wrong? A CI pipeline went haywire? Don’t worry. I got you.

As a company leader, what value are you extracting from your business and IT? What about from security data lakes and processes? Are you able to drive speed for your business because of real-time, advanced analytic capabilities? Successful companies are making technology architecture their business architecture—aligning stakeholders, processes, data, and analytics in an integrated fashion to deliver faster, data-driven decisions that are more accurate than ever before.