Filters
Reset allAll
All
All

Understanding if your applications are not just available but also functioning as expected is critical for any organization. Infrastructure monitoring and application observability alone are often not enough to reliably predict the actual end user experience which can be significantly impacted by factors such as third-party dependencies and different end-user device types. By simulating real user interactions, synthetic monitoring can help you proactively identify issues with your business-critical applications and infrastructure before they impact end-users.

Financial institutions have vast amounts of data about their customers. However, many of them struggle to leverage data to their advantage. Data may be sitting in silos or trapped on costly mainframes. Customers may only have access to a limited quantity of data, or service providers may need to search through multiple systems of record to handle a simple customer inquiry. This creates a hazard for providers and a headache for customers.

As an MSSP, there are certain nuances and challenges that you may have which are not typically present in a traditional security operations team. It's important to have the right tools available to you to overcome any obstacle and provide the best experience and outcome for your customers.

Discover how automotive giant Ford Motor Company centralizes Elastic Cloud operations to support a variety of search and analytics needs across the organization. This allows teams to easily provision new clusters on-demand on Google Cloud and use Elastic for multiple use cases, from building internal search applications, to monitoring their cloud infrastructure, to enabling search and analysis of large datasets like vehicle telemetry.

Discover how automotive giant Ford Motor Company centralizes Elastic Cloud operations to support a variety of search and analytics needs across the organization. This allows teams to easily provision new clusters on-demand on Google Cloud and use Elastic for multiple use cases, from building internal search applications, to monitoring their cloud infrastructure, to enabling search and analysis of large datasets like vehicle telemetry.

See how Randstad Netherlands uses all the features of the Elastic Stack to monitor their environments on AWS and put their analysts first. Randstad NL, an Elastic user since version 1.7, combines events from applications, systems and third party tooling into their Elastic Stack to detect and mitigate threats at scale — all from within Elastic Security.

- Defining priority use cases, workflow integrations, operational metrics, and more to deliver incremental value

- Defining priority use cases, workflow integrations, operational metrics, and more to deliver incremental value

Google Kubernetes Engine (GKE) is a managed Kubernetes environment by Google Cloud Platform (GCP), offering many services and delivery mechanisms to support a wide variety of deployment types. Autopilot removes many challenges associated with workload management, deployment automation, and more so you can focus on building and deploying your application while Google Cloud manages everything else.

Companies are increasingly running applications across multiple cloud environments for their needs. The reasons driving this vary - from flexibility, to access to best of breed solutions across providers, to downstream end customer choices that may necessitate the use of a specific provider for a specific client need. But across these underlying reasons, there is a growing need to easily deploy and operate across multiple cloud providers.

As the global economy slows down, organizations continue to migrate to the cloud to deliver more reliable services and applications. Running them efficiently and cost-effectively has never been more important. And the need for observability and to do more with less is a high priority for technology leaders.

Accelerate security investigations with machine learning and interactive root cause analysis in Elastic
Comprehensive security requires multiple layers of threat protection. Sophisticated threats exploit idiosyncrasies in your environment. Unsupervised machine learning identifies patterns of normal activity from your data, and therefore can catch attacks that standard approaches to threat hunting, such as pre-defined rules, are likely to miss.

As the global economy slows down, organizations continue to migrate to the cloud to deliver more reliable services and applications. Running them efficiently and cost-effectively has never been more important. And the need for observability and to do more with less is a high priority for technology leaders.

The highest priority for any organization operating in the cloud is data protection. But security is not just the responsibility of cloud providers alone. Organizations need to understand the shared responsibility model, and their role in securing their valuable IP, to avoid compliance chaos.