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How to monitor NVIDIA GPU metrics with Elastic Observability

Graphical processing units, or GPUs, aren’t just for PC gaming. Today, GPUs are used to train neural networks, simulate computational fluid dynamics, mine Bitcoin, and process workloads in data centers. And they are at the heart of most high-performance computing systems, making the monitoring of GPU performance in today's data centers just as important as monitoring CPU performance.

Testing the new Elasticsearch cold tier of searchable snapshots at scale

The cold tier of searchable snapshots, previously beta in Elasticsearch 7.10, is now generally available in Elasticsearch 7.11. This new data tier reduces your cluster storage by up to 50% over the warm tier while maintaining the same level of reliability and redundancy as your hot and warm tiers.

Top 5 SIEM trends of 2021 and how Elastic Security solves them

Security information and event management (SIEM) systems are centralized logging platforms that enable security teams to analyze event data in real time for early detection of targeted cyber attacks and data breaches. A SIEM is used as a tool to collect, store, investigate, and report on log data for threat detection, incident response, forensics, and regulatory compliance.

How to monitor Amazon ECS with Elastic Observability

With an increasing number of organizations migrating their applications and workloads to containers, the ability to monitor and track container health and usage is more critical than ever. Many teams are already using the Metricbeat docker module to collect Docker container monitoring data so it can be stored and analyzed in Elasticsearch for further analysis. But what happens when users are using Amazon Elastic Container Service (Amazon ECS)? Can Metricbeat still be used to monitor Amazon ECS? Yes!

Explore and analyze your deployment costs within Elastic Cloud

We are excited to announce the new Elastic Cloud usage analysis page. You can now explore and analyze your Elastic Cloud usage to better understand how the resources you consume contribute to your monthly bill. Your Elastic Cloud monthly bill consists of usage fees for the resources you used, including: Understanding your resource utilization allows you to make smarter decisions about your Elastic deployments as well as identify areas where you may be able to save costs.

Creating a Day of Week Runtime Field and Using It in Kibana

The video contains a demonstration of the creation of a runtime field in which the day of the week is calculated from a timestamp field that contains the date. A visualization is then created in Kibana Lens using an indexed field and the newly created runtime field. Runtime field is the name given to the implementation of schema on read in Elasticsearch.

Shadow an Indexed Field With a Runtime Field to Fix Errors

The video contains a demonstration of using a runtime field to fix errors in the indexed data. We intentionally index documents with some errors, and then use a runtime field to shadow the indexed field. The demonstration shows how a user querying the data or creating a visualization in Kibana Lens will see the correct information, which is calculated in the runtime field. This scenario allows for immediate fixing of errors in the indexed data by shadowing them with runtime fields (instead of reindexing). Runtime field is the name given to the implementation of schema on read in Elasticsearch.

Istio monitoring with Elastic Observability

Istio is an open source service mesh that can be used by developers and operators to successfully control, secure, and connect services together in the world of distributed microservices. While Istio is a powerful tool for teams, it's also important for administrators to have full visibility into its health. In this blog post, we'll take a look at monitoring Istio and its microservices with Elastic Observability. As the Istio docs mention.

Dynamically Created Runtime Fields

The video contains a demonstration of the creation of an index template that defines that unknown fields will be created as runtime fields. Documents are then indexed into an index that inherits from that template, and because these documents contain fields that are not defined in the template, the fields are automatically created as runtime fields (i.e. these fields are usable for search and aggregation, but are not indexed). Runtime field is the name given to the implementation of schema on read in Elasticsearch.